In this article, we will focus on the different stages of television innovation over time and the way these changes have created the advertising systems we know today.

The post The Evolution of Television and the Rise of Advertising appeared first on Clearcode.

But here’s the thing: the DSP and the bidder are slightly different. The DSP encompasses a comprehensive system with various components and features and serves as the platform for advertisers to purchase and oversee digital advertisements, whereas the bidder’s role is bidding on ads according to the advertiser’s specified targeting parameters.

When it comes to using or offering a DSP, companies can either build one, rent one, or buy one. This decision is important from a strategic point of view, as it involves different costs and effects, but not every company has the same opportunity; i.e., for some companies, the only choice will be to build a DSP, whereas others might be better off renting or acquiring a DSP.

In this blog post, we’ll discuss the pros and cons of building a bidder or a DSP for advertisers, brands, and tech companies.

Key Takeaways

• A demand-side platform (DSP) is an advertising technology platform that allows advertisers to buy ad space from publishers in real-time, targeting specific audiences.
• DSPs emerged in 2007 with the introduction of real-time bidding, allowing advertisers to procure ad space from multiple publishers at once.
• The features of a DSP include ad campaign optimization tools, integrations with ad exchanges, supply-side platforms (SSPs) and data platforms, analytics and reporting modules, and a user-friendly interface.
• A bidder is a key component of a DSP. It uses algorithms to place bids on ad impressions based on the advertiser’s targeting criteria, ensuring the acquisition of valuable impressions at optimal cost.
• The key features and requirements of an RTB bidder include modularity, speed, reliability, scalability, and efficiency.
• Companies have three options when it comes to using a DSP: building one from scratch, renting an existing one, or buying and customizing an existing platform.

What Is a Demand-Side Platform (DSP)?

A demand-side platform (DSP) is an advertising technology (AdTech) platform where advertisers buy ad space on an impression-by-impression basis from publishers via ad exchanges and supply-side platforms (SSPs). 

DSPs will integrate with dozens of different ad exchanges and SSPs to increase an advertiser’s chances of reaching their target audiences.

A DSP is like a stockbroker for ad space, where advertisers and agencies buy ad inventory from publishers just like investors buy stocks from companies.

The emergence of DSPs dates back to 2007, when real-time bidding first appeared, allowing advertisers to buy ad inventory on an impressions-by-impression basis across numerous publishers.

Despite being perceived as existing for the singular purpose of buying available ad space, DSPs include various components to manage, deliver, optimize, and report on ad campaigns. 

These components include:

• Ad campaign optimization elements, such as budgeting, campaign tracker, and bidder.
• Integrations with ad exchanges, SSPs, and data platforms.
• Analytics and reporting modules that provide comprehensive data and analytics to advertisers and ad agencies, allowing them to optimize their RTB purchases based on insights from previous ad buys.
• User-friendly interface for properly creating, managing, and optimizing ad campaigns.

An essential feature of DSPs is their ability to leverage data from data management platforms and other sources to improve ad targeting and optimize media purchases. Through these insights, advertisers can run campaigns more effectively, reaching their target audience with increased precision.

What Is a Bidder?

A bidder is a key component of a DSP that is responsible for making real-time bidding decisions on behalf of advertisers. Essentially, it incorporates algorithms that place bids on ad impressions based on various parameters and targeting rules the advertiser sets.

When a user visits a website, an ad impression opportunity is created and sent to an ad exchange. The ad exchange then auctions off this ad impression to DSPs. 

The bidders within DSPs evaluate the ad impression based on the advertiser’s predefined criteria, such as audience demographics, the user’s browsing history, and time of day. After evaluating the bid request, the bidder determines the value of the impression and places a bid accordingly.

This entire process, from the moment the user visits a website to the placement of the ad, happens in milliseconds, which is why it’s known as real-time bidding (RTB). The goal of the bidder is to win impressions that are most valuable to the advertiser while ensuring cost-effectiveness by bidding the optimal amount to win the ad space without overpaying.

Key Features and Technical Requirements of an RTB Bidder in a DSP

A bidder is a critical component of a real-time bidding (RTB) system in digital advertising. 

Here are the key features of an RTB bidder:

1. Modularity and customizable algorithms: A bidder supports various modules and adaptable bidding algorithms. These modules can ascertain factors like the publisher’s URL and the user’s location. Additionally, the bidding algorithms can adjust bidding behavior based on certain criteria, such as bidding higher for specific URL categories or pacing bids to avoid exhausting the entire budget at the campaign’s onset.
2. Speed and reliability: Given that most ad exchanges mandate a bid response latency of less than 125 milliseconds, bidders are built to receive and respond to bid requests before being timed out. They are located in the same data center as the ad exchange in order to respond to the bid request in time. The architecture of these bidders is designed to be asynchronous so that they can maintain rapid response times even when interacting with third-party services. Bidders also need to maintain high performance.
3. Scalability and efficiency: Bidders need to be scalable and operate efficiently to maximize the use of resources. A balance should be struck between optimizing the bidder for performance and using additional hardware resources. During peak Internet traffic periods,  leveraging cloud computing enables server resources to be scaled appropriately.

Now, let’s look at the pros and cons of building your own RTB bidder or DSP.

Pros and Cons of Building a DSP or a Bidder for Tech Companies

Determining the optimal approach for integrating a DSP into your digital advertising strategy involves carefully considering various factors. For tech companies, the sole viable option is building a custom DSP. At the same time, brands, agencies, and other enterprises can choose between building, renting, or buying based on their business objectives.

Building a DSP from Scratch

Creating a DSP from the ground up is a daunting task, but it comes with several potential advantages. However, this approach is best suited to companies with existing tech (e.g., AdTech companies) or ad agencies with a substantial media budget that can secure the necessary technical expertise for the maintenance and development of the platform.

Advantages of Building a DSP

• No markup on media:  Cut out the middleman and save on commissions.
• Intellectual property ownership: Building their own DSP adds to a company’s asset portfolio.
• Control over data: The company retains full ownership and control over their data, ensuring no third-party access.
• Control over DSP features: The agency has the flexibility to design and modify features based on their specific needs.

Disadvantages of Building a DSP

• High costs: Building a DSP from scratch involves significant upfront and ongoing expenses.
• Long development cycle: It takes time to develop a functional DSP and start running campaigns through it.
• Learning curves: Understanding the intricacies of a custom-built DSP can be challenging.
• Maintenance and infrastructure costs: These are recurring expenses that are unavoidable.
• Connection with SSPs and ad exchanges: Establishing relationships with supply-side platforms (SSPs) and ad exchanges is an additional challenge that requires resources and can be particularly daunting for inexperienced developers.

For tech companies, building a custom DSP is the only route available. The unique technical capabilities and innovative ethos of tech companies position them to take full advantage of developing a DSP tailored to their specific needs. While this endeavor necessitates significant investment and expertise, the rewards include complete control, data ownership, and the opportunity to refine the DSP’s features over time.

One of the major challenges in building a DSP is securing seats at the major ad exchanges. As a newcomer, you may lack the credibility or purchasing volume required to earn these seats initially. However, if you have existing relationships with supply-side platforms and ad exchanges, then it is a matter of handling the technical side of the integrations.

Alternatives to Building a Custom DSP

If building a DSP from scratch is not feasible, there are other alternatives that offer similar benefits.

One alternative is to build a meta-DSP. 

A meta-DSP is a piece of software that sits on top of existing DSPs andhelps manage and automate campaign design, targeting, trafficking, and reporting across various DSPs.

In contrast to a standard DSP, a meta-DSP typically doesn’t engage in media buying itself. Instead, the DSPs linked to the meta-DSP handle media buying through RTB auctions.

The primary function of a meta-DSP is to provide brands and advertising agencies with the capability to create, configure, and oversee multiple campaigns across diverse DSPs using a single user interface.

A meta-DSP evaluates the distinct targeting capabilities and inventory sources of the connected DSPs. It can also select the most appropriate DSP for procuring a specific impression, guided by the campaign’s KPIs.

Summary

The choice between building, renting, or buying a DSP comes down to your company’s budget, technical capabilities, and specific business needs. Each option comes with its own set of pros and cons that need to be carefully considered before making a decision.

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The post Pros and Cons of Building Your Own RTB Bidder or DSP appeared first on Clearcode.

Players from various industries, such as retail, media and entertainment, telecommunication, and gaming, are deciding to build their own DSPs. In this blog post, we cover their main reasons for developing this AdTech platform.

Key Points

• A demand-side platform (DSP) is an AdTech platform for ad buyers (brands and ad agencies) to purchase ad inventory on an impression-by-impression basis.
• DSPs are connected to ad exchanges and supply-side platforms (SSPs) and enriched with data from data platforms like data management platforms (DMPs) and customer data platforms (CDPs).
• Advantages of DSPs include automated ad buying, scalability, cost-effectiveness, and precise audience targeting.
• Key market drivers for DSPs are the demise of third-party cookies, new and emerging digital channels, the development of new ad formats, a focus on contextual and content-driven advertising, and regulatory compliance.
• Companies can enter the DSP market by acquiring an existing DSP, renting one, or building their own.
• Reasons companies want to build their own RTB bidder or DSP include capitalizing on first-party data assets, cutting costs on media, gaining autonomy, and addressing measurement challenges. Building a DSP also allows companies to optimize their demand path, avoid exchange bias, occupy niche verticals, and gain new clients with ad fraud detection and other security mechanisms.
• As the advertising industry experiences significant growth, companies from various industries are exploring the potential of building their own DSPs. Among new entrants, retail, telecommunications, publishing, media, and entertainment are the leading industries.

What Is a Demand-Side Platform, and What Is It For?

A demand-side platform (DSP) is an AdTech platform for ad buyers such as brands and ad agencies to purchase ad inventory on an impression-by-impression basis. The buyers can set the advertising campaigns and programmatically bid to purchase precisely targeted video ads, display ads, in-game ads, etc. 

To run and complete the buying process, DSPs are connected to:

• SSPs and ad exchanges to purchase ad inventory.
• Data management platforms (DMPs) to provide a more detailed view of customers and create more personalized marketing messages.
• Customer data platforms (CDPs) to track and manage the customer journey more effectively.

The most common way DSPs buy available ad space on websites and apps is via real-time bidding (RTB). The RTB process is a live auction whereby DSPs bid on impressions offered by ad exchanges and supply-side platforms (SSPs).

The Key Functionalities of a DSP

DSPs enable brands and advertisers to streamline the procurement of ad impressions across various supply sources. By automating the process, they enhance efficiency and precision in targeting the intended audience while managing costs effectively.

Some DSPs also leverage artificial intelligence and machine learning to enhance their functionality. While not all DSPs incorporate these technologies, a subset employs AI and ML techniques to optimize ad placement and pricing. These tools analyze data patterns and user behavior to guide advertisers towards optimal ad placements, ensuring they reach individuals who are most likely to engage and convert.

