Preparing For The Cookieless Era With AI with Amperity’s Peter Ibarra

With the era of third-party cookies nearing an end, advertisers and publishers are scrambling to include Artificial Intelligence (AI capabilities) in their Advertising Technology (adtech) and Martech stacks. In the last few years, AI in marketing has become the core of running successful digital campaigns. Brands and customers have similar expectations from AI tools. These are used to create personalized marketing campaigns that help marketers orchestrate a disruption-free customer journey across multiple channels. Doing personalization right with AI requires a refined approach to customer data management. We feel that CDPs have a big role to play in driving enriched personalization through high-quality data. In this Q&A, we speak with Peter Ibarra, head of adtech solutions, Amperity about what companies need to be prepared for this year to prepare for third-party cookie depreciation, consumer data privacy, and the role of AI in a cookieless era.

In the cookieless era, how should brands use AI and data analytics for “Paid Media Activation”?

The much-discussed cookie deprecation has seemed like a far-off future problem, but the reality is companies need to be ready now. The rental economy is over, and marketers need to own more of their process. This means as a paid media marketer, you should move quickly to:

• Own your customer data & identity graph
• Own your audience segmentation
• Own your onboarding to ad environments
• Own your measurement

It’s time to pivot your advertising strategy towards an owned, first-party direction in the face of cookie collapse.

As it relates to AI, exciting new AI tools promise to unlock new levels of personalization at scale.

The caveat?

Well, AI requires quality data inputs to work properly. Without that, you’re paying to send people ads for things they just bought, you’re making them wait on a service call while you dig up a transaction record and you’re committing resources to audiences that don’t convert.

If you’re training generative AI tools to personalize content and experiences but the data input is inaccurate, then you’re just creating a greater volume of misplaced marketing. Feeding your tech stack with junk data is like buying a Lamborghini and filling the tank with low-grade fuel.

After decades of digital marketing, the specter of garbage-in, garbage-out still looms as large as ever. To put it bluntly, nothing else in your technology stack matters unless you solve this foundational problem.

How would third-party deprecation impact retail brands? What is the future of programmatic advertising in the cookieless era?

The deprecation of third-party cookies has already led to signal loss and challenges for digital marketers, especially in retail. Retail brands relying on third-party cookies may experience higher customer acquisition costs, decreased audience addressability, and unreliable measurement.

That said, it also presents an opportunity for retailers to use their customer data, behavioral and purchase, for monetization.

We’ve seen dozens of retail media networks (RMN) come to market and promise valuable audiences in the face of signal loss for their supply partners.

As they enter the next phase of their maturity, they must build for quality, not just volume. The advertisers they work with expect performance to improve and with more RMNs, there is more competition. It’s about owning more of the monetization process and ensuring high-quality customer data is fueling the advertising/customer experience.

In the cookieless era, the future of programmatic advertising lies in owning customer data and identity graphs. Brands need to transition from renting to owning data processes, including audience segmentation and onboarding to ad environments, to thrive in the evolving advertising ecosystem.

How would ad targeting platforms evolve in the context of AI-powered customer data management? Any tips that you would like to offer to programmatic adtech users?

Ad targeting platforms are poised to undergo significant evolution to enhance precision, relevance, and efficiency. However, for AI to do its “magic”, analyzing vast amounts of data and enabling more sophisticated targeting and personalization at scale, it must have quality data inputs.

My tips for programmatic adtech users would be first and foremost, to prioritize first-party data. Then leverage AI tools that help you build a unified data foundation to find connections between data points to tell if they belong to the same person with the same nuance and flexibility of a human but at a massive scale.

When your customer data tools are AI-enabled, you are better able to unify every touchpoint in the customer journey from the first interaction to the last purchase, the result is a comprehensive customer profile that tells you who your customers are.

And, good news, it also tells your AI marketing tools who your customers are.

What’s next when it comes to aligning customer data management with elevating loyalty and personalization?

As generative AI tools for marketing continue to evolve, they bring the promise of getting back to the level of one-to-one personalization that customers would expect in their favorite stores, but now at a massive scale. That won’t happen on its own, though — brands need to provide AI tools with accurate customer data to bring the AI magic to life.

But when they do, data quality to power AI provides tremendous benefits, including:

• Customer experiences that stand out — more personalized creative, and offers better customer service interactions, a smoother end-to-end experience, etc.
• Operational efficiency gains for your teams — faster time to market, less manual intervention, better ROI on campaigns, etc.

Reduced compute costs — better-informed AI doesn’t need to go back and forth with the user, which saves on racking up API calls that quickly get expensive.

How do you foresee Google’s deprecation of third-party cookies impacting consumer privacy online?

The deprecation of third-party cookies by Google will change the way consumer data is used online. With fewer third-party tracking cookies, there’s less opportunity for widespread tracking of user behavior across different websites. This shift means consumers have more control over their personal data, by allowing users to opt-in vs opt-out of data sharing. This will force companies to explore new consent incentives and test alternative tracking methods.

For instance, there will be a significant move toward the collection and management of first-party data because of the numerous benefits it offers such as improved data accuracy, enhanced customer relationships, greater data control and security and more effective personalization strategies.

In what ways might the elimination of third-party cookies change the current data compliance landscape?

