3 min read

How Experimentation Drives Insights in the Post-Cookie Landscape

How Experimentation Drives Insights in the Post-Cookie Landscape

Table of Contents

Many companies breathed a collective sigh of relief last June when Google Chrome announced it would delay removing their support of third party cookies until 2023. This effectively allows digital marketers another two years to transition away from a reliance on third-party cookies to generate and access customer data.

With a growing focus on privacy, finding a cookieless solution that ticked all the boxes was never going to be easy. The delay has generally been welcomed, but it must be recognized that it’s still just a delay. Assuredly at some point in the future, third-party cookies will disappear once and for all. The challenge at hand centers on how to generate and access better customer insights to improve the digital customer experience (CX). What should companies be focusing on now?


Cookie Value vs. Customer Value

What is missing from the objections to a cookieless future is the voice of the customer (VoC). Most customers welcome the cookie’s demise because there’s little visible value to them and presents a growing amount of privacy concerns. Pop-ups asking for cookie permissions are annoying and a source of friction in the customer journey, plus not really understanding what cookies they’re agreeing to can result in anxiety for customers. Neither of these get the customer journey off to a good start.

Some marketers continue to argue that the value of cookies is in the intent data they provide. But the reality is that unless companies are able to transform that intent data into a relevant and contextual CX, it won’t lead customers any further along the journey to buying.

When visitors land on a website, there’s a very small window of opportunity to engage them. The experience they get, largely defines whether they drop off, spend time browsing, or progress to making an online purchase. It’s their actions—what they’re looking at, which ideas they’re responding to and how they’re progressing along the customer journey that’s valuable. Cookies don’t give those answers, but experimentation can.


Maximizing the Value of Experimentation in the Customer Journey

Experimentation driven by artificial intelligence (AI) takes the basic principles of A/B testing and multivariate testing (MVT) but supercharges them. It opens up a world of possibilities by enabling companies to test hundreds of ideas in thousands or even millions of combinations, live on a website, in real time, with real customers. This generates meaningful insights quickly that inform how to improve and optimize CX. These insights are significantly more accurate than assumptions based on the demographic and intent data that third-party cookies provide.

For example: a website visitor may spend 90 seconds on a page but take no action. How does a company respond to that? What was it that made the visitor pause? By experimenting with different ideas and seeing how visitors respond to those ideas, one can identify points of friction in the customer journey, which can then be improved upon.


Better CX Through Better Use of Customer Data

Where AI makes this more effective is that it’s able to handle the complexity of thousands of ideas and combinations. Instead of getting bogged down in the complexity of it all (as a human might), AI is able to leverage the data to show which ideas are moving visitors further along the customer journey. To be really specific, each step can be considered a micro-conversion that strives to ultimately get visitors to click the buy button and become a customer.

Each interaction with visitors generates data. Being able to better leverage that data through AI-driven optimization and experimentation enables companies to serve up rich and relevant content that improves CX. The fundamental difference is that experimentation uses the knowledge gained from the last customer to optimize the CX for the next visitor.

With CX being recognized by many analysts and luminaries as one of the most significant drivers for growth, it is an area that most companies are looking to improve. But it’s a complex task because each visitor is unique, with unique preferences that change over time. Historic visitor and customer data has some value, but even more valuable is how visitors respond in real time to what they experience on a website or mobile app. Optimizing CX is having the ability to experiment with ideas to  better adjust to visitors and their changing needs while browsing.

Using AI to experiment with hundreds of ideas and having the ability to change these ideas mid experiment to adjust to customers enables companies to optimize CX in meaningful ways which directly impacts outcomes such as achieving growth targets. Instead of worrying about the demise of cookies, companies that want to keep ahead of the game should be looking at how to better leverage the customer data they already have and experimenting at scale to serve up better CX.

What is Realized Performance in Experimentation?

2 min read

What is Realized Performance in Experimentation?

Evolv AI offers a number of ways to understand how your optimization is performing overall. One of these indicators is realized performance, which...

AI in UX Design: Revolutionizing the User Experience Design Process

6 min read

AI in UX Design: Revolutionizing the User Experience Design Process

The user experience design process is evolving at an unprecedented rate, largely driven by advances in artificial intelligence (AI). As businesses...

AI Marketing Strategies for Enhanced Engagement

10 min read

AI Marketing Strategies for Enhanced Engagement

Technological advancements have markedly influenced the evolution of marketing strategies and their impact on customer engagement, with artificial...