18.2% revenue increase thanks to real-time personalization

Case Study

+18.2% revenue increase through tailored personalization at computeruniverse

The challenge was to identify customer types early in the buying process and address each one individually. To meet it, we developed a 5-step process to optimize the company's own real-time personalization. Intelligently integrating big data, user experience (UX), and real-time communication created a tailored shopping experience with a significant impact on conversions and revenue growth.

Personalization

E-Commerce

+18.2% revenue uplift

+23.8% more logins before checkout

Real-time scoring based on 200 data points

Challenges and solution

The challenge: recognizing customer types, data management, and individual communication

Founded in 1999 and based in Bad Homburg, computeruniverse GmbH is an electronics retailer that constantly faces competitive pressure. With more than 100,000 products in its range, it has a solid data foundation for big data optimization.

Data alone can't tell you what action to take. Personalization is the interface between big data and user experience.

To succeed in e-commerce, you need to interpret customer behavior and make recommendations based on data.

Two overlapping circles: "Big Data" (quantitative) on the left, "UX" (qualitative) on the right; in the overlap, a red upward-pointing arrow labeled "Personalization".

The challenge in e-commerce:

Visitors only log in during the buying process.

So how and where do you start real-time personalization strategically, with profitability in mind?

The goal was therefore to create a system that recognizes customer types and addresses them in a targeted way. Communication with the target audience was to be individualized, and relevant product recommendations were to raise the likelihood of a (repeat) purchase.

The solution: data, dynamic testing & texting

To use more data for personalization, the first concept aimed to get existing customers to log in with their data early.

Personalization happens through dynamic text in the login prompt. The arguments for logging in were aligned with the motives of each persona.

We then analyzed the booking flow and supported it with personalized information. Testing all measures at the same time allowed us to measure success quickly and refine the adjustments. An early login prompt alone led to over 20 percent more customers logging in.

Goals of the strategic realignment

Increase cart value and achieve a revenue uplift.

Build personalization measures step by step.

Better understanding of the target audience and more targeted communication.

Practical implementation

5 steps to real-time personalization

The goal was to create a system and a process that ensures measurability, brings more transparency to customer analysis, and recognizes and addresses customer types (personas).

1. Qualitative audience description with persona models

Which values, needs, and goals matter most to the target audience? Neuromarketing templates make them easier to understand.

2. Quantitative analysis

Data analysis of transaction data and identification of segments on category pages.

3. Qualitative audience description meets quantitative model

All collected data is layered on top of each other to create a digital image of the target audience and develop communication measures.

4. Scoring for real-time audience identification

Nearly 200 data points enable the distinguishing factors for real-time audience identification.

5. Neuro prediction system

All information now comes together and enables real-time communication. Website visitors are recognized and met with relevant information.

Identify customer types in real time and meet them in the buying process

The actual personalization now took place on the detail page. This is where the "advisor function" comes in as cross-selling. In this concept, suggestions for alternative products are matched to the customer types.

Product suggestions under the heading "Other customers also bought" with three items: Thrustmaster TH8A Shifter (€178.89), Thrustmaster TX Racing Wheel (€420), and Thrustmaster TSS Handbrake (€234.58), each with star ratings and the note "in stock and ready to ship".

For this, the recommendation function was extended with rules aligned to the persona's value world. This made the communication in cross-selling more relevant.

Customers added a product from a recommendation to their cart 8.63% more often when it was matched to their customer type. The higher relevance of the recommendations now shows up as increased purchase interest.

Bar chart shows an 8.63% higher add-to-cart value for recommended products in the test variant compared to the control group.

Sample information: 95% CTBO, > 3,500 conversions per variant, runtime > 1 business cycle

Project successes at a glance

Instead of "one size fits all," computeruniverse is now moving into the era of personalized real-time communication and the dynamic online store. Measurable results and clear measures will keep strengthening the online store in the future.

This is made possible by the interplay of qualitative and quantitative methods, data, testing, and well-considered audience models. An increase of over 18 percent in revenue speaks for itself.

+18.2% revenue uplift

And a 7.9% increase in sales conversion through benefit communication in the cart.

+8.63% add-to-cart

Increased add-to-cart conversion through targeted product recommendations.

+23.8% more logins

Personalized communication gets customers to log in before they reach the cart.

Interested in a consultation or more references?

Gabriel Beck

Member of the Executive Board

+49 40 60 94 32 660 gabriel.beck@konversionskraft.de

Does our way of thinking resonate with you? Then we should work together.

Send us a no-obligation inquiry and tell us how we can support your mission. We'll get back to you within 48 hours.

Weitere Case Studies aus verschiedenen Branchen

D2C

Rapid Growth Engine

+54%

Conversion rate in three months

Three experiments per week, the first after 13 days.

AI delivers customer understanding and tests in days instead of weeks. 59% of experiments win; the benchmark is 20 to 30%.

Case lesen 6 Min.

Electronics

Personalization

+18.2%

more revenue

Recognizing customer types before anyone logs in.

From 200 data points, a profile of each visitor emerges in real time. The messaging adapts long before checkout begins.

Case lesen 4 Min.

Fashion

Personalization

> +10% RPV

in 4 weeks

From tool to first personalization in four weeks.

A few clearly justified use cases instead of hundreds of possibilities. All three first experiences beat the control group.

Case lesen 3 Min.

Well-known German fashion brandFashion

Conversion optimization

+€44.88 million

Net revenue in three years

Customers preferred buying in the store. That became a test.

A Motivation Lab showed why customers hesitate in the shop. From that grew a program of 50 to 60 experiments a year.

Case lesen 5 Min.

Telecommunications

Conversion optimization

+30%

more orders, cumulative

Two thirds of all tests successful, with a success guarantee.

A proof of concept with uplift targets agreed in advance proved the value of experimentation. Today freenet runs the program itself.

Case lesen 4 Min.

D2C

Customer centricity

7 jobs

Purchase motives built into the product

Seven purchase motives that reached all the way into the packaging.

Ten jobs-to-be-done interviews revealed what turns first-time buyers into repeat customers. air up used the results in shop, product, and service.

Case lesen 5 Min.

Sneakers & streetