Predictive personalization: why it matters and how Contentsquare fuels it

With generative AI accelerating production, there’s more content being produced than ever before. But more content doesn’t necessarily mean more engagement, more conversions, more revenue. 

Because with all that content comes a ton of irrelevant experiences and messages—and it's the relevant experiences and messages that stand out.

That’s why it’s more important than ever to get personalization right. 

And most brands aren’t great at personalization. If you feel like that includes your brand, hey: don’t take it personally. According to personalization expert Mark Abraham, only 10% of brands are personalization leaders. 

But don’t worry, help is here. This article will look into 

• How predictive personalization enables brands to deliver highly relevant, satisfying experiences

• How the Contentsquare platform helps enable personalization through behavioral insights

• How combining Contentsquare with personalization system Mastercard Dynamic Yield takes your predictive personalization efforts to new heights

You’ll also learn how electronic consumer goods retailer Elkjøp Nordic personalizes experiences in real-time using Mastercard Dynamic Yield, powered (in part) by insights from Contentsquare.

What is predictive personalization?

We’ve all heard the saying ‘the customer is always right’. But the goal of predictive personalization is ‘you’re always right about the customer’.

It’s about anticipating customer needs and preferences and tailoring the customer experience to meet them. (This also includes not messaging, notifying, or prompting them when you can predict it’ll annoy them.)

To see into your customers’ futures, you don’t need tarot cards or a crystal ball. Thanks to AI and machine learning algorithms, you can now analyze your customer data to spot patterns and trends that let you anticipate what they’ll respond most positively to.

What does predictive personalization look like? Here are 5 examples from a range of industries:

1. Retailers and ecommerce companies recommend products based on customers’ browsing histories, predict when customers might need to reorder essentials, and offer personalized discounts

2. Financial service companies use customers' behavioral data and stated financial goals to give customers personalized budgeting tips and investment advice

3. Travel companies suggest next destinations or hotels based on past trips, anticipate travel needs, and offer personalized travel packages 

4. Software platforms automatically customize dashboards, menus, and workflows based on user roles and usage patterns

5. Energy providers provide personalized usage insights, peak-time alerts, and customized energy-saving recommendations

What are the benefits of predictive personalization?

When done badly, personalization can backfire. Any of these scenarios sound familiar?

• A company is recommending you buy a product that you already bought 6 months ago

• Out of sheer idle curiosity, you looked into how much vacations to Siberia cost—and now you’re seeing nothing but package holidays to Siberia your recommendations

• You’ve received an email from your bank that opens “Hey >>first name<<! We really value you as an individual…” 

Experiences like this are both irritating and alienating. Instead of telling you the company sees who you are and cares about you, it tells you they have no idea who you are and couldn’t care less.

However, getting personalization right pays off. According to management consulting firm McKinsey, “Companies with faster growth rates derive 40 percent more of their revenue from personalization than their slower-growing counterparts.” 

How predictive personalization generates extra revenue

• It engages customers: relevant and timely experiences raise user engagement and satisfaction to new heights

• It boosts conversion rates: shocking news here, but recommending customers products, services, and content they’re probably going to like results in more sales. Recommending combs to a bald man? Not so much.

• It enhances loyalty and wins trust: when customers feel understood and valued, they’re more likely to be loyal to a brand. And they’re more willing to open up. As Mark Abraham says in his TED Talk: “Personalize experiences and customers will be willing to give you their data.”

• Reducing marketing costs: by targeting the right customers with the right message at the right time, predictive personalization can optimize marketing efforts and reduce wasted spend 

Now you’ve got a taste of what predictive personalization can do for your business, you’re probably asking ‘how can we ensure we pull off predictive personalization properly?’

The data you need for predictive personalization—and how Contentsquare helps you get it

To anticipate what customers want when they show up to your site or log in to your app, you need to understand their past actions and listen to what they tell you through your communication channels.

You’re going to need 2 types of data here…

First, quantitative data: numerical data that can be counted and measured. This includes:

• Behavioral data (such as pageviews, click-through rates, conversion rate, and average order value)

• Demographic data (such as age, gender, and income level.)

• Firmographic data (such as size of company, industry, and revenue)

Second, qualitative data. This is non-numeric information, including

• Zero-party (intentionally shared) data such as declared preferences (for example, for communication frequency), self-identification, and customer feedback (captured through voice of customer surveys or feedback collection forms)

• Contextual behavioral insights that enable you to explain why customers behaved in a certain way

While not itself a predictive personalization platform, Contentsquare’s experience intelligence platform is an AI-powered goldmine of the sort of quantitative and qualitative behavioral insights you need to give your experiences that personal touch.