In other words, DSPs facilitate the intricate task of purchasing ad impressions across diverse platforms, and when coupled with AI and ML capabilities, they can potentially elevate the accuracy and impact of advertising efforts.

For that reason, DSPs:

• Manage ad inventory: Advertisers can set up ad campaigns, buy ad inventory from various publishers, and optimize the performance of their campaigns through a single user interface.
• Track campaign performance and optimize campaigns in real time: DSPs offer advanced tracking and analytical tools, allowing advertisers to monitor ad performance, make data-driven decisions, and optimize campaigns in real time.
• Bid in real time: DSPs work in conjunction with supply-side platforms (SSPs) to enable real-time bidding across multiple ad exchanges, enhancing access to quality ad spaces.

The Key Advantages of a DSP

DSPs enable automated ad buying, thus freeing up marketers’ time and resources that were previously spent on manually negotiating with publishers. 

In addition to automation, DSPs have a few other general advantages:

• Scalability: DSPs offer greater access to various forms of ad inventory because of their connections to SSPs and ad exchanges.
• Cost-effectiveness: Through real-time bidding and automated decision-making processes, DSPs can optimize costs by determining the most suitable bid for an ad in real time.
• Targeting specific audiences: With the help of data, AI, and ML, DSPs facilitate the targeting of specific audience segments across a range of publisher sites, allowing for more precise and effective advertising campaigns. For instance, targeting options may include behavioral, lifestyle, demographic, device, audience lookalikes, in-market audiences, contextual, and retargeting.

Key DSP Market Drivers

The DSP landscape is influenced by several factors — from the growing amount of first-party data to the demise of third-party cookies and strict privacy regulations. 

Although these factors will have a negative impact on how DSPs have been working up until now, DSPs will need to evolve to help advertisers navigate this new world — e.g., by allowing them to utilize their first-party data for ad targeting.

Below, we explain the current major reasons behind the ever-changing market and the role DSPs can play.

The Demise of Third-Party Cookies

Although the demise of third-party cookies in web browsers is negatively impacting the DSP market and the AdTech market more broadly, there are many opportunities for existing companies to update their existing DSPs and for new entrants to enter the space to provide solutions to this challenge.

Third-party cookies have been a crucial tool for audience targeting and retargeting in digital advertising. With their phasing out due to privacy concerns and regulatory changes, advertisers are actively seeking alternative targeting solutions. 

DSPs can capitalize on this need by offering sophisticated targeting capabilities that leverage first-party data and alternative identifier solutions and technologies, such as UID 2.0, FLEDGE, and Topics API.

New Ad Formats Development

Since the very first display ad in 1994, new ad formats have emerged and taken over the digital space on computers, mobile devices, audio services, and television. Wherever the audience is — in games, on TV, on retail sites, etc. — ads are sure to follow. 

DSPs aim to buy ads precisely targeted at specific audiences, whether these are in-game ads, native ads, social ads, etc. And these platforms do it close to real-time. Advertisers can rely on the dynamic that DSPs give them in terms of running modern ad campaigns.

Focus on Contextual and Content-Driven Advertising

With the limitations on individual user tracking, contextual advertising is gaining importance. Contextual targeting displays ads based on the content of the web page rather than user data. DSPs that can effectively leverage contextual targeting and dynamic content optimization will likely see increased demand from advertisers who want to reach relevant audiences in a privacy-friendly manner.

Regulatory Compliance and Ad Verification

As ad environments become more complex, advertisers are increasingly concerned about brand safety and ad fraud. DSPs that offer robust ad verification tools and ensure brand-safe placements will be preferred by advertisers seeking to maintain a positive brand image and maximize campaign effectiveness.

Should Companies Build, Rent or Buy a DSP?

To enter the DSP market, a company can build a custom DSP, rent an existing one (e.g., a white-labeled DSP), or acquire a DSP vendor. Each approach has its pros and cons, but there are many advantages for companies that build their own DSPs.

Pros and Cons of Building, Renting, or Acquiring a DSP

Here is the comparison between these options.

Top DSP Companies

As said earlier, the value of the DSP market will reach USD 92.12 billion by 2029. The majority of that number will probably come from the top DSP companies that dominate the global market. Among the largest players are well-known giants such as Amazon, Facebook, and Google. However, the space in the vertical also includes smaller companies.

The Top Reasons Why Companies Want to Build Their Own RTB Bidder or DSP

The decision to construct an RTB bidder or DSP is strategic. Whether driven by cost-efficiency, technological autonomy, or market diversification, the benefits of building a bidder or DSP underscore its role as a tool for companies aiming to thrive in the digital advertising ecosystem.

For Ad Agencies

Saving on the cost of media

By far, this is the biggest reason for building a bidder or DSP — especially for ad agencies. Due to various trends and changes within the online advertising ecosystem over the past decade, the role and position of ad agencies has shifted. Before the introduction of the Internet, ad agencies were a critical component of a brand’s advertising activities, handling everything from creating the ad to delivering it to a publisher’s sales team. 

But towards the late 2000s, when new AdTech companies were coming onto the scene, we witnessed something that we’d never seen before: brands were bypassing the agency and working directly with AdTech companies due to the ease of use these platforms provide. 

As a result, agencies have been playing damage control, working tirelessly to reestablish the value they provide their clients. With this has come a need to cut costs.

And one of the main ways agencies can cut costs is by eliminating the fees they pay to AdTech companies — demand-side platforms in particular. 

Depending on the vendor, some agencies pay between 10% – 30% in commissions. On average, SSPs and DSPs collect 35% of programmatic spend. And, if an agency’s media spend is in the tens of millions of dollars per year, then there’s a significant number of dollars going to DSPs.

Control over tech stack

By building their own RTB bidder or DSP, ad agencies control the tech stack and gain autonomy. This includes the freedom to design and implement tailored features, integrations, and a strategic product roadmap. This heightened control ensures agility and adaptability, enabling the agency to respond to evolving market demands and emerging trends.

By controlling their tech stack, agencies can also avoid the limitations and uncertainties associated with third-party solutions and ensure that the platform is tailored precisely to their unique needs and preferences.

For Tech Companies

For AdTech companies, the decision to build their own DSP is more than a strategic choice — it’s often the only viable path. 

Relying on an existing DSP creates potential issues around competition and relinquishes the control needed over tech stack customization, integrations, and feature development. This essential control grants AdTech companies the ability to fine-tune their offerings and align with their unique value propositions.

Expansion of product offerings

Often renowned for their innovation and technological prowess, tech companies can exponentially expand their product offerings by venturing into the realm of DSPs. A prime example is a server company delving into the creation of a DSP. This strategic expansion not only diversifies the company’s revenue streams but also leverages their existing technical expertise to enter a new market segment. By building their own DSP, tech companies can seamlessly bridge the gap between technology and advertising, providing a comprehensive solution that caters to diverse customer needs.

Benefits of Building Your Own Bidder or DSP for Advertising Operations

Optimizing Demand Path

Building a DSP allows companies to ensure transparency throughout the entire ad delivery chain, eliminating any uncertainty about where their ads are placed and who views them. This newfound transparency builds trust with customers and partners, fostering more fruitful relationships in the long run. An important part of this aspect is demand path optimization (DPO).

Avoiding Exchange Bias

Companies also strive to avoid any bias towards particular publishers or exchanges, seeking complete neutrality in their advertising operations. By building their DSP, they eliminate concerns about undue favoritism and maintain an even playing field for all stakeholders involved.

Occupying Niche Verticals

The realm of AdTech is branching into new territories, including in-game advertising, mobile ads, and streaming TV ads. As AdTech expands its reach, companies can capitalize on these specialized domains by building highly customized DSPs tailored to cater to the specific needs of each niche. This can lead to a higher return on ad spend (ROAS) for their clients.

One example of a company entering the DSP market is MarTech company Zoomd Technologies. In 2021, they built Mobile DSP to deliver mobile RTB-based campaigns across multiple ad exchanges to their clients. Among the many reasons behind their decision were mobile-oriented causes in particular.

Another example is SITO Mobile, a US-based AdTech company that allows advertisers and ad agencies to run location-targeted mobile ad campaigns via its proprietary demand-side platform (DSP).

Enhanced Security and Protection

Advertisers seek platforms that enhance their brand’s security, eliminating the threat of displaying ads in an inappropriate space. At the same time, they want to safeguard their ad budgets from the growing ad fraud phenomenon.

By incorporating protection services, anti-fraud algorithms, dedicated marketplace quality teams, exclusion and inclusion lists, sensitive site blocking, and more, companies that build their own DSP will probably win a piece of the market.

Entering The Expanding AdTech Landscape

As the advertising industry experiences a remarkable surge in global digital ad spending, with projections indicating a 10.5% year-on-year increase in 2023, reaching a staggering USD 696 billion, companies across various industries are waking up to the immense potential of building their own DSPs. The leading industries among new entrants are primarily retail, telecommunications, publishing, media, and entertainment.

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While there are hundreds, if not thousands, of ready-to-use DSPs on the market, it sometimes makes more business sense for a company to build their own custom DSP.

Although the advantages can be substantial, building a DSP demands significant time and financial investments that not every company may fully benefit from this undertaking. However, for certain businesses, developing their own proprietary DSP might be the only viable option to meet their specific needs.

Read this blog post to learn about the process of building a DSP.

What Is a Demand-Side Platform (DSP)?

A demand-side platform (DSP) is an advertising technology (AdTech) platform that enables advertisers and agencies to purchase ad space on an impression-by-impression basis from publishers via ad exchanges and supply-side platforms (SSPs). The inventory can be purchased in real time through a single-user interface. 

With a DSP, advertisers can buy:

• Display ads: These are banners and interactive ads that appear on websites and apps.
• Video ads: These include pre-roll, mid-roll, and post-roll video ads that play before, during, or after online video content.
• Native ads: These are ads that blend seamlessly with the form and function of the platform or website they appear on.
• Mobile ads: These are ads displayed on mobile devices.
• Audio ads: These are ads on audio streaming platforms, podcasts, and internet radio.
• Digital out-of-home (DOOH) ads: These are ads on digital billboards, which are screens in public spaces, transportation hubs, and shopping centers.
• Connected TV (CTV) ads: These are ads delivered through internet-connected smart TVs and streaming devices.
• In-game ads: These are ads placed within video games.

The primary function of a DSP is to purchase ad inventory. However, within the DSP, AdOps can create, run, and manage many ad campaigns simultaneously across multiple SSPs and ad exchanges, increase the ROI of their campaigns via optimization mechanisms, improve targeting by integrating the platform with other data platforms, and analyze the performance of their campaigns with reporting and analytics modules.

How Does a DSP Work?

