How Conversational AI Is Enabling Brands to Move Beyond Third-Party Cookies

By focusing on a dialogue with consumers through more robust, conversational AI, brands can deliver the best customer experience possible while also respecting consumer privacy.

By Christian J. Ward

Sep 14, 2022

5 min

We stand at a decisive moment for brands as they look to the future of consumer data strategies. With disparate state-by-state legislation, numerous proposals for a national regulatory framework in the US, and differing international laws, including the GDPR, the data governance guidelines for brands to follow are inconsistent – and potentially costly should they run afoul of the rules.

Tech giants have slowly but surely decoupled themselves from some of the more shady practices that have ruled online targeting for years. Apple's iOS 14.5 update severely hampered Meta's tracking abilities, and Google's proposed phase-out of third-party cookies by 2024 will render those identifiers all but useless across Chrome browsers, bringing Chrome in line with other browsers like Safari that have already moved beyond cookies.

Whether the change comes in 2022, 2024, or 2026 shouldn't matter: the decreased reliance on third-party cookies should be considered a positive for brands in the business of better customer experience.

By focusing on a dialogue with consumers through more robust, conversational AI, brands can deliver the best customer experience possible while also respecting consumer privacy.

Rejecting Data Gluttony

Due to the increased use of cookie data pools and other third-party sources, brands have gotten accustomed to having thousands of data points on every consumer that enters their orbit.

But for all the data sitting in consumer data platforms, the vast majority of it isn't used (or even usable). Brands may have 12,000 data points on an individual consumer, but ask any marketing manager and they'll tell you they only regularly utilize 10-15 of those top-line points: location, age, the last product purchased, or even previous article read.

This practice of data gluttony does more harm than good. All of this information does nothing but clog the arteries of functioning marketing efforts. Further, with emerging privacy regulations, data minimization, and a broader mandate of storing less rather than more data, ultimately, this gluttony could create significant liability for brands in the future.

Data gluttony directly results from current digital practices where brands project a monologue rather than truly engaging in a dialogue with customers. By gathering as much data on consumers as possible, brands have built their datasets with the intent to follow rather than engage consumers.

Marketers project their message and then track how users react and behave to that message. They then store that data to try to re-monologue towards those consumers at a future date. This imprecise science leads brands to target a consumer as an outdoorsman after accidentally clicking on a single ad for a sleeping bag, for example. These conditions create a poor user experience and do nothing to build a long-term relationship with the brand.

On the other hand, a dialogue-based approach grounds marketing efforts in data directly supplied by a consumer through search queries and conversational AI, with consent built in.

Building a Dialogue With the Consumer

This may sound rudimentary, but what exactly is "data?" Its Latin roots roughly translate to "the thing having been given." In other words, real data is information that is freely given by the consumer, not gathered without their knowledge, consent, or control.

Unfortunately, most brands view data as something to be taken and exploited. But in dialogue, something is offered, and something is returned. To contextualize this dialogue in data terms, brands should be taking a zero-party, value-exchange model to how they view consumer data.

While Google has an incredible data tracking capability, a huge portion of their knowledge is actually the data provided freely by consumers into their search bar. They provide an excellent example of how search queries begin the conversation. Conversely, most brands and businesses blast their monologue with content, pop-ups, and a thousand drop-down menus hoping that consumers will take the time to navigate to an appropriate answer.

In the broadest terms, a dialogue is a value exchange: the experience of searching is made better by the data given by the consumer. In this exchange, brands can customize and properly personalize the answers to help the consumer on their path to discovery and purchase. Remember, it's a "customer journey" not a "brand journey."

With the current breakthroughs in conversational AI, brands of all sizes now have the ability to move beyond rudderless, consent-flouting third-party datasets and into engaging dialogues with a consumer.

Giving the Right Answers to the Right Questions

If given the opportunity, consumers will tell a brand what they want. It's incumbent upon the brand to provide the right answer to those queries. When the answers are as specific as the question, not only has the brand created an engaging dialogue with a customer, but they've provided personalization on the consumer's terms.

Conversational AI, natural language processing, and knowledge graphs are vital tools for brands that can enable this dialogue. They're also at the heart of numerous successful brands, including Amazon and Google.

If you're a consumer and you visit a clothing retailer looking for a winter jacket, performing a simple search for "winter jacket" may get you the results you want, or it may not. The taxonomy of a website may not make the connections you need as a consumer. Within product names and descriptions, the term "jacket" may exclude a product labeled a "coat," for example.

Knowledge graphs work to structure data around conversational language. The more specific a consumer is in a website's search, the more advanced the results.

Rather than searching "winter jacket," a consumer can search for "women's winter jacket for hiking in the rain." Structuring a website's product information, uses, features, and details within a knowledge graph can return the most accurate results, giving the consumer exactly what they're looking for.

Not only is this approach the shortest distance between what a consumer wants and what a brand has, but it functions within the bounds of natural language, all without relying on surreptitiously collected data that exists outside of the bounds of consumer consent.

Getting Comfortable Talking to Machines

With the rise in voice search, virtual assistants, and better-quality search engines, it's hard to imagine a future where we talk to machines less. Integrating search into a website that leverages conversational AI and natural language processing gives consumers a platform to ask for exactly what they want.

As brands begin to build toward a future where mountains of data aren't readily available, structuring their consumer relationship around a dialogue will be the key to delivering the best experience possible, all while staying above board with respect to regulation and consumer expectations of privacy.

The key is being there with the right answers when your customers come to you with their many questions.

Learn more about AI and the future of digital experiences with Yext's new virtual event series and join the waitlist for Yext Chat at

*This article was originally published on Spiceworks.

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