On the quantitative side, Contentsquare lets you capture 100% of customer interactions, thanks to its autocapture capability Smart Capture. 

With no manual tagging required, you can rest assured you have a comprehensive dataset of user behavior to analyze and share with your tech stack (including predictive models).

As for qualitative insights, Contentsquare gives you an Experience Analytics product with a whole suite of tools to retroactively analyze and get to the bottom of your user behavior. 

Our platform’s AI, Sense, makes it easy for anyone—not just data analysts—to conduct iterative analysis and get visually intuitive, highly shareable insights.

And then there’s feedback. Contentsquare’s Voice-of-Customer (VoC) product makes it easy to solicit, analyze, and act on feedback at speed and scale. Set up surveys in seconds, use Sense to filter and analyze responses, and apply experience analytics to understand the behavior that led to confusing feedback.

Using the platform’s Data Connect capability, you can then easily feed behavioral data from Contentsquare into your data warehouse, integrating seamlessly with Snowflake, BigQuery, Databricks, Redshift, and Amazon S3 without any need for custom APIs.

And that’s great news for your machine learning models and personalization tools.

Let’s take a look at some of the ways Contentsquare helps you build more personal, relevant experiences for your customers. 

3 ways Contentsquare enhances your personalization plans

1. Identify points where personalization is sorely needed

Personalization is often most needed where customers are getting frustrated or disengaged. And Contentsquare is built (in part) to find—and understand—frustration.

Using Journey Analysis and Funnel Analysis, you can see exactly how users are navigating through your experience—including where they’re getting stuck and dropping off.

In-session VoC surveys and feedback buttons are also useful for uncovering frustration. For example, you can trigger exit-intent surveys when customers are leaving your site, or popover surveys to appear after users cancel their subscriptions.

In addition to this, Experience Monitoring will give you AI-triggered alerts when there are errors, performance issues, or customer frustration. You can then understand their potential impact on revenue using Impact Quantification.

It’s easy to get the insights you need with Sense. (And you don’t need to be a data analyst.)

Simply ask our platform’s built-in AI assistant Chat with Sense a natural language question about your users’ behavior and you’ll get an answer in seconds, complete with illustrative charts and suggested follow-up questions.

In no time at all, you’ll be able to track down places in your user journeys that could benefit from a more personal approach.

2. Analyze the impact of your personalization experiments on behavior—and revenue

Contentsquare insights can be easily and seamlessly fed into predictive personalization platforms to help you analyze the impact of your personalization efforts on customer behavior.

For example, Contentsquare can be integrated with personalization operating system Dynamic Yield by Mastercard. 

Mastercard Dynamic Yield helps businesses create and deliver personalized experiences to customers. Using AI and drawing on a unified hub of customer data, the system makes personalized recommendations and adjustments in real-time as customers interact with your site and app. It also personalizes email, SMS, push notifications, and search. 

To gauge the success of Mastercard Dynamic Yield personalization, and to understand what works so you can repeat it, you need to know exactly how it's impacting customer behavior. 

That’s where Contentsquare comes in clutch. By adding behavioral context to your A/B tests, you take the guesswork out of analyzing the results. 

Instead of speculating as to why variant A outperformed variant B, you’ll

1. Analyze the variants side-by-side Heatmaps to see where users clicked, scrolled, and swiped (and what they ignored) 

2. Use Session Replay to watch back individual user sessions and see what customers were doing before, during, and after the test variation. AI-powered Session Replay Summaries make it quick and easy to spot trends in behavior across sessions, and you can jump to specific moments of interest in each replay

3. Measure the revenue impact of your personalization tests with Impact Quantification, helping you to prove the value of your efforts to stakeholders, and to prioritize which personalization initiatives to focus on in future

In short: you can now run iterative personalization tests with maximum confidence and personalize your experiences more quickly, effectively, and strategically.

3. Understand your audience segments in granular detail

Customers for any brand vary widely, which is why analyzing them en masse isn’t going to give you the nuanced picture you need to optimize every journey. 

Customer segmentation is, therefore, critical to delivering targeted, personalized experiences. By grouping your customers into cohorts based on shared characteristics, you’ll better understand their behavior and needs—and be able to create more precisely targeted experiences.

Contentsquare makes it easy to create behavioral, geographic, and technographic segments, to filter by them when conducting analysis, and to compare the behavior of different cohorts side by side (when moving through funnels, for example). 

Filters include

• Device used (mobile, desktop, tablet)

• New or returning visitor

• Session duration 

• Number of pageviews

• Users who have and haven’t clicked on a particular element

• Frustration score

Using these filters, you can understand the behavior of every conceivable segment of your audience in granular detail, and figure out what works best for different types of customers.