Advertisers and ad agencies can create, launch, and manage multiple ad campaigns across a variety of supply sources through a single user interface. Most companies have a dedicated team, known as ad operations (AdOps), that is responsible for setting up and managing the ad campaigns inside a DSP. 

The mechanisms and components involved in buying ad impressions encompass real-time bidding (RTB) processes and integrations with SSPs and ad exchanges, as well as the use of bidders and algorithms to process data.

The following video explains the simplified process of creating an ad campaign and buying ad impressions using a DSP, ad exchanges, and an SSP:

Here’s a breakdown of the process in detail:

1. An advertiser establishes campaigns, including targeting criteria, and creatives (ads), within the DSP.
2. Ad exchanges and SSPs notify the DSP about available impressions.
3. The DSP analyzes data associated with the impression.
4. Based on the relevance to the buyer’s target audience, the DSP determines the value of the particular user who will see the ad.
5. The DSP places a bid on the impression, reflecting the maximum amount the advertiser is willing to pay to display their ad to this user.
6. The ad exchange or SSP collects bids from multiple DSPs and selects the highest bidder.
7. If the DSP wins the bid, the ad is served to the user’s device in real time.
8. The DSP continuously monitors and optimizes campaign performance, adjusting bids to maximize ad effectiveness and return on investment (ROI).
9. This process is repeated for each impression, allowing the DSP to reach and engage the desired audience efficiently.

The whole real-time bidding (RTB) process happens as the page is loading; it is completed in roughly 100 milliseconds.

Who Can Benefit From Building a DSP and How

While any company can build a DSP, the companies that have the most to gain are advertisers, ad agencies, and AdTech companies. Developing such a platform presents significant business opportunities, including revenue growth, increased market presence, and — additionally, for the AdTech companies — the ability to offer comprehensive solutions to advertisers.

Moreover, a custom DSP can:

• Help companies reduce the commissions they pay to intermediaries.
• Give companies full control over the product roadmap and ownership of the tech — i.e., codebase and intellectual property (IP).
• Provide companies with more control over their data and the media-buying process.

AdTech Companies

Building a DSP allows AdTech companies to tap into the growing programmatic advertising market. By offering a DSP, they can provide advertisers with a comprehensive platform to manage their ad campaigns, opening up new revenue streams through fees, commissions, and licensing models.

A custom DSP also gives AdTech companies full control over the technology and features offered to advertisers. They can tailor the platform to meet specific market demands, including unique targeting options, advanced optimization algorithms, and customized reporting and analytics capabilities.

Another advantage for independent AdTech companies that want to build their own DSP is the ability to develop strategic partnerships with specific SSPs, ad exchanges, DMPs, and verification partners. This allows them to expand their network, create a unique offer, and reach a broader customer base.

Advertisers and Ad Agencies

The main benefits for advertisers and ad agencies include enhanced control over their advertising campaigns, precise audience targeting, efficient and transparent costs, and increased competitive advantage.

In their case, the platform can be aligned with their unique objectives, preferences, and target audience. This level of control enables advertisers and ad agencies to make real-time adjustments, experiment with different strategies, and incorporate algorithms to optimize their campaigns for maximum effectiveness.

They can also use granular targeting options to reach the right audience at the right time, delivering personalized messages that resonate with their customers.

Regarding cost efficiency and transparency, developing a custom DSP eliminates the reliance on third-party platforms, reducing costs associated with platform fees and intermediaries.

And, finally, building a custom DSP positions advertisers and ad agencies as innovators and industry leaders. They differentiate themselves from competitors by offering unique targeting capabilities, customized features, and seamless integration with their existing technology stack.

Key Features of a Demand-Side Platform (DSP)

When developing a DSP, it’s essential to focus on the most important features of the platform, such as budgeting (aka, an ad banker), bidder, integrations, the user interface, the user profile database, the reporting module, the campaign tracker, and the ad server.

Optimization Features

Well-designed DSPs have modules to maintain ad campaigns, optimize ad targeting, and control spending. These are driven by algorithms and machine learning that analyze performance data, adjust bidding strategies, and allocate the budget toward the most effective placements and audiences, thus automatically optimizing campaigns.

• The campaign tracker is the component responsible for collecting data on campaign performance.
• Targeting options allow advertisers and ad agencies to reach their desired audience precisely based on demographics, location, behavior, interests, and device types.
• The ad banker is the module that prevents overspending. It helps manage and control an advertiser’s media spending during real-time bidding.

Integrations

To work correctly — i.e., access a wide range of ad inventory and data sources — a DSP has to be integrated with SSPs, ad exchanges, and DMPs. These integrations allow advertisers to tap into diverse inventory options, reach various publishers, and leverage insights about their desired audience for precise targeting and retargeting.

Analytics and Reporting

DSPs provide comprehensive analytics and reporting capabilities to monitor campaign performance. This can include reporting in real time and customizable dashboards that visualize all necessary or valuable data.

Main Challenges When Building a DSP

Building a DSP is a complex task that involves many different moving parts, each with their own challenges, such as managing technological complexity, integrating multiple features, and maintaining high-speed performance. Here, we address the most common challenges that we at Clearcode have overcome when building DSPs for our clients.

Maintaining High-Speed Performance and Dependability

The DSP must be reliable and perform well under heavy loads, especially during peak traffic times. Ensuring high performance and uptime requires robust architecture and efficient code, which can be challenging to design and implement. 

Using microservices, where each part of the DSP works independently from the others, or cloud-based architectures, which can easily scale up or down as needed, can often be the most suitable solution to these challenges.

Achieving Scalability

As the user base and data volume grow, the DSP should be able to scale accordingly to handle increased traffic and data processing. Designing a platform with scalability in mind will help ensure the DSP can handle an increase in usage.

Integrating with Other Platforms

To work properly, DSPs must integrate with various ad exchanges, supply-side platforms, and data management platforms. These integrations must be implemented correctly and tested thoroughly to ensure the DSP can respond to the bid requests within the required timeframe.

Optimal Ad Targeting

Implementing sophisticated algorithms for efficient ad targeting and delivering the right ads to the right users at the right time is a challenge. The platform must analyze user data, context, and behavior to make accurate predictions and decisions.

To process vast amounts of data in real time and predict user behavior, personalize ads, and optimize bidding strategies, a range of technologies can be utilized, including, for example, big data technologies, real-time processing systems, machine learning algorithms, AI, cloud technologies, databases, security technologies, and web technologies.

How Can You Design and Build a DSP?

Developing a demand-side platform is a complex process that involves several steps. Below are the phases that we follow at Clearcode to build DSPs, as well as other programmatic advertising software.

Discovery

First, we:

• Gain an understanding of what you want to achieve with your DSP and get a clear project vision. 
• Outline what you’ll need to get your DSP off the ground and identify any potential technical roadblocks related to real-time bidding, ad targeting, and processing large amounts of data. 
• Address possible technical limitations, like making sure your DSP can grow with your business, comply with data privacy laws, and make ad targeting as effective as possible.

Sprint 0

Next, we:

• Pinpoint any unknowns in the DSP project and brainstorm ways to solve them. 
• Choose the key features for the initial version of your DSP (the minimum viable product or MVP) and put together a to-do list (also known as a backlog) of user stories that define these features. 
• Find the best tech tools and design the best setup for efficiently buying ads, managing real-time bidding, and sorting your audience into groups. 
• Get started on the groundwork for your MVP or validate a specific part of the project with a proof of concept (PoC).

MVP Development

This is when we:

• Start bringing your DSP to life, including setting up the front-end and back-end development, getting the infrastructure in place, designing the user interface, and making sure everything works as it should with thorough testing. 
• Launch your MVP to a small group of users or stakeholders, usually made up of advertisers and marketing folks. 
• Get their feedback to help shape the next stage of development, focusing on things like user experience, how efficiently ads can be bought, and what kind of reporting features are needed. 
• Keep an eye on how the platform is performing, making sure everything runs smoothly and dealing with any unexpected problems that crop up.

Post-MVP Development and Maintenance

After the MVP, we:

• Keep working on your DSP in short, focused bursts (known as 2-week sprints) with the aim of adding new or better features each time, like more advanced targeting options or more detailed analytics. 
• Offer ongoing help and maintenance to make sure that the software and infrastructure stays up and running and that any problems are sorted out quickly. 
• If needed, we’ll hand the project over to your team, giving them the documentation and access they need to manage and maintain the DSP.

Examples of Clearcode-Built DSPs

Kanary NEST

Our client, Kanary NEST, partnered with us to build a scalable demand-side platform designed for programmatic media buying in the online display advertising industry.

The main challenges included developing a platform that could handle billions of bid requests and display the data in real time.

To deliver the platform, we blended several technical solutions and coupled them with a user-friendly interface and sharp design elements.

• We architected the system design with horizontal scalability in mind, empowering the platform to manage billions of bid requests daily, despite being built on a limited infrastructure.
• To deliver an ultra-fast platform, we used multiple software development solutions and tools, including Python, Twisted, Redis, Storm, and others.
• To provide marketers with access to the major biddable display advertising inventories, we integrated Kanary with AppNexus and ad exchanges supporting OpenRTB protocols, such as Nexage.

Starting from scratch, we constructed the project and introduced the minimum viable product (MVP) to a select group of beta testers. Their initial feedback guided our enhancements and the platform’s ongoing development. It was showcased at the TechCrunch Disrupt 2013 conference in New York, where it gained significant praise. Later, in August 2014, Kanary NEST was acquired by Gravity4 — an AdTech company based in Silicon Valley.

SITO Mobile

SITO Mobile, a mobile DSP that leverages location-based technology, engaged us to optimize their infrastructure, access a broader amount of inventory, and minimize discrepancies between their SSP partners.

The primary challenges involved gaining access to more extensive inventory and optimizing the infrastructure to increase the number daily impressions the DSP could process. 

Key points:

• We integrated the SITO Mobile DSP with various ad exchanges and SSPs, enhancing its capacity to handle bid requests per second, automating routine tasks, and improving report generation based on tracked events.
• We designed solutions to handle the discrepancies between the DSP and ad exchanges/SSPs by working directly with them to develop custom reporting mechanisms. This action drastically reduced the discrepancies from around 50% to 1%, thereby improving SITO Mobile’s media spend and positively affecting their bottom line.
• For improved platform stability and constant monitoring, we offered SITO Mobile a service-level agreement (SLA) that provided 24/7 monitoring. This resulted in immediate responses to performance issues, proactive avoidance of potential problems, and frequent infrastructure optimizations.

Our partnership with SITO Mobile profited from our vast experience in advertising-technology development, which enabled us to understand the specific needs of the project, engage proactively with other vendors, and recommend solutions based on our knowledge of the online advertising ecosystem.

