It’s not surprising that all top performing websites use 1:1 personalization to improve their customer experiences and maximize their results. How do they do this at scale? Which CRO methodology works best? The answer is: all of them, if used for the right purpose.
In our personal lives, we’ve come to expect personalized experiences from the websites we visit and use. When we first log into Netflix we’re met with a carefully chosen selection of movies and TV shows based on our tastes. In subsequent sessions, it’s further curated to suit our previous viewing history. Netflix learns about us in every session.
When we visit Amazon we see a set of products catered around our previous purchases, items we have viewed in the past, and a ton of other data about us (like, a ton…).
But when we visit most websites, we see the exact same thing as everyone else. All nuance and uniqueness about us as individuals is ignored as we’re pushed into a one size fits all experience. This happens all too often, especially when we click through from an ad to a landing page and are met with an irrelevant experience. As marketers, we should be delivering a tailored experience that meets all of our customers’ needs and helps us maximize every last ad dollar.
In this blog post, we’ll share how you can provide the best personalized experience by using the right CRO approach for the right task when optimizing conversion rates.
Let’s first turn our attention to the tried and true methodology of A/B testing and multivariate testing (MVT). This methodology allows businesses to test ideas against each other to find which idea is the best at converting visitors, using a signal (statistical significance). The objective is to test ideas to ascertain a conclusion.
However, once a winning idea has been found, it’s typically baked into the website and served to everyone. This goes against the CX ideal of personalization for each website visitor, on each visit. In fact, it’s not personalized at all from that point.
A/B testing and MVT are powerful tools to find ideas that work for everyone, but they don’t provide visitors with personalized experiences. That’s not to say that these approaches don’t have value—they certainly do! They’re best suited for ideas around core website functionality like:
A/B and MVT offer a powerful mechanism that helps businesses choose the best one size fits all experience.
For most businesses the first step towards personalization is to implement a rules-based approach. Rules-based personalization allows businesses to tap into the insights we have about our customers and to deliver relevant experiences based on those insights.
However, rules are not perfect. This can be understood better by thinking about rules as “If this, then that” statements. For example, if the visitor is from NYC, then show images of the Brooklyn Bridge. Rules require us to have a “this”, aka a piece of data that helps us understand who the visitor is.
In my experience, marketers are dependent on 3rd party de-anonymization solutions to provide more robust insights against their website visitors, but this isn’t a perfect source of data. For example, as COVID allowed more people to work from home, we’ve noticed a decrease in the ability to match a visitor to a business.
To make matters worse, if a business predominately sells to small businesses, and match rates are very low. One customer I’ve worked with was getting 3rd party insights for only 10% of their total web traffic. That means you don’t have a “this” for 90% of the traffic!
The other complication is nailing the “that”. How do we actually know the best experience to provide to a specific cohort of visitors?
Most rule-based personalization is based on the marketer's belief or assumption of what the visitor needs to see. It’s often quasi-logical: “They’re from an ecommerce company so I want to show an ecommerce-centric headline and our ecommerce case studies,” but it’s ultimately guided by intuition.
However, what if a mixture of case studies across their most recognizable logos is actually the best experience to show web visitors regardless of their industry? While we try to figure that out, we’re losing out on valuable conversions.
Even with these challenges, there are situations where rules-based experiences are optimal:
Well established and thoughtful rules can be a solid first step towards providing personalized experiences, but they are not the personalization panacea.
To provide a true 1:1 personalized experience at scale you need a different methodology. Enter Intellimize’s Continuous Conversion™.
The core philosophy underlying this approach is that the world we live in is never static so your website shouldn’t be either. Every visitor on your website is unique, bringing a unique set of needs and ever-changing context to their visit (think: competitors rebranding or releasing new products, internal changes to go-to-market strategies, or even global economic events).
However, we as marketers don’t have enough resources to continuously think through the vast number of unique experiences that are best for each individual website visitor. Even if that were possible, the ideas that were the best last week might not be relevant this week.
To truly enable 1:1 personalization at scale, we need machine learning to optimize all of the ideas we have and dynamically decide which combination of ideas is right for that specific visitor, at that specific moment in time, based on context, their behaviors and actions, and other data points.
And that’s just what Continuous Conversion™ does.
It allows us to focus on the things humans do best: creatively think about the experiences that are the best for different personas, for visitors in different phases in their sales cycle, for visitors in different regions, and from different types of businesses.
We already do this with search ads for Google Ads where we provide different copy ideas for a handful of headlines, body copy, and CTAs. Google dynamically decides the right combo of each for every visitor and optimizes toward a conversion goal. We do too.
With Continuous Conversion™, marketers’ ideas are continuously (pun intended) tested and retested. There’s no need to inform Intellimize that something in the world has changed—the machine learning automatically recognizes that based on changes in visitor behavior against the core goal of a website, no babysitting required. It’s constantly working to learn and improve, even when you’re not.
Continuous Conversion™ is extremely powerful when we don’t have perfect insight about our website visitors and don’t know the best ideas to show specific visitor segments. Here are just a few examples where Continuous Conversion™ is unrivaled:
To make the most of every ad dollar we need to dynamically curate the best experience for every web visitor and optimize these experiences toward a conversion goal. In order to achieve this, there are different methodologies to be understood and leveraged.
Awareness of these approaches and the strengths and weaknesses of each will help CRO practitioners to discern the right approach for each task.
Intellimize is a single-source website optimization and dynamic personalization platform that enables marketers to leverage each methodology mentioned above, as each has its benefits. The ability to utilize the best approach on a per idea basis is how Intellimize help customers increase their conversion rates. Just see how we've helped customers like Drift boost leads by 322% and Dermalogica achieve a 100% lift on adding items to bag.
If you’d like to learn more don’t hesitate to make time to talk with one of our conversion experts.