According to a 2021 survey, 67% of internet users are more concerned with their privacy than ever before [1]. In response to constantly evolving regulations and privacy concerns, Google recently announced that it will cease supporting third-party cookies on its web browser, Chrome, by 2024[2]. Other browser providers like Apple’s Safari and the open-source browser, Firefox have also abandoned third-party cookies. Thankfully, there is an alternative solution, and AI comes to the rescue.

Traditionally, third-party tracking has been the backbone of online advertising. Without access to this data, marketers will have to strategize alternative ways to drive data-driven marketing campaigns. Besides first and second-party data, AI has proven to be instrumental in collecting customer data and using it to unlock insights for more effective campaigns.

This article will explore how the loss of third-party cookie data will affect advertisers, how marketers can prepare for the loss of third-party cookie data, and how you can leverage AI to gain insights in a cookie-less world.

Why are browsers killing third-party cookies?

Digital marketers often use fingerprinting to provide personalized ads. This controversial technique relies on user-specific browser ID tags generated by third-party cookies [3]. These online user identifiers are typically set by a third-party platform or the website’s technology provider. The 3rd party cookies are stored on the users’ devices.

Companies have traditionally used third-party cookies to track website visitors, collect user data to provide targeted ads, and improve user experience. The main advantage of cookies is that they enable advertisers to track users’ browsing behavior throughout the entire web, within a specific browser, not just on the company’s website.

Essentially, cookies don’t allow users to control where and how their personal data is used. This has led to a growing distrust of 3rd-party cookies, prompting users to demand better privacy, transparency, and control over how their data is used.
Various data protection regulations, including California’s CCPA and Europe’s CDPR, allow users to choose whom to entrust their data and inform them how their data is being used.

Therefore, to keep up with regulations and address users’ privacy concerns, some browser application providers like Apple and Mozilla have already disabled third-party cookies. Google is set to follow suit soon.

How will the loss of third-party cookies affect advertisers?

Cross-site audience targeting might soon be a thing of the past when all major browsers stop supporting cookies. Unless advertisers figure out a way to circumvent this issue, it will be nearly impossible for them to set up audience targeting and frequency capping for most internet users.

The resulting shortage of customer data might limit the effectiveness of digital advertising campaigns, which will be evidenced by an overflow of non-personalized ads all over the internet.

Similarly, web publishers could lose up to $10 in ad revenue due to a shrinkage in ad personalization options [4]. Google estimates that some publishers could lose approximately 50% to 70% of their revenue unless they reinvent their approach to ad and data management [5].

On the bright side, several B2C companies have already started coming up with alternatives to third-party cookies, like leveraging first-party user data from their CDP and CRM platforms and offline contacts to customize their targeting techniques to sell more products to loyal customers.

How marketers can prepare for the loss of third-party cookie data

Amid the rapidly changing marketing ecosystem, there are steps companies can take to prepare and adapt to the changes as they seek alternatives to third-party cookies. Some of the most effective actions businesses can take include:

Unifying first-party data

The primary purpose of collecting customer data for businesses is to understand who their customers are and what they care about. Since cookie data is out of the equation, the only remaining data source for companies is first-party data.

First-party data is any data collected directly from the consumer. This data has several advantages over cookie data, especially when it comes to relevance and accuracy, making it a viable alternative to third-party cookies. That said, before any company can leverage this data, it first needs to unify all collected data from different sources and visits.

By unifying first-party data, businesses can better create a more comprehensive user profile, complete with demographic and user behavior information. Companies can unify first-party data through:

• Deterministic matching
• Probabilistic matching

Deterministic matching typically involves using known identifiers like names and email addresses to match all visits and site activities to one user. Conversely, probabilistic matching involves using less personal identifiers like web browsers or geolocation data and probability to match user visits and activities.

Investing in alternative data enrichment methods

Despite the availability of first-party data, the information comes with many gaps, which were traditionally filled with cookie data to gain relevant insights. Essentially, cookie data reduces the guesswork by enabling companies to form a unified customer profile.

Therefore, marketers need to find alternative ways of enriching customer data without cookie data. They can focus on extrapolating user preferences from the limited first-party data they have on hand. For instance, they can attempt to predict keywords that represent each user’s unique interests. When combined with data on user behavior, these predictions can provide insights into what each user is looking for.

Analyzing data, predicting behavior and adjusting their strategies accordingly

The process doesn’t just end at unifying and enriching first-party data. Marketers also need to analyze it for insights. Data analysis allows marketers to discover user behavior patterns and existing barriers to conversion. When well executed, marketers can create better strategies that don’t rely on cookie data.

Ultimately, data analysis can give companies a competitive advantage by giving them a better view of their potential customers and enabling them to anticipate their customers’ wants and needs.