Ad Banker Case Study

Clearcode developed a distributed budget management tool, referred to as “the ad banker”, specifically for real-time bidding. This tool aids tech firms in avoiding budget overspend and shortening the development timeline when constructing a demand-side platform (DSP). Our benchmark tests found that the ad banker can reduce budget overspending from 37.2% to just 1.2%.

AdTech

The Anatomy Of a Demand-Side Platform (DSP) [infographic]

Mike Sweeney

Feb 27, 2019

AdTech

How We Built the SITO Mobile Demand-Side Platform (DSP) on AWS [case study]

Mike Sweeney

Mar 04, 2020

AdTech

Top Demand-Side Platform (DSP) Companies [Updated in 2024]

Mike Sweeney, +1

Sep 30, 2020

The post How To Build a Demand-Side Platform (DSP) appeared first on Clearcode.

At the same time, users want to receive a personalized advertising experience. This means that AdTech companies must strategically incorporate privacy-enhancing technologies (PETs) to protect user data, maintain their privacy, and deliver targeted ads.

In this blog post, we’ll explore the possibilities that PETs offer for enhancing user privacy.

Key Points

• Privacy-enhancing technologies (PETs) are critical for improving data protection in the AdTech industry by balancing between data privacy and the delivery of a personalized advertising experience. PETs primarily focus on minimizing the collection and use of personal data, as well as the amount of data processed, while maximizing data security to protect consumer privacy.
• Most AdTech platforms can implement a variety of PETs that include differential privacy, secure multi-party computation, techniques for anonymizing personally identifiable information, and solutions that incorporate PETs for secure data sharing (such as data clean rooms).
• Each AdTech platform can leverage different PETs to enhance user privacy.
• AdTech companies like ad networks, DSPs, SSPs, and ad exchanges can utilize PETs such as differential privacy tokenization, homomorphic encryption, secure multi-party computation, federated learning, and pseudonymization.

Please note: For the purposes of this article, we will be using the term privacy-enhancing technologies (PETs) to represent all technologies, techniques, and strategies that improve the quality of data protection.

What Are Privacy-Enhancing Technologies

Deloitte defines privacy-enhancing technologies (PETs) as a broad spectrum of “data privacy protection approaches, from organizational to technological.” PETs seamlessly integrate elements of cryptography, hardware, and statistical methodologies to guard against unauthorized processing or sharing of consumer data. They act as protective measures, ensuring the secure handling of sensitive information.

PETs help ensure data is secure by focusing on three key pillars:

• Minimizing the collection and use of personal data
• Maximizing data security to protect consumer privacy
• Minimizing the amount of data processed

We described most AdTech-related PETs in our previous posts: What are Privacy-Enhancing Technologies (PET) in AdTech and The Benefits of Privacy-Enhancing Technologies (PETs) In AdTech.

The Key Privacy-Enhancing Technologies (PETs) that AdTech Companies Can Utilize

Most AdTech platforms can implement technologies that include differential privacy, multi-party computation, techniques for anonymizing personally identifiable information (PII), and solutions that incorporate PETs for secure data sharing (e.g., data clean rooms). Each piece of technology helps to achieve a different goal, resulting in enhanced data protection for users.

Differential Privacy: Adding Noise to Collected Data

Differential privacy (DP) provides a framework for sharing information about a dataset without revealing specifics about individuals. Differential privacy (DP) techniques introduce statistical noise into the data collected by publishers and advertisers, ensuring that users’ identities remain anonymous while still enabling valuable insights to be derived from aggregated data.

To add some clarity, differential privacy is achieved by incorporating a certain level of randomness into an analysis. 

Unlike conventional statistical analyses that involve calculating averages, medians, and linear regression equations, analyses conducted with differential privacy introduce random noise during computation. 

The “random noise” elements refer to randomized perturbations or statistical variations introduced into data calculations or results, typically through algorithms or mechanisms such as Laplace noise or Gaussian noise. 

As a result, the outcome of a differentially private analysis is not precise but an approximation, and if the analysis is performed multiple times, it may produce different results each time.

Examples of applying DP in the AdTech landscape include:

• APIs created for the Google Privacy Sandbox initiative, which prevent the Chrome browser from sharing identifiable data until it can be combined with many other users’ data points. 
• Apple’s implemented differential privacy in its systems, starting with iOS 10. When users choose to share Diagnostic and Usage Data, Apple applies the principles of differential privacy to safeguard that data. It further applies DP to Web Browsing data.
• Facebook used differential privacy to protect a trove of data it made available to researchers who were analyzing the effect that sharing misinformation has on elections.

Secure Multi-Party Computation (MPC): Safe Data Computing

Secure multiparty computation (MPC) allows two or more parties to perform computations on their collective data without revealing their individual inputs. However, the mathematical protocols of MPC do not attempt to hide the identities of the participants; this can be achieved by adding an anonymous-communication protocol. 

MPC enhances privacy, as parties can gain insights from the combined data set without exposing their private information.

Examples of MPC in the AdTech landscape include:

• Magnite creates synthetic stable IDs using encrypted data to activate the data without accessing the raw datasets.
• DOVEKEY by Google simplifies the bidding and auction aspects of TURTLEDOVE by introducing a third-party KEY-value server. 
• The Interoperable Private Attribution (IPA) initiative by Mozilla and Meta aims to provide a framework for attribution measurement without tracking users.

Anonymization, Pseudonymization, Encryption, and Tokenization Techniques: Replacing Personally Identifiable Information (PII)

Anonymization, pseudonymization, encryption, and tokenization are techniques for replacing PII with non-sensitive information tokens. These tokens are created to “cover” raw data so it isn’t exposed.

The names of the techniques may suggest similarities or differences between them. However, in the context of the AdTech industry, it is important to know the differences.

Anonymization

Anonymization involves the process of transforming data in such a way that it no longer identifies or can be linked to an individual. The goal is to remove any identifying information entirely, making it practically impossible to re-identify specific individuals from the data. 

Anonymization techniques applied in the AdTech industry can include aggregation, data masking, and other methods that significantly reduce the risk of re-identification.

Anonymization is often used by AdTech platforms to:

• Perform statistical analysis
• Conduct basic audience segmentation
• Generate insights

Encryption

Encryption is a security measure that involves transforming data into a coded form — often referred to as ciphertext — that cannot be understood by anyone who doesn’t have the key to decode it.

In the context of AdTech, encryption can be used to secure PII when it is being transmitted between systems or when it’s stored in databases. The encryption ensures that even if the data is intercepted or accessed without authorization, it will remain unreadable and, therefore, useless to the attacker.

Encryption is often used by AdTech platforms to:

• Secure data transmission
• Store data securely
• Protect user privacy
• Comply with data protection regulations

Pseudonymization

Pseudonymization involves replacing or modifying personally identifiable information (PII) with pseudonyms or aliases. The original data is transformed in a way that makes it more challenging to identify individuals directly but still allows for certain types of analysis or processing to be performed.

Pseudonymized data retains the potential for re-identification if the pseudonyms are somehow associated with the original identities.

Pseudonymization is often used by AdTech platforms to:

• Deploy targeted advertising
• Measure campaign effectiveness

Tokenization

Tokenization is a method of substituting sensitive data with unique tokens that have no meaning or value on their own. The technique allows for efficient data processing and storage without revealing actual personal information.

AdTech platforms may tokenize PII, such as email addresses or device identifiers, by replacing them with randomized tokens. 

Tokenization is often used by AdTech platforms to perform:

• Deploy targeted advertising
• Track users
• Measure campaign effectiveness

Data Clean Rooms (DCR): Data Sharing, Targeting, and Measurement

Data Clean Rooms (DCR) are controlled environments that allow multiple processes to be applied to data to protect it. The main purpose of DCRs is sharing and analyzing data without exposing the raw information in order to provide insights while simultaneously safeguarding user privacy.

Currently, the AdTech industry has two main types of DCRs.

The first type is represented by AdTech walled gardens — i.e., Google, Amazon, and Facebook — each of which runs media clean rooms from which they deliver hashed and aggregated data to companies that use their advertising platforms.

The second type is represented by independent AdTech companies, such as LiveRamp, Snowflake, Aquilliz, and Decentriq, that provide companies with ready-to-use data clean rooms to use across different industries and digital advertising channels.

In our interviews with Juan Baron, Director of Business Development & Strategy (media & adv) at Decentriq, and Gowthaman Ragothaman, CEO of Aqilliz, we learned that in the digital advertising space, the most common use cases of DCRs are:

• Media planning
• Retargeting
• Creating audience segments
• Activation
• Measurement
• Providing predictive analytics
• Attribution

Privacy-Enhancing Technologies for AdTech Companies

As mentioned before, the integration of privacy-enhancing technologies within AdTech platforms is a crucial component for ensuring user data protection and adhering to evolving global data privacy regulations. Another benefit of adopting these technologies is providing a competitive edge in a privacy-conscious market.

PETs for Ad Networks

Ad networks have several privacy-enhancing technologies at their disposal to ensure user data protection. 
By using tokenization and differential privacy, ad networks can deliver effective, targeted advertisements while also respecting and preserving user privacy.

Contextual advertising reduces the need for personal data collection by displaying ads on matching websites. Differential privacy prevents the identification of individuals while analyzing reports. And, tokenization replaces sensitive data — e.g., e-mail addresses — with non-sensitive tokens, securing data in case of data breaches and identity theft attempts.

PETs for Demand-Side Platforms (DSPs)

By incorporating data clean rooms, homomorphic encryption, differential privacy, and secure multi-party computation, DSPs can navigate the balance between ad personalization and user privacy.

Data platforms that incorporate PETs, such as data clean rooms, can provide secure environments for data processing and analysis, ensuring that sensitive user information remains protected. 

Homomorphic encryption allows DSPs to perform computations on encrypted data without decrypting it, thereby securing data while still making it usable for ad targeting. 

Similar to ad networks, DSPs can also leverage differential privacy, introducing statistical ‘noise’ into data to prevent the identification of individuals while still allowing meaningful analysis for ad targeting. 

Secure multi-party computation enables data insights from multiple sources without exposing raw data, further enhancing privacy.

PETs for Supply-Side Platforms (SSPs)

Supply-side platforms (SSPs) can also leverage various privacy-enhancing technologies to ensure the safety of user data while optimizing ad space for publishers. By adopting differential privacy, federated learning, and homomorphic encryption, SSPs can effectively protect user data while optimizing ad placements.

To aggregate and analyze user data (e.g., analyze trends and behavior) without infringing on user privacy, SSPs can leverage differential privacy. This technique introduces statistical ‘noise’ into data, thereby safeguarding individual identities.

Federated learning, an advanced machine learning algorithm that enables data analysis and processing on the device it was collected on, can strengthen ad optimization by building more accurate models of serving ads. 

Homomorphic encryption can protect user data while enabling SSPs to build encrypted user profiles. These encrypted profiles can be used to target ads effectively while the underlying user data remains secure and private.

