Cookies had a good run. The third-party data trackers beloved by marketers have been a part of the consumer web experience since the launch of Netscape in 1994. But, in an effort to position themselves as guardians of consumer privacy—and to comply with increasing regulations—tech giants Apple, Mozilla, and Google have rendered cookies virtually obsolete. Welcome to the cookieless future: Good for consumers, a pain for enterprises—unless you embrace Generative AI and first-party data.
About 80% of advertisers rely on third-party cookies and now must explore new ways to engage with customers. Apple’s iOS 14 app tracking permission requirement has been disastrous for adtech companies, with Facebook, Snap, Twitter, and YouTube losing a combined $10 billion in revenue during the two quarters following the app tracking change.
But, all hope isn’t lost. When it comes to cookies, their elimination could end up being a good thing for brands. That’s because the information cookies collect can be broad, and even useless, when it fails to properly match back to the correct user. It happens more often than you think. Take it from Gartner:
“The attribution accuracy of third-party cookies has often faltered with poor consumer identity match rates between 40% and 60%t. These developments are also an opportunity for marketers to find better ways to communicate with audiences and run effective targeted advertising, in a privacy-friendly way.”
Here we share the Persado view on why a cookieless future is actually bright if your brand embraces the tools of Generative AI and first-party data. First, let’s align on what cookies are, why they matter, and why they’re being retired.
What Are Cookies?
Cookies are small text files made up of data that websites store on browsers. Websites use the data captured by cookies, which includes usernames and passwords, to identify a user (or more accurately, their computer) as they navigate a network.
Cookies track user browsing behavior, allowing marketers to understand customer preferences better. The two main types of browser cookies—third-party and first-party:
Advertisers, analytics companies, and other websites set third-party cookies to collect data about users that have no direct relationship with a brand or organization. These cookies act as a “middleman” between websites and third-party providers, collecting information about a user’s browsing habits or preferences so that it can be used to target advertising.
When we talk about a “cookieless future” we’re talking about third-party cookies—or more specifically, we are talking about the impact of no longer having the third-party data those cookies collect. But there are also first-party cookies and data.
Websites owned by brands set first-party cookies, which store information about user preferences and visits, including language settings and data analytics. They are necessary for many websites to function properly and provide a good user experience. For instance, when a customer logs into their account with your brand or adds items to a shopping cart, first-party cookies will save that information to inform the user’s next visit.
Note as well the relationship between first-party cookies, which gather web browsing information automatically, and first-party data, which consumers give to those same brands willingly and with consent.
Examples of first-party data include:
- Demographic information
- Customer feedback
- Survey data
- Purchase history
- Actions taken on a company’s website, app, or product
- Data found in a company’s CRM
Why are third-party cookies going away and what is the impact?
This process has been underway since 2019, when Mozilla’s Firefox web browser joined Apple’s Safari in announcing it would block third-party cookies by default. The next year, Google declared it would phase out third-party cookies on its Chrome web browser, used by more than 60% of the world’s internet users. Then in September 2021, Apple’s iOS 14 update began to require apps to ask permission to track users (many of whom say, “No thanks!”).
All of these actions have been motivated by increased consumer awareness and concern about the volume of personal data that web companies collect and use. At its core, the move to a cookieless future is about privacy.
Although Google has delayed the demise of third-party cookies to 2024 as it tests less intrusive means of delivering targeted advertising (like Google Privacy Sandbox), it’s safe to say cookies are dead—or at least, nearly dead.
What are brands doing to prepare for a cookieless future?
In a survey by Forrester, 76% of marketing respondents said they are collecting more first-party data in response to data deprecation (defined as difficulty in collecting and activating consumer data as a result of restrictions).
The reason why is that first-party data comes directly from customers through a company’s owned channels, giving it higher accuracy than third-party data. As such, it can be leveraged to create more meaningful experiences through personalization.
“Personalization is a force multiplier—and business necessity—one that more than 70% of consumers now consider a basic expectation.”McKinsey
So how can brands differentiate their personalization efforts from those of their competitors? With AI-generated language.