Elimination of third-party cookies will significantly alter the data compliance landscape. Companies will need to focus more on obtaining explicit consent for data collection while aligning with a mishmash of regulations across geographic regions with  GDPR and CCPA. This shift could also prompt new regulations specifically addressing alternative tracking technologies and first-party data collection practices to ensure the data company is consensually provided.

Can you describe the challenges and opportunities that brands may face as they shift from third-party to first-party data collection?

Companies face fundamental challenges such as the need to invest in new technologies for first-party data collection and the potential reduction in the amount of available consumer data. This new reality will present opportunities including building more direct and meaningful relationships with customers, gaining accurate and relevant data that can inform customer interactions, and enhancing brand trust and credibility.

The key is to align on a strategic vision and select the right data management solutions to achieve it. Ones that are scalable, user-friendly with “out-of-the-box” analytics features, compliant, and capable of integrating seamlessly with existing martech and other systems.

How should they prepare their data governance policies to adapt to a world without third-party cookies?

Companies should revisit their data governance policies to ensure compliance with privacy regulations and ethical standards. This includes implementing robust consent management systems, ensuring compliance, and being transparent about data collection and usage practices. Investing in management and security to protect first-party data is also crucial.

Finally, it’s important to remember that while many CDPs offer tools and features that can support compliance, transparency, and security, they are not a complete solution in themselves.

Companies must actively manage these aspects in line with their specific needs and regulatory requirements.

What impact do you predict the loss of third-party cookies will have on digital advertising and marketing strategies?

The loss of third-party cookies will completely disrupt the digital media ecosystem. While most advertisers think about third-party cookies in the context of targeting, they are used across a variety of tools that span data collection, audience segmentation, data onboarding, and most importantly, measurement. There is no silver bullet to replace the third party cookie and advertisers have the opportunity to reimagine their digital media tech stack.

In fact, we’re seeing that brands who leave the cookie environment now are experiencing a competitive advantage and will continue to do so since most of the industry has not shifted their reliance from 3P cookies.

How might the Privacy Sandbox and other similar initiatives balance the need for user privacy with the commercial need for targeted advertising?

Initiatives like Google’s Privacy Sandbox aim to create technologies that allow for user privacy while still enabling targeted advertising. These initiatives may involve using aggregated, anonymized data or machine learning algorithms that process data on the user’s device without transmitting sensitive information.

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But while Google’s Privacy Sandbox is beneficial from a privacy standpoint, it limits the depth of data brands are used to working with. They should not rely on Google to provide the data or tools they need to power personalization capabilities compared to what first-party data used with a CDP offers.

CDPs consolidate diverse data sources to offer a comprehensive view of customer behavior and preferences, excelling in personalization through detailed segmentation and targeted campaigns. This contrasts with the Privacy Sandbox’s limited use of personal data.

CDPs stand out with their real-time data processing, enabling immediate response to customer behaviors, a feature less emphasized in the Privacy Sandbox. They offer businesses direct control and ownership over customer data, allowing more flexibility in data management and use. This control is crucial, especially compared to dependence on third-party platforms like the Privacy Sandbox.

Additionally, CDPs offer customization to meet specific business needs and integrate with other tools, creating a tailored tech stack that may not be as achievable with the Privacy Sandbox. They also support compliance with various privacy regulations such as GDPR or CCPA, enabling responsible and ethical data management while still deriving valuable insights.

What alternative technologies or methods do you believe will emerge to replace third-party cookies for tracking and data analytics purposes?

The alternatives we’re already seeing include first-party data activation tools, the return of contextual advertising, data clean rooms for measurement and collaboration, and AI.

By using AI and machine learning for predictive analytics based on first-party data or using blockchain for transparent and secure data transactions.

How can businesses ensure transparency and maintain trust with their customers during this transition?

Businesses will maintain consumer trust during this transition by being transparent about their data collection and usage practices. Regular communication with customers about how their data is being used and providing them with greater control over their data will foster trust. Additionally, keeping pace with and adhering to growing privacy regulations and ethical standards is key.

How do you see the role of artificial intelligence and machine learning evolving in marketing with the decline of third-party cookie usage?

As reliance on third-party cookies decreases, AI and machine learning will play a more significant role in marketing.

As we move forward, it’s becoming increasingly clear that brands must embrace new AI-driven methodologies to effectively acquire and retain customers. This shift isn’t just about keeping up with technological advancements; it’s a response to intensifying business pressures and evolving consumer demands.

From a business perspective, the pressure is mounting for efficiency, scalability, and the effective use of data to drive greater returns. In this landscape, AI’s role is crucial. For CMOs, delivering greater return on investment has emerged as the primary objective for 2023, underscoring the need for a more sophisticated, data-driven approach.

However, this shift isn’t solely about the numbers. Consumer demands are equally influential in shaping this new paradigm. There’s a growing concern among consumers about how AI and their personal data are used. They expect brands to be not only conscious but also responsible in their data utilization. Furthermore, as consumers become more willing to share their data, they anticipate a higher degree of personalization and relevancy in their interactions with brands. They want experiences that are tailored to their preferences, delivered at the right time, and through the right channels.

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The intersection of business efficiency and consumer-centricity is defining a new era in marketing. Brands that successfully navigate this landscape by leveraging AI in a responsible, consumer-focused manner are poised to thrive in this dynamic environment.

Thank you, Peter! That was fun and we hope to see you back on AiThority’s TechBytes conversations soon.