PETs for Data Platforms (DMPs)

Data platforms, including data management platforms (DMPs), customer data platforms (CDPs), and data clean rooms, are central hubs for collecting, integrating, and managing large amounts of structured and unstructured data from different sources. Because of their primary function, they need to maintain user privacy on a high level. 

Both differential privacy and pseudonymization can enhance the process of audience segmentation and data sharing in DMPs. DMPs can use these techniques to create anonymized or pseudonymized user segments, enabling precise ad targeting without compromising individual user privacy.

PETs for Ad Exchanges

Ad exchanges are digital marketplaces for buying and selling ad inventory from multiple DSPs and SSPs where prices are determined through real-time bidding (RTB) auctions. 

Incorporating differential privacy and secure multi-party computation can help protect the sensitive information of users during the bidding process. By adding statistical noise to the data used for bidding, ad exchanges can ensure that bidding does not result in the leakage of sensitive user information.

Other use cases for differential privacy include reports and analytics modules. 

By using differential privacy, data and insights can be displayed in a way that prevents the identification of individual users, thereby enhancing privacy.

Ad exchanges can also utilize secure multi-party computation to match advertisers and publishers based on their respective criteria, without revealing the private information of either party.

PETs for Ad Servers

Ad servers store and deliver ads to websites and apps and provide reports on ad performance. With the technologies and techniques of differential privacy, encryption, and federated learning, ad servers can enhance user privacy significantly.

Differential privacy can ensure that the processes of data analysis do not expose sensitive user information.

Encryption in ad servers secures user data by encoding it into a format that can only be accessed with the correct decryption key.

For ad servers, federated learning allows for data analysis without needing to share the data itself, enhancing user privacy.

Summary

The adoption of privacy-enhancing technologies in the AdTech industry is an important step toward respecting user privacy and ensuring data security. With the correct application of these technologies, platforms can deliver effective advertising while also prioritizing the privacy and security of their users’ data.

Data & Privacy

What are Privacy-Enhancing Technologies (PET) in AdTech?

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May 18, 2023

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The Benefits of Privacy-Enhancing Technologies (PETs) In AdTech

Natalia Figas

Jun 15, 2023

The post 6 Privacy-Enhancing Technologies for AdTech Companies appeared first on Clearcode.

To understand better what other benefits an SSP can bring, we dive deep into the key features of a supply-side platform.

Key Points

• A supply-side platform (SSP) is an advertising technology platform that enables publishers to manage, sell, and optimize their available ad inventory on websites, mobile apps and other digital advertising channels.
• To connect publishers with buyers, SSPs integrate with various demand sources, such as DSPs, ad exchanges, ad networks, and agencies.
• Critical features in an SSP are yield optimization, integrations with demand sources, ad quality controls, header bidding, analytics and reporting, budgeting, frequency capping, and inventory and campaign management.

What Is a Supply-Side Platform (SSP)?

A supply-side platform (SSP) is an advertising technology platform that enables the management, sale, and optimization of publishers’ available inventory on websites and mobile apps. By leveraging SSPs, publishers can tap into real-time bidding (RTB) media transactions, selling display, video, and native ad space to advertisers on an impression-by-impression basis.

Publishers use SSPs to streamline ad operations and maximize their efficiency and revenue potential.

How Does a Supply-Side Platform (SSP) Work?

SSPs have several options for selling a publisher’s inventory. The most popular one, though, is through real-time bidding (RTB) auctions.

The illustration below shows the selling process of ad space with an SSP via RTB.

Here’s an explanation of how an SSP works using real-time bidding:

1. A publisher defines and organizes their available ad space, including formats (display, video, native), ad sizes, and targeting options.
2. Each time the publisher’s webpage loads, an ad request is sent to multiple ad exchanges and sometimes straight to demand-side platforms, either directly from the webpage to an SSP or from the publisher’s ad server to an SSP.
3. Various DSPs would make bids on the impression that the publisher was offering (as seen in the graphic above).
4. The winning bid is then sent back to the website, where the ad is shown to the user.

Key Features of an SSP

When choosing or building an SSP, it is essential to determine the key features that will meet a company’s specific use cases. Below we’ve listed the main SSP functionalities that help effectively manage and optimize programmatic advertising operations.

User Interface

Publishers utilize the user interface to manage campaigns, examine reports, handle payments, and access other SSP capabilities.

The user interface is critical to operating the SSP in an easy and comfortable way.

Analytics

Comprehensive analytics capabilities are essential for publishers to gain insights into their ad performance and make data-driven decisions. 

SSPs provide detailed reports on key metrics such as:

• Impressions
• Clicks
• Revenue 
• Fill rates.

Publishers can leverage these insights to optimize their ad strategies, identify revenue opportunities, and evaluate the effectiveness of their inventory monetization efforts.

Reporting

Publishers can obtain information from SSPs about who is bidding, the price at which their inventory is being purchased, and the amount paid by specific advertisers. This provides deeper perceptions of the value of their inventory for particular advertisers.

Custom Reporting

The custom reporting module allows AdOps to generate tailor-made reports that align precisely with specific requirements. 

Within the reporting module, various typical settings come into play, such as:

• The selection of pre-saved templates. 
• The determination of fixed or dynamic periods. 
• The choice of aggregation periods. 
• The specification of time zones.
• The selection of metrics and dimensions. 
• The application of filters.

Custom reporting modules often include visually appealing charts to enhance the readability of information.

Live reporting

For analyzing data from recent events, AdOps can leverage live reporting. The feature is usually limited by predefined metrics and displays information up to three hours back and with a delay time between the newest and present data of up to one minute.

The module of live reporting also is visually appealing, as the information is shown on charts and in tables.

Header Bidding

Header bidding (HB) allows publishers to offer their inventory to multiple demand sources simultaneously before making the ad call to the ad server. The SSP collects the bids from the demand sources, typically via Prebid, and evaluates them based on factors such as bid price, targeting parameters, ad quality, and publisher preferences. 

The highest bid is selected as the winning bid, and the ad associated with that bid is served to the user. Most SSPs incorporate this feature as they want to maximize revenue for their clients (i.e. publishers).

The benefits of the header bidding in SSPs include:

• Increased revenue as they can pick the best bid.
• Improved fill rates as they sell more ad space.
• More insights as HB provides publishers with bid prices and demand source performance.

The header-bidding feature of an SSP enables publishers to manage their various header-bidding wrappers and demand partners from one user interface.

If you want to learn more about header bidding development, i.e., wrappers, adapters, and reporting and analytics tools, view our presentation and read Q&A With an AdTech Developer: How To Implement Prebid Server.

Yield Optimization

Yield optimization is a variable pricing strategy that uses data analysis and other optimization methods to improve fill rates and sell impressions (CPM) at the highest possible price. For that matter, yield optimization utilizes the following:

• Data analysis,
• Floor prices optimization mechanics,
• Fill rates management,
• First- and second-price auctions.

The feature considers factors such as historical performance, audience behavior, market trends, and advertiser demand.

Ad Quality Controls

Ad quality controls refer to various features inside SSPs, such as ad verification, content categorization, and malware detection. Each of them has a different role and the same aim — to maintain safe ad serving for publishers. This means that proper ads are displayed to the proper audiences, ensuring brand integrity, improving user experience, and safeguarding from fraudulent or malicious ads.

Money lost on ad fraud is getting stronger, and at the end of 2023, it is predicted advertisers to lose $100 billions due to the activity of fraudsters.

Demand Source Integration

In order to allow publishers to connect with a diverse pool of potential buyers, SSPs need to integrate with demand-side platforms (DSPs), ad exchanges, ad networks, agencies, and direct advertisers. Developing communication protocols is a necessary step towards integrations with those multiple demand sources.

Here are the communication protocols utilized in the process of integration SSPs with other platforms:

• APIs.
• Server-to server integrations.
• Software development kits (SDKs).
• Tag-based integrations.

If you want to learn more about SSPs integrations, read our previous blog post How to Integrate a DSP with Ad Exchanges and SSPs.

Budgeting

Budget settings in SSPs serve as a crucial tool for optimization. They enable AdOps to establish limits on traffic for connected publishers and demand sources. 

For instance, AdOps can control the number of requests sent to each demand source based on received responses or revenue generated, ensuring an efficient ratio between revenue and cost.

Frequency Capping

Frequency capping in an SSP limits the number of ad impressions or requests that are passed onto the demand sources for a single user.

When applied to a publisher, it restricts how many times a particular ad is served to a specific visitor on a webpage within a certain period. This setting is often used for safety purposes when an excessive number of ad requests originate from the same user, but also to avoid showing the same user the same ad too many times in a row

Alternatively, when frequency capping is implemented for a demand source, it controls how frequently that source can win an ad request for the same visitor. 

This does not limit the overall traffic from the visitor, but it prevents a single demand source from winning too many ad requests from the same user within a certain period. 

Consequently, this promotes a more diverse distribution of responses from various demand sources as the DSP for the capped demand source would simply not return a bid response once the limit has been reached.

Ad Targeting

To filter out incoming requests with specific criteria, different targeting options are used. For example, certain demand sources don’t want to take part in auctions for visitors from the EU, so it would be a waste of resources to send such requests to this demand source. 

Examples of targeting criteria include:

• Domain
• Appbundle
• App name
• IP
• Country/Region
• Ad size
• Ad type
• Video formats/sizes
• Device
• OS
• Browser
• Content
• key-values

Customizable Macro Support and Override

SSPs often need to deal with a variety of systems, and these systems sometimes don’t align perfectly. This inconsistency can cause AdOps teams some difficulty. 

For this reason, SSP should be able to manually adjust incoming values from supply sources before they are transmitted to the demand side. This means AdOps teams can change certain parameters, like the app bundle or app name, ensuring the most accurate data is passed on.

Another useful aspect of this feature is the ability to define the structure of query parameters on the endpoint URL directly within the user interface. This comes in handy when partners have different requirements. AdOps teams can place placeholders in the URL, which the system then fills with the appropriate values from incoming requests or defined values if overridden.

For instance, suppose an incoming call looks like this:

https://adserver-testing.com/vast/11111?w=[replace_me]&h=[replace_me]&cb=[replace_me]&ua=[replace_me]&uip=[replace_me]&app_name=[replace_me]&app_bundle=[replace_me]&d_model=[replace_me]&d_make=[replace_me]&app_store_url=[replace_me]&device_id=[replace_me]&vast_version=2

The feature allows AdOps to customize the URL as follows

https://tv.springserve.com/vast/99999?w=[WIDTH]&h=[HEIGHT]&cb=[CB]&ip=[IP]&ua=[UA]&app_bundle=[APP_BUNDLE]&app_name=[APP_NAME]&app_store_url=[APP_STORE_URL]&did=[DEVICE_ID]&us_privacy=[US_PRIVACY]&schain=[SCHAIN]

The system will replace the placeholders ([WIDTH], [HEIGHT], etc.) with relevant incoming or defined values, making it much easier to manage ad serving and to meet various partners’ needs.