Activate first-party data with language
Brands have long collected data about customers behavior and matched it, when possible, with identifiers they could use to categorize customers based on demographics (gender, age, or income) or psychographics (purchase behavior and motivation). Yet individual customers often defy these categories. Collecting, cleaning, and analyzing data to make it usable can also be challenging. Third-party cookies offered a helpful compromise in the form of a usable, behavior-based view of customer digital activity.
But, brands don’t need to make that compromise anymore due to advances in marketing technology and data maturity. In fact, brands that thrive from this shift won’t just use the data they have to communicate with existing customers. They will activate it by combining Generative AI with first-party data to deliver language personalization. In this way, brands will speak to customers on the web, through email, and within apps in a way that engages them. The cookieless future will be brighter, and more personal, than what came before.
Language data refers to the words, concepts, tone, and visual formatting that best motivates a given customer to take the next set of actions.
Generative AI combined with first-party data sources can enable brands to deliver messages that engage customers. Persado’s adaptive algorithm can enable brands to serve up the language customers are most likely to respond to. This isn’t a future vision. It’s already here.
One retailer with a long history of issuing weekly coupons, for example, leveraged the first-party data housed in its customer data platform to segment customers into different personas. The brand then worked with Persado to use its Generative AI with the first-party data to customize messages and engage each persona in a way that was less coupon-dependent.
The result has allowed the brand to distinguish loyal shoppers who don’t need a coupon from those who might hesitate to shop without one. For coupon users, the brand further personalized to deliver distinct coupon types based on customer behavior. The result is differentiated, targeted engagement that produced an estimated $10 million in incremental revenue in the first year.
For brands like this one, the death of third-party data isn’t the end of effective marketing. It’s an opportunity to activate the customer data they already own—data about the language that best connects with customers. These brands are delivering more relevant customer interactions than before to create powerful business impact.
Leverage Generative AI and first-party data to connect with audiences
The power of personalized language is not limited to existing customers, either. One benefit of cookies came through programmatic advertising on third-party sites to engage audiences for whom you don’t yet have first-party data. Yet even without cookies, brands can place relevant messages on channels to build awareness and gather insights into how anonymized audiences respond to certain words, tone, and concepts.
For example, a credit card issuer worked with Persado—an enterprise Generative AI provider—to gain more traction for a loyalty card. It did so by personalizing the language on their Facebook ads. Based on real-time viewer behavior, the card issuers adapted the message to highlight different loyalty benefits to appeal to a given user. Persado could still optimize and learn without collecting identifying user data.
Being able to speak in a relevant way to audiences without collecting personal or identifying information will become more important in the coming years. A 2022 Ipsos poll found an overwhelming majority (84%) of Americans say that they are at least somewhat concerned about the safety and privacy of the personal data that they provide on the internet.
Generative AI combined with first party data can play a role in creating more custom experiences based on the insights data brands already have. It can also couple that data with real-time insights into how customers act based on brand messages. These technologies, the core of the Persado platform, don’t just generate personalized language. They predict the best performing messages so executives can drive material outcomes across communications without relying on private data.
Personalize language across the omnichannel journey
Activating first-party data for awareness and acquisition is just a first step. Over time, brands will leverage new capabilities to improve and personalize across the organization. Onboarding, customer service, renewal, and upselling can all be more relevant and effective using the same first-party resources.
With experience, brands will learn more about the data that customers freely share in exchange for better service. Brands must do so while also soothing customer anxiety over how they plan to use the data. As Gartner notes: “Customers expect their data to remain private and secure, but at the same time, they desire a personalized and contextualized experience.” It’s a balancing act brands juggle.
This can be a struggle for brands that are still figuring out how to reward customers who are willing to share their data with more personalized content experiences. The answer is an Generative AI that can produce natural language faster than humans alone, paired with multivariate experimentation and machine learning, to crack content personalization. The capabilities of a Generative AI built on an enterprise language knowledge base is a secret weapon for brands. With enterprise-grade Generative AI brands can leverage language personalization to increase engagement and conversions with messaging that’s proven to perform for each individual segment and channel. Schedule a demo with Persado to learn more about how your brand can benefit.