What’s more, you can measure the revenue value of every segment with Impact Quantification, helping you to focus on the most valuable segments when you’re optimizing and personalizing aspects of your journeys.

All of this information helps enrich the picture you have of your customers and of how they react to personalization efforts. 

You can further enrich that picture by overlaying customer segment data from Mastercard Dynamic Yield, which enables segmentation according to real-time behavioral patterns, when analyzing in Contentsquare. 

Similarly, you can use the insights you get into the behavior of particular audience segments when working on campaigns in Mastercard Dynamic Yield. 

When you understand (for example) precisely how new visitors on mobile react differently from returning visitors on mobile to personalized recommendations popping up at checkout, it gives you a huge headstart in designing personalized experiences for those segments.

How Elkjøp Nordic uses Contentsquare and Masterard Dynamic Yield to personalize and optimize experiences

Personalization leaders are all capturing, structuring, analyzing, and acting on quantitative and qualitative data—including insights from Contentsquare. 

Take, for example, electronic consumer goods retailer Elkjøp Nordic, (part of British multinational electrical and telecommunications retailer Currys PLC).

Elkjøp Nordic is the biggest consumer electronics company in the Nordics. With over 25% of the consumer electronics market share, it operates over 400 brick-and-mortar stores across Norway, Sweden, Denmark, and Finland. 

At a recent Contentsquare CX Circle event, Julia Paulsen, Director of Ecommerce at Elkjøp Nordic, guided us through how her team is using behavioral data and customer feedback to optimize Elkjøp Nordic’s website across Sweden, Finland, Denmark, and Norway, and drive millions of dollars of revenue. 

Elkjøp Nordic is transitioning from a product-central model where only 10% of what customers see online is determined by data (with 90% of what they see being determined by human and generic rules) to a model where 80% is controlled by data.

There’s no shortage of data out there, but as Julia explains, they have to be highly selective to ensure they’re making the right personalization decisions.

“We’re all swimming in data lakes these days—but you might get bitten by a big (or small) fish if you’re not thinking about what data you actually need and actually use,” she says. “You need to ask yourself: what data actually brings value to the customer? Because that’s what will bring value to your business.”

In Elkjøp Nordic’s case, this valuable data encompasses both quantitative and qualitative data that’s drawn from a wide range of sources, including

• Customer identity (zip-code, address, browsing history)

• Transactional data (orders)

• Product data (product attributes, popularity and trends, stock levels)

• User-generated content (reviews and ratings)

• Contextual data (device used, location)

• Third party data (advertising data)

In addition to all of these, of course, there’s behavioral data. Elkjøp Nordic uses Contentsquare to forensically track in-session behavior. They then feed this data into Mastercard Dynamic Yield to more accurately personalize customer experiences in real time. 

Find out how Elkjøp Nordic uses Mastercard Dynamic Yield to build customer-centric digital experiences in the Dynamic Yield customer story. And watch Mastercard Dynamic Yield’s interview with Julia to find out more about how the system enables her team to improve website experiences through testing and data-driven recommendations.

Businesses have to stop thinking they know what’s best for the customer and listen to the signals they’re giving us through their behavior. Customers are communicating with us with every click and bounce. Contentsquare provides us with the insights we need to listen to what they’re telling us.

Julia Paulsen,

Director of Ecommerce at Elkjøp Nordic

There’s also customer feedback. As Julia explains, Elkjøp Nordic uses feedback forms when testing optimizations to uncover customer sentiment—particularly frustration. This came in handy when the business was redesigning its website.

“Instead of going ahead and reinventing the wheel, we decided to ask the customer first,” says Julia. “Luckily for us, we weren’t short of data: we had 21,000 pieces of feedback a week! We then used AI to quickly analyze this feedback and answer the all-important question: ‘What’s wrong with our website?’” 

To find out what they discovered, how they subsequently optimized their website—starting with their checkout page—for peak season, and the impact these actions had on their conversion rates and revenue, watch Julia’s fascinating (and hilarious) CX Circle presentation in full.

Get on the elite-level personalization path today

Predictive personalization is the key to unlocking deeper customer engagement, boosting conversion rates, and fostering unwavering brand loyalty. 

Many brands struggle to master personalization, but with the right platforms, any brand can become a leader in this space. 

Contentsquare is a critical part of this equation. By combining Contentsquare's unparalleled behavioral data insights with your chosen personalization platform, you can anticipate customer needs, deliver truly relevant experiences, and prove the tangible impact of your efforts.

Ready to transform your personalization strategy and see significant growth? 

Book a demo with Contentsquare today and discover how the all-in-one platform can fuel your predictive personalization efforts.