Inventory and Campaign Management and Optimization

With these features, publishers can gain comprehensive control over their diverse inventory types, including display, video, native, and more. They can easily manage advertiser blacklists and whitelists, set specific IAB categories, and efficiently block undesirable types of ads.

Inventory optimization helps extract maximum value from an available inventory or individual ad slots. 

However, the absence of universal rules requires a nuanced approach, with AdOps experimenting with specific settings tailored to each unique supply-demand connection.

What settings can be optimized?

• Floor price
• Metrics-based optimizations, such as:
  • Opportunity fill vs. request fill
  • Score
  • Response time
  • Fill speed
  • Score speed
  • Opportunity score
  • Opportunity fill speed

What’s the Difference Between an SSP and an Ad Exchange?

Ad exchanges and SSPs collaborate closely, yet they serve different purposes. DSPs and SSPs can work on media transactions through ad exchanges.

The majority of SSPs nowadays do have exchange mechanisms, though, so DSPs may integrate with them directly and buy inventory through RTB auctions. The OpenRTB protocol is used to establish this DSP-SSP connection as well as connections between SSPs, ad exchanges and DSPs.

What Is the Difference Between a Supply-Side Platform and a Demand-Side Platform?

Both platforms operate within the digital landscape. However, they serve different purposes for different groups of users.

A supply-side platform is used by publishers to manage and monetize their ad inventory. It enables publishers to connect with multiple demand sources, such as DSPs, ad networks, and ad exchanges, to sell their advertising inventory.

A demand-side platform is utilized by advertisers and agencies to purchase ad inventory across various publishers and ad exchanges. DSPs allow advertisers to manage their campaigns, target specific audiences, and optimize their ad spend through real-time bidding and programmatic buying.

The table below displays the main differences between the two platforms.

AdTech

What Is a Supply-Side Platform (SSP) and How Does It Work?

Michal Wlosik, +1

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AdTech

The Anatomy of a Supply-Side Platform (SSP) [infographic]

Mike Sweeney, +1

Jun 12, 2019

AdTech

How To Design and Build an SSP and an Ad Exchange

Natalia Figas

Jul 13, 2023

The post Key Features of an SSP appeared first on Clearcode.

SSPs are crucial for publishers, facilitating real-time bidding for display, mobile, and video ads, advancing ad targeting, maximizing revenue, and offering in-depth analytics. 

Ad exchanges, on the other hand, serve as digital marketplaces, bridging the gap between ad buyers and sellers and making real-time transactions possible.

In this article, we will shed light on the roles of SSPs and ad exchanges, explore instances where their development becomes beneficial, and provide a detailed walkthrough on how to design and build these platforms leveraging our extensive industry experience.

Key Points

• A supply-side platform (SSP) is an advertising technology platform digital publishers use to manage, sell, and optimize their advertising inventory. It automates the selling process, connecting publishers to multiple ad exchanges and demand-side platforms (DSPs).
• An ad exchange serves as a platform that streamlines the transaction of accessible ad impressions between advertisers, who bid through DSPs, and publishers, who offer their inventory via SSPs or directly through the ad exchange itself. 
• SSPs and ad exchanges collaborate with each other in ad inventory buying and selling transactions. However, they are responsible for different processes.
• AdTech companies, publishers, brands, e-commerce platforms, and telcos can benefit from building an SSP and ad exchange.
• The key features of an SSP are header bidding, budgeting, frequency capping, ad targeting, macro support and override, inventory and campaign management and optimization, and reporting.
• The main challenges that companies face when building these platforms include scaling the infrastructure to handle changes in traffic volumes, incorporating accurate solutions for header bidding, and respecting privacy regulations and users’ privacy.

What Is a Supply-Side Platform (SSP)?

A supply-side platform (SSP) is an advertising technology platform used by digital publishers to manage, sell, and optimize their advertising inventory (ad space). To streamline the process of selling ads, an SSP’s features include inventory and campaign management, yield optimization, header bidding, and analytics and reporting. SSPs allow publishers to monetize their websites, apps, or other digital platforms.

An SSP connects to multiple ad exchanges and demand-side platforms (DSPs) to maximize the exposure of a publisher’s ad inventory to potential buyers. It’s designed to help publishers get the highest possible ad prices through real-time bidding (RTB) auctions.

What Is an Ad Exchange?

An ad exchange serves as a platform that streamlines the transaction of accessible ad impressions between advertisers, who bid through DSPs, and publishers, who offer their inventory via SSPs or directly through the ad exchange itself.

The metaphor of a stock exchange is often used to describe ad exchanges due to the similarities between the trading processes of media space and stocks.

The whole process is conducted via real-time bidding (RTB).

What’s the Difference Between an SSP and Ad Exchange?

A supply-side platform (SSP) and an ad exchange are crucial components of the programmatic advertising ecosystem, but they serve different purposes. 

An SSP is a platform publishers use to manage, sell, and optimize their available ad inventory. It automates the selling process, connecting publishers to multiple ad exchanges and demand-side platforms (DSPs).

An ad exchange is a digital marketplace where advertisers and publishers buy and sell ad space, often via real-time bidding. It facilitates these transactions, acting as a mediator between the buying and selling parties. 

Ad exchanges connect to multiple DSPs and SSPs, ensuring a vast pool of advertisers and publishers can engage in the buying and selling of ad space.

SSPs are more publisher-focused, while ad exchanges serve both advertisers and publishers.

How Do an SSP and Ad Exchange Work?

An SSP and an ad exchange work together in the AdTech ecosystem, streamlining the buying and selling of digital ad space.

This is how an SSP works:

1. Publishers, such as website owners and app developers, link their digital properties with an SSP. They relay information about their available ad space or ad inventory to the SSP, detailing the size and type of ads they can host and their location on the website or app.
2. The SSP collects this ad inventory data from all its associated publishers and offers it to potential buyers.
3. When a user visits the publisher’s site or app, the SSP sends information about the user and the available ad space to the ad exchange.

This is how an ad exchange functions:

1. The ad exchange receives information about the available ad space and user from the SSP.
2. The advertiser or agency creates the campaign by setting the targeting, ad size etc.
3. The DSP analyzes the bid request and then matches it with the information contained in the ad campaigns created by advertisers and ad agencies.
4. The ad exchange holds a real-time auction for each ad impression. This process usually takes place within the few milliseconds it takes for a webpage to load.
5. The highest bid wins the impression. The ad exchange then coordinates with the SSP to display the winning ad on the publisher’s site or app.

Who Can Benefit From Building an SSP or an Ad Exchange?

Building an SSP can provide a few benefits for AdTech companies, publishers, brands, e-commerce platforms, and telcos. Below we briefly discuss the main benefits for these parties.

AdTech Companies

Building an SSP can generate more income for AdTech companies, as they earn money from transaction fees every time an ad is bought or sold on their platform. The more transactions, the more revenue they earn.

An SSP can also help AdTech companies grow their business as it can attract publishers who want to sell ad space and, as a result, brings in more advertisers. So, it helps expand their business by attracting more clients.

SSPs also provide valuable data about ads, user behavior, and market trends. This information can help AdTech companies improve their products, create new services, and better service their clients.

Publishers

Publishers can benefit from an SSP in a few ways. First, they can automate inventory sales across multiple formats and devices, reducing manual work and enabling them to monetize their sites or apps effectively.

SSPs provide detailed reports, offering insights into bidding processes, inventory value, and advertiser behavior. They can also connect with multiple networks, ad exchanges, and DSPs, attracting more buyers and potentially enhancing yield.

Furthermore, SSPs implement price floors, ensuring inventory isn’t undersold and assisting in yield optimization. Some platforms employ a blend of soft- and hard-price floors, creating a hybrid auction model.

SSPs also boost brand safety by filtering out unwanted ads, providing publishers the ability to control which ads appear on their sites.

Ad Agencies

For large brands and ad agencies, creating their own ad exchange can offer many benefits — from boosting ROI to improving campaign results to cutting costs.

An ad exchange imparts greater control over the displaying of ads, data collection, and ad delivery, allowing the agency to define client-centric metrics and criteria, hence improving results. 

Also, ad agencies can build their own ad exchange to replace their existing third-party AdTech platforms, which will not only give them more control over the tech but also allow them to reduce the fees and commissions paid to third-party tools.

An ad exchange can also enable agencies to access valuable data sets on user behavior, which helps improve targeting and campaign performance.

Main Challenges When Building an SSP and an Ad Exchange

Let’s take a look at challenges that are typically encountered when designing and building a supply-side platform (SSP) and ad exchange.

Achieving Scalability

SSPs and ad exchanges must be capable of processing billions of daily requests. This requires a platform that can scale dynamically to manage increasing or decreasing traffic without compromising on speed or reliability.

The key factors to consider when designing for scalability include:

• The platform’s ability to handle peak traffic loads.
• Its capacity to manage the continuous stream of bid requests and responses.
• Its ability to store and process vast amounts of data.
• Its adaptability to rapid changes in demand.
• Its ability to anticipate and accommodate potential growth in terms of user base, the number of partners, and the volume of data processed.
• Acceptable cost per transaction.

To avoid downtimes and build a scalable SSP and ad exchange, a well-designed architecture is required, as well as a robust server infrastructure, optimized cloud-computing solutions, and efficient data handling and storage systems.

Implementing Real-Time Bidding

The success of the real-time bidding (RTB) process lies in the ability of the platform to facilitate a real-time auction for each ad impression as a webpage is loaded. Each auction takes place within milliseconds, meaning that carrying out this process adds a lot of technical complexity.

The key factors to consider when designing the RTB system include:

• Selecting the right technologies to ensure seamless communication between the SSP, DSP, and the ad exchange.
• Handling the collection and processing of data involved in the real-time bidding process, such as the bid request, the actual bids, and the bid response
• Implementing algorithms that optimize the process of displaying the best-performing creative based on data.

User Data Privacy

As both SSPs and ad exchanges often collect and process user data when running targeted advertising, it is essential to balance effective ad personalization with user privacy.

From the technological point of view, the first step towards making SSPs and ad exchanges compliant with regulations such as GDPR and CCPA involves ensuring accurate collection and transmission of user consent information from publishers and between tech platforms. However, to follow the rules entirely, platforms need to adapt certain technological solutions, such as encryption and other PETs, to protect user data.

