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Are Your Hyper-Personalization Efforts Working? Best Practices & What to Track

By SCUBA Insights

Every brand asks the same question: Are my personalization efforts actually working?


The numbers for hyper-personalization are there—Forbes says 46% of customers will buy more when given a personalized experience, for example. But how can you prove the ROI of your own efforts to the higher-ups? 


In this article, we’ll cover some ways to measure audience personalization in marketing and customer service. In other words, how to tell if your efforts are working, and how to prove it to you-know-who. 


What it takes to make hyper-personalization work 

“Hyper'' personalization is basically an amped-up version of the old-school marketing personalization you may remember. But we’re no longer just popping the customer’s name in the subject line and email or Facebook ad copy. 


Now, brands are personalizing the entire online experience—from search results and product recommendations to ads displayed and discounts offered. They’re optimizing content and offers based on past behaviors like purchase location and time, payment method, coupons used, and social media activity.


So, you’ve heard that old saying “Anything worth doing is worth doing well”? Set yourself up for success with some best practices for doing hyper-personalization right.


  1. 1. Talk to your customers 

Discounts, product recommendations, text message marketing, and targeted ads are some of the most desired personalized experiences for customers. But your crowd could be completely different. CX surveys like NPS or customer effort score can provide insight into what your customers want, like and don’t like. 


Pay attention to customer comments on social media, in the DMs, on sales calls, and in reviews. The customer sentiment information you find in there may be useful for messaging and customer service. Marketing attribution is getting better thanks to machine learning (ML) and AI—but never underestimate the power of a good customer feedback screenshot.


  1. 2. Diversify your data

Achieving hyper-personalization requires you to take enormous amounts of data and find actionable relationships between seemingly unconnected customer actions. 


But sales lives in Salesforce, and marketing does everything in HubSpot (or worse, Excel). Sound familiar? Find yourself a tool that can integrate data from as many different sources and formats as possible. The more points you have to work with, the more accurate your view of the customer journey, and the more opportunity to personalize the experience.


  1. 3. Improve audience segmentation 

Hyper-personalization requires building better audience segments. The smaller and more targeted your audience groupings, the more you can:


  • Tailor your customer service and support efforts 
  • Create better offers 
  • Deliver more engaging content
  • Understand and address customer challenges


So, go beyond demographics like “female, age 45 - 55, married.” Instead, imagine how your business could benefit from audiences based on values, interests, and behaviors, like: 


  • Customer satisfaction scores
  • Number of purchases
  • Timing of purchases
  • Favorite product attributes
  • Service needs
  • Browser type
  • Delivery method 


  1. 4. Prioritize testing and iteration  

To get the best results on personalized customer communications—be it CTV ads, in-app ads, or email content—you need to test different versions and track the results in real time. Which ads or videos got the most reshares, likes, and comments? Which ones led to the most conversions? 


With real-time data, you can monitor and adjust as you go. Then track, measure, make small changes, and repeat. This is the idea of making 1% improvements over time that eventually add up to something big. To encourage testing and iteration, make it easy to obtain and act on insights. For example, with an intuitive, no-code analytics tool that renders data visually, on demand.

How to measure the success of your hyper-personalization efforts

Now that you’ve got the right foundations in place, you can start gathering some data and (hopefully) make some juicy correlations. But what should you be tracking?


This will depend primarily on your audience and what you’re trying to achieve. Here are some common metrics for tracking the success of your audience personalization campaigns: 


  • Click-through rate (CTR): How many people click on a link in your marketing messages or emails.
  • Conversion rate: The percentage of people who take a desired action, like making a purchase or filling out a form.
  • Customer satisfaction: Measured through surveys, sentiment analysis, or by tracking the number of complaints or compliments you receive.
  • Customer engagement: Look at metrics like open rates, shares, comments, and likes on social media posts.
  • Increase in engagement over time: A variation on the above, this compares month-over-month engagement to see if people are becoming loyal advocates. 
  • Customer lifetime value (CLV): A measure of the average customer's value (revenue) generated over the entire relationship.
  • Customer churn: The percentage of customers who stopped using your company's product or service in a certain time period.
  • Increase in order value: Great for tracking the success of personalized product recommendations cross-selling, subscriptions, and “related products” offers. 
  • Product or feature usage: Track the number of logins in a certain time period, advanced feature usage, or customization, and (bonus) see how it correlates with CLV. 


Hyper-personalization is not a one-and-done marketing strategy. To make hyper-personalization work for better customer retention, the work is ongoing. You need a multi-faceted approach involving multiple teams, workflows, and tools. But with processes in place and fully integrated, real-time metrics at your disposal, you can position your enterprise for success with hyper-personalization. And best of all, you’ll be able to prove it. 


Want to see tracking and measurement for better hyper-personalization in action? Request a demo to see what Scuba Analytics can do.

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