Read more about AI in Digital Marketing: How To Use Data for Better Customer Experience, Customer 360

How AI can help to tackle ending third-party cookies

By leveraging AI capabilities to replace the data they would have gained from 3rd party cookies, companies can automate time-consuming manual processes, allocate marketing budgets effectively, and make more effective business decisions. Here are a few ways companies can incorporate AI in their marketing strategies as an alternative to third-party cookies.

Customer targeting and generating customer profiles

Every customer segment has unique interests and experiences with your brand. Therefore, using the same message across all customer segments throughout your campaign is a sure way to throw your marketing budget down the drain.

Marketo recently performed a survey on 2200 customers. Of the participants, 78.6% said they were more likely to engage with a brand whose offers are directly tied to how they have previously interacted with the brand[6]. Simply put, customers want personalization.

With AI, companies can effectively discover which customer profiles generate the highest conversion and engagement – all from first and second-party data. Companies can also gain insights into customer geographic data, which could come in handy in their marketing campaigns.

When leveraging AI for this purpose, you first need to integrate all past and future campaigns. You can include data from Google Analytics as well. This way, your AI software will have enough data to discover the highest-converting audiences.
Once you’ve got that covered, you can target the customer segments in new campaigns and test them through audits to determine the effectiveness of your campaign. The data from the audits can help you retarget your audience with the messages they resonate best with.

Sales forecasting

Businesses can now leverage AI capabilities to predict how their future marketing campaigns will perform. Through predictive analytics, AI software can forecast sales. This allows sales teams to plan inventory replenishment and scale effectively.

Predictive analytics uses machine learning models trained with historical and real-time first-party data. Therefore, the strategy becomes more accurate the more you use it. AI-powered predictive analytics models can help a business determine which strategies or channels are contributing to reaching their intended KPIs and which ones aren’t.

Automating previously manual marketing processes

According to a HubSpot report, marketing teams spend about 16 hours a week on routine tasks [7]. To put this in more perspective, that’s almost half their workweek. AI can help automate some manual, time-consuming processes, including ad formats and creative production at scale.

There are already several off-the-shelf solutions that can help you create multiple variants of the same creative master. But, with AI, you can take it a step further by measuring what drives conversion across each platform. For instance, AI can help you gain insights on where to display a product, when to show a logo, and how to label a call to action for the best results. AI can also enhance digital marketing through computer vision in creative analytics.

Crafting personalized customer experiences

The loss of third-party data will negatively impact personalization. However, by leveraging AI capabilities, companies can still offer personalized content and excellent customer support to each customer.

AI can use first-party data to analyze past purchases and offer recommendations based on each customer’s unique needs. Businesses can also use AI-powered chatbots to boost customer engagement and satisfaction; the result is more sales and greater customer retention.

Contextual advertising

Contextual advertising focuses on displaying ads based on context on certain parts of the website to catch the visitors’ attention. The ‘context,’ in this case, could be based on the user’s location, weather, or website content.

AI tools like IBM Watson Advertising Generator use predictive analytics and contextual advertising algorithms to cluster customers into different groups and provide timely, relevant, and interesting ads. This way, businesses can provide effective ads without using invasive tracking techniques.

Final thoughts on AI as an alternative to third-party cookies

Despite the looming fears that the end of third-party cookies may be too disruptive for the advertising ecosystem, AI has proven to be an effective and efficient alternative to third-party cookies. AI allows companies to phase out traditional privacy-breaching advertising methods for better, more accurate, and trustworthy advertising practices. ee more about AI consulting services.

References

[1] Statista.com. Online Privacy. URL: https://www.statista.com/topics/2476/online-privacy/#dossierKeyfigures. Accessed December 6, 2022
[2] Blog.Google. Charting a Course Towards a More Privacy-First Web. URL: https://blog.google/products/ads-commerce/a-more-privacy-first-web/. Accessed December 6, 2022
[3] Diday.com. What is Device Fingerprinting. URL: https://digiday.com/marketing/what-is-device-fingerprinting/. Accessed December 9, 2022
[4] Adage.com. Publishers Risk Losing 10billion. Thanks to Cookie Cuts. URL: https://adage.com/article/digital/publishers-risk-losing-10-billion-thanks-cookie-cuts-and-brands-are-not-ready-data-changes-iab-says/2321031. Accessed December 9, 2022
[5] Services. google.com. Disabling Third Party Cookies. URL: https://services.google.com/fh/files/misc/disabling_third-party_cookies_publisher_revenue.pdf. Accessed December 9, 2022
[6] Prnewswire.com. Consumers to brands-the the louder you scream, the less we care. URL:  https://www.prnewswire.com/news-releases/consumers-to-brands-the-louder-you-scream-the-less-we-care-300102426.html. Accessed December 9, 2022
[7] Hubspot.com. Marketers Routine Tasks. URL: https://blog.hubspot.com/marketing/marketers-routine-tasks-data, Accessed December 9, 2022

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