Some examples of privacy-enhancing technologies include:

• Minimization techniques
• Encryption
• Anonymization/pseudonymization
• Virtual Private Networks (VPNs)
• Privacy-preserving APIs
• Trusted execution environment (TEE)
• On-device learning/federated learning (FL)
• Privacy-preserving data mining (PPDM)
  • Differential privacy (DP)
  • Homomorphic encryption (HE)
  • Multi-party computation (MPC)

We covered PETs in more detail in the blog post What are Privacy-Enhancing Technologies (PET) in AdTech?, where you can learn more about how they are being used in AdTech today.

How to Design and Build an SSP or Ad Exchange?

Developing a supply-side platform and ad exchange is a task that involves several steps. Below are the phases we at Clearcode follow to build SSPs, ad exchanges and other digital advertising software.

Discovery

This phase includes:

• Understanding the objectives, vision, and context of your SSP or ad exchange development project.
• Identifying your project’s initial requirements and potential technical challenges associated with real-time bidding and data processing.
• Answering various technical questions that surface during this phase, such as ensuring scalability and data privacy compliance.

Sprint 0

This phase includes:

• Identifying the technical unknowns of the SSP or ad exchange development project and exploring potential solutions.
• Selecting the features for the minimum viable product (MVP) and creating a list of user stories that will constitute and shape the product backlog.
• Researching the optimal tech stack and infrastructure architecture for efficient ad serving and real-time auctions.
• Conducting initial research for MVP development or proof of concept (PoC) development.

MVP Development

This phase includes:

• Building your SSP or ad exchange’s MVP — encompassing front-end and back-end development, infrastructure setup, UX/UI design, and thorough quality assurance testing.
• Launching your MVP to initial users or stakeholders, typically a select group of publishers and advertisers.
• Gathering feedback for the post-MVP development phase, focusing on aspects such as the user experience, ad serving efficiency, and reporting features.
• Monitoring the platform’s performance, ensuring smooth operations, and responding to any unforeseen emergencies.

Post-MVP Development and Maintenance

This phase includes:

• Continuing the development of the SSP or ad exchange via our agile development process (2-week sprints), aiming to provide new or improved features at the end of each sprint, such as advanced targeting options or enhanced analytics capabilities.
• Providing ongoing support and maintenance of the software and infrastructure, ensuring high availability and addressing any issues promptly.
• Transitioning the project to your internal team if required, including comprehensive training on managing and maintaining the SSP or ad exchange.

Examples of SSPs and Ad Exchanges that Clearcode has Built

Over the years, Clearcode’s AdTech & MarTech development teams have designed, built and delivered various SSPs and ad exchanges for AdTech companies, publishers, media companies, and ad agencies. 

Below you’ll find short descriptions and links to two projects we’ve worked on.

A Scalable SSP

Clearcode designed and built an SSP with the goal of solving key challenges around performance and scalability. The SSP incorporated an ad exchange component and was designed to help companies decrease development time when building a supply-side platform (SSP) or ad exchange.

We deployed a microservice architecture and coupled it with a horizontal scaling pattern to overcome the scalability challenge. By introducing inter-service communication over the publish-subscribe (pub/sub) layer and developing a populator service, we managed to handle the challenges associated with an SSP’s performance.

As a result, the ad exchange has stable performance, is scalable, is able to sell more inventory to DSPs, and has the most up-to-date inventory.

Supply-Side Platform (SSP), Ad Exchange and Prebid Adapter Development for FatTail

FatTail, a leading US-based AdTech company, collaborated with Clearcode to create their AdBookPSP solution, establishing the first SSP specifically tailored for deal-based programmatic transactions.

The primary challenges included modifying the Prebid adapter to transmit all bids from the demand sources to Google Ad Manager, as opposed to the standard limit of 3, and gaining a thorough understanding of the integration process with Google Ad Manager.

Through incorporating deal instructions from AdBook+, executing real-time processing, integrating with the DSPs, carrying out decision-making, and finally, conducting post-RTB processing, we were able to create a one-of-a-kind custom solution.

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In this blog post, we’ll explore the benefits of PETs in AdTech and the challenges that come with implementing them.

This is our second article on the topic of privacy-enhancing technologies in AdTech. If you want to learn what PETs are, what examples of PETs exist in AdTech, why and how they are used, and what the future holds for them, then read our blog post: What Are Privacy-Enhancing Technologies (PET) In AdTech? And if you want to know why companies should be looking at implementing privacy-enhancing technologies (PETs) into their businesses, read Clearcode’s piece in Exchange Wire’s Industry Review 2023.

Key Points

• Privacy-enhancing technologies (PETs) are technologies designed to protect user privacy while still enabling data collection and analysis. They can include techniques such as encryption, anonymization, and differential privacy.
• Thanks to PETs, advertisers can target specific audiences without collecting or sharing personal data. This can improve user trust and reduce the risk of data breaches or misuse.
• PETs can also help advertisers and publishers comply with privacy regulations, such as GDPR and CCPA.
• Advertisers can use PETs to gather insights about user behavior and preferences without exposing personal data. This can lead to more effective ad targeting and a better user experience.
• PETs can also benefit publishers by allowing them to monetize their content without compromising user privacy. By using PETs to collect non-personal data, publishers can offer more relevant ads to their audiences without risking user trust.
• While PETs can offer many benefits, they are not a silver bullet for privacy concerns in AdTech. Companies must still be transparent about their data collection practices and ensure that they are using PETs effectively to protect user privacy.

The Benefits of Privacy-Enhancing Technologies (PETs) In AdTech

Protecting Personal Information

One of the main benefits of PETs in AdTech is securing personal information. PETs ensure that user data is collected, processed, and stored securely, reducing the risk of data breaches and unauthorized access. This not only protects the privacy of individuals but also helps companies avoid costly lawsuits and reputational damage.

Examples of PETs that protect personal information include:

• Anonymization techniques — to remove personally identifiable information (PII) from user data, such as names, addresses, and phone numbers.
• Differential privacy — to add noise to data to make it difficult to identify individual users.
• Homomorphic encryption — to process encrypted data. 

Maintaining User Trust

PETs can help companies build and maintain user trust by providing transparent data collection and processing practices. By being transparent about how data is collected and used, companies can show that they respect user privacy and are committed to protecting their data.

Things that help maintain user trust in the context of privacy-enhancing technologies include:

• Privacy policies — AdTech companies can explain their practices of data collection and thus give users control over their data.
• User consent — AdTech companies can obtain user consent through opt-in or opt-out mechanisms, depending on the type of data being collected.
• Data minimization — AdTech companies should only collect the data necessary to provide their services.

Compliance With Regulations

PETs can help companies comply with privacy regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). These regulations require companies to implement specific privacy protections and disclose how user data is collected and used. 

PETs can help companies meet these requirements and avoid fines and legal penalties.

Companies can use differential privacy algorithms in their data analysis to extract valuable insights while preserving individual privacy. By aggregating and anonymizing sensitive data, these algorithms prevent the identification of individual users. This approach helps companies meet privacy law requirements like GDPR and CCPA, reducing the risk of fines and legal consequences while safeguarding user privacy.

Examples of laws that regulate the collection, storage and use of data:

• General Data Protection Regulation (GDPR) — regulates the collection, use, and storage of personal data by businesses and organizations in the EU.
• California Consumer Privacy Act (CCPA) — gives California residents the right to know what personal information is being collected about them, the right to request that their personal information be deleted, and the right to opt-out of the sale of their personal information.
• Personal Data Protection Act (PDPA) — the PDPA is a privacy law in Singapore that regulates the collection, use, and disclosure of personal data by organizations. It gives individuals the right to access their personal data and to request that it be corrected if necessary.
• General Data Protection Law (LGPD) — LGPD is a Brazilian privacy law that enhances privacy by regulating the collection, use, and storage of personal data by businesses and organizations in Brazil.
• Privacy Act 1988 — The Privacy Act is an Australian law that enhances privacy by regulating the handling of personal information by Australian government agencies and some private sector organizations.
• Personal Data Protection Act (PDPA) — The PDPA is a privacy law in Malaysia that enhances privacy by regulating the processing of personal data by organizations.

Improving the Accuracy of Data

PETs can also help companies improve the accuracy of their data. By using PETs, companies can ensure that the data they collect is high-quality and reliable, which can improve the effectiveness of their advertising campaigns.

Data validation

Data validation is the process of ensuring that data is accurate and complete. For example, one privacy-enhancing technology that can be used for data validation is homomorphic encryption. 

Homomorphic encryption is a type of encryption that allows computations to be performed on encrypted data without decrypting it first. AdTech companies can use homomorphic encryption to validate their data without exposing it to third parties or risking a data breach.

Data enrichment and collaboration

Data enrichment is the process of enhancing existing data with additional information. PETs can help AdTech companies to perform data enrichment in several ways. 

For example, they can use anonymization techniques to remove personally identifiable information (PII) from user data before enriching it with additional information. This ensures that the privacy of users is protected while their data is being enhanced. 

PETs can be used to enable secure data sharing and collaboration between different AdTech companies while preserving user privacy. 

This can be achieved by using techniques such as secure multi-party computation (MPC) or homomorphic encryption, which allow multiple parties to perform computations on encrypted data without revealing the underlying data.

Machine learning

Privacy-enhancing technologies (PETs) can be used in AdTech to ensure that machine learning models are trained on private data without compromising user privacy.

Reducing Costs

PETs can help companies reduce costs by minimizing the risk of data breaches and reducing the costs associated with maintaining a large and complex tech stack. 

By reducing the need for data storage and processing, advertisers, publishers, and AdTech companies can save money on infrastructure and maintenance costs.

The Challenges of Privacy-Enhancing Technologies (PETs) In AdTech

Despite the many benefits that privacy-enhancing technologies (PETs) offer for the AdTech industry, there are also several challenges that must be addressed for their effective implementation. These challenges can range from technical and financial to legal.

Complexity

Privacy-enhancing technologies can be complicated to understand and implement, requiring specialized knowledge and expertise. For example, the implementation of federated learning requires expertise in distributed systems and machine learning algorithms.

Compatibility With Existing Systems

Implementing PETs can be demanding and difficult, requiring compatibility with existing IT systems and integrations with workflows.

Cost

The adoption, maintenance, and adjustment of PETs can be costly, which can be a barrier for some companies. The cost of implementing PETs can include hardware and software purchases, employee training, ongoing maintenance and updates.

Trade-Offs

PETs can require trade-offs between privacy and other considerations, such as the accuracy of data. Companies may need to balance the benefits of PETs with other priorities, such as marketing effectiveness or business goals.

Lack of Standards

The absence of standardized PETs can make it hard for companies to choose the best solutions for their requirements. 

Nevertheless, the Interactive Advertising Bureau (IAB) has formed a dedicated group to develop standards for PETs in AdTech. 

This group consists of advertisers, publishers, technology providers, and privacy advocates. They aim to create a set of standardized protocols for PETs that will be accepted by the industry. 

The standardization of PETs will ensure that they are effective and consistent across the industry.

Opportunities of Privacy-Enhancing Technologies (PETs) In AdTech

Despite the challenges, PETs also offer significant opportunities for publishers and advertisers, including improved cybersecurity and new innovations.

As we mentioned earlier, PETs can reduce the risk of data breaches and leaks, which can help companies avoid costly legal and reputational damage.

PETs are a way to enhance the privacy and security of users, which can be a selling point for companies. By demonstrating a commitment to user privacy, companies can build trust and loyalty among their customers.

Summary

Privacy-enhancing technologies offer many benefits to the AdTech industry, including improved data protection, regulatory compliance, and user trust. 

However, the adoption of PETs also comes with challenges, including complexity, compatibility with existing systems, and cost considerations. AdTech companies must be aware of these challenges and develop strategies to overcome them effectively.

Overall, the development and adoption of PETs is critical to ensure the protection of user privacy in a constantly evolving digital landscape. 

By investing in PETs and working together to establish standards and best practices, AdTech companies can prioritize user privacy while continuing to provide effective programmatic advertising processes.

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In this article, we discuss these technologies, including blockchain, cryptocurrency, augmented and virtual reality, artificial intelligence, and 3D reconstruction. By incorporating them into their games and virtual environments, developers can create a more engaging, personalized, and realistic experience for users while making it easier to manage and scale the virtual world.

Key Points

• The metaverse is a fully immersive virtual world that relies on several key technologies for its development and growth.
• Blockchain technology is a fundamental building block for most of the metaverse’s applications, providing decentralization, transparency, and immutability to transactions.
• Cryptocurrency is the only method of payment accepted in the metaverse, allowing users to purchase resources and assets.
• Augmented and virtual reality engines help facilitate the virtual world’s immersive and engaging three-dimensional environments, allowing users to experience physical simulations.
• Artificial intelligence plays a crucial role in the metaverse’s development and growth, helping create a more engaging, personalized, and realistic user experience.
• 3D reconstruction technologies are crucial in creating an environment that mimics the real world, making it possible to bring the metaverse to life.

What Technology Will Power the Gaming Metaverse?

While the metaverse is still far from being a reality, there are certain technologies that can establish the foundations, used to develop it further, and power the metaverse environment.

Blockchain

The metaverse relies heavily on blockchain technology as it serves as a fundamental building block for most of its applications. Blockchain technologies enable decentralization and transparency to ensure all the processes in the metaverse are operating seamlessly.

The main benefits of blockchain technologies are the fact that it provides greater transparency into transactions that are immutably recorded and time-stamped, which enables users to view the entire transaction history and minimizes the opportunity for fraud. 

Developers utilize blockchain technology to incorporate various functionalities into the metaverse, including verifying digital ownership, transferring value, establishing governance, promoting digital collectability, facilitating accessibility, and promoting interoperability.

Using blockchain technology as a foundational element of the metaverse has several advantages:

1. Keep track of transactions — blockchains act as a virtual ledger and create a record of all transactions issued in the metaverse. The data in a blockchain is stored in a decentralized database reducing the likelihood of malfunctions. 
2. Chains of data — blockchains are a method of storing information by grouping it into blocks. These blocks have a limited storage capacity and are closed once they’ve been fully filled. Once a block is complete, it is linked to the previous block to form a chain of data, which is known as the blockchain.
3. Chronological order — blockchains arrange data chronologically and automatically based on their structure, create a timestamp of the record and make it impossible for the data to be changed or deleted. Once a block has been sealed, it is set in stone, allowing the entire process to be free from manipulation and providing transparency to all parties in the metaverse.

Cryptocurrency

Cryptocurrency is one of the main technologies used in the metaverse as this is the only method of payment accepted in the metaverse. There is no other way for users to carry out transactions in the metaverse other than exchanging real-world currencies (aka fiat currencies) for crypto. 

They are used to purchase various resources in the metaverse, including NFTs, digital real estate, and in-game items. Cryptocurrency has become a valuable asset for only for the game players but also for investors who wish to make money off them in the future.

AR & VR

Augmented reality (AR) and virtual reality (VR) engines are essential components of the metaverse that help facilitate the immersive and engaging three-dimensional environments of the virtual world. 

Virtual reality and the metaverse may appear to be similar, but they have some distinct differences. Virtual reality is only a part of the broader metaverse as it consists of several technologies that complement VR technology, such as augmented reality (AR), mixed reality (combines elements of VR and AR), blockchain technology, artificial intelligence (AI), and cloud computing. 

VR technology can be compared to a puzzle, in the sense that it needs other complementary technologies to create a more immersive and interactive experience. 

Virtual reality allows users to view and interact with 3D simulations, but it is unable to provide physical simulations, which is a crucial aspect of the metaverse. 

This is where augmented reality helps as it expands the scope of the metaverse and enables users to actually experience physical simulations. 

They can hear, feel, and interact with the virtual metaverse. The combination of VR and AR creates more realistic experiences that positively impact users but requires massive investments from tech companies.

Artificial Intelligence (AI)

Artificial intelligence has become an essential aspect of our daily lives by enhancing multiple processes of various devices to create a positive user experience. 

For example, virtual assistants such as Siri, Alexa, or Google Assistant remind us about important tasks, send messages, make phone calls, and manage smart home devices such as thermostats, security cameras, and lighting systems. 

AI is also used in navigation systems to calculate the best route to a destination based on real-time traffic and personal driving habits, as well as to support recommendation engines to suggest what type of content should be shown to a specific user. 

Moreover, AI helps to identify fraudulent activities in banking systems and prevent fraud-like transactions from occurring. 

Not to mention, self-driving cars and trucks that use AI to navigate roads, avoid obstacles, and make decisions based on real-time data from sensors and cameras.

AI is also being used in the development of the metaverse to:

• Plan business strategies.
• Speed up decision-making processes.
• Improve the user interface and experience.
• Help process data with machine-learning techniques.
• Create unique outputs and insights.
• Provide sensors for non-player characters.
• Translate content into multiple languages.
• Create metaverse avatars.

The use of AI in the metaverse can help create a more engaging, personalized, and realistic experience for users, while also making it easier to manage and scale the virtual world. 

As the metaverse becomes more prominent in our lives, we can expect to see AI playing an increasingly important role in its development and growth.

3D Reconstruction

Although 3D reconstruction has been around for a few decades now, the recent COVID-19 pandemic has increased its usage since consumers were unable to visit stores during the lockdowns. 

Therefore, many businesses are now utilizing 3D reconstruction technologies to create virtual tours of properties and showrooms. It was somewhat predictable that this technology would also spread into the metaverse.

Given that the metaverse is a 3D virtual world, it is understandable that 3D construction plays a crucial role in bringing the metaverse to life.

The challenge for the metaverse is to create an environment that mimics the real world by using special 3D cameras and other reconstruction technologies to render:

• Realistic 3D images
• Models of buildings
• Various everyday objects

The information gathered by 3D cameras and high-quality 4K photography is further processed by computers to produce realistic simulations that can be utilized in the metaverse.

The Internet of Things (IoT)

The idea of the Internet of Things (IoT) was initially introduced in 1999 and involves linking every physical component of our environment to the Internet using different sensors and devices.

In the case of the metaverse, IoT offers numerous benefits:

• IoT applications can gather data from the physical world and incorporate it into the metaverse to create more accurate and realistic virtual environments. For instance, weather or temperature data collected through IoT-enabled devices can help the metaverse adjust its environment accordingly.
• IoT can facilitate the seamless integration of the 3D world with a wide range of physical devices, resulting in real-time simulations within the metaverse.
• Through the use of AI and machine-learning algorithms, IoT can improve and optimize the metaverse environment by managing the data it collects.

Edge Computing & 5G

Edge computing is typically utilized in commercial settings to facilitate faster data transfer with minimal delays and ensure seamless experiences. It is one of the key factors that has made the metaverse viable as computers must handle the intense simulations efficiently to reduce lag and provide users with an immersive and uninterrupted gaming experience.

Another essential feature often coupled with edge computing is the availability of 5G networks. 

Previously, users encountered network issues while participating in the metaverse due to slow rendering and data transfer speeds caused by the absence of high-speed Internet. 

However, with the introduction of 5G and its availability at affordable rates, more users can enjoy the metaverse from their devices without any network-lag issues.

The combination of edge computing and 5G has allowed users to participate in the metaverse and enjoy a truly immersive experience.

Why Will NFTs Play a Major Role in the Gaming Metaverse?

Non-fungible tokens (NFTs), along with other digital assets, will play a crucial role in building the economy of the metaverse, as they serve as proof of ownership for virtual assets.

NFTs are exclusive assets that are stored on a blockchain, like Ethereum, Polygon or Solana. They serve as authentic documentation of ownership of virtual assets, which can only exist within the digital world. 

The fact that they are stored on a public blockchain ensures their security and legitimacy, while making them easily transferable across different applications.

In 2022, the NFT market saw an organic trading volume of approximately $24.7 billion on various blockchain platforms and marketplaces.

It is predicted that revenue in the NFT industry will have reached $3.5 billion by 2023 and will continue to grow at a compounded annual rate (CAR) of 22.82% until 2027, resulting in a projected total revenue of $8.1 billion. The average revenue per user in the NFT sector is expected to be $70.46 in 2023.

The use of NFTs in gaming allows players to have complete ownership of their digital assets, such as skins, weapons, and handbags. This enables them to trade NFTs freely with other players in the same universe, sell them for real money, and potentially use them across multiple blockchains.

NFTs are often monetized through smart contracts, which execute specific actions when certain predetermined conditions are met. 

For example, artists using NFT smart contracts can receive royalty payments on all subsequent resales of their pieces. Musicians can sell a stake in their songs to investors who will receive royalties every time the song is played on a streaming service.

NFTs also support the “play-to-earn” (P2E) gaming model, which provides gamers with a financial incentive to play games. 

In P2E games, players earn cryptocurrencies that can be used within the game, sold on an open market, or monetized through smart contracts. 

If a gamer creates an NFT character that someone else uses to earn cryptocurrencies, the creator receives a portion of those earnings. It contrasts with traditional gaming, where gamers acquire assets that have no real-world value.

NFTs are seen as a key element of the metaverse and can provide many benefits.

The use of NFTs in the metaverse can help:

• Increase customer satisfaction. 
• Improve margins, enhancing product and service visibility.
• Foster collaboration with nontraditional gaming partners. 
• Attract new customers.

Summary

The gaming metaverse relies on several technologies, including blockchain, cryptocurrency, AR/VR engines, AI, and 3D reconstruction. These technologies enable decentralization, digital ownership verification, immersive environments, an enhanced user experience, and realistic virtual worlds. Utilizing these metaverse technologies will play a crucial role in its continued development and growth.

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The post What Technologies Will Empower The Gaming Metaverse? appeared first on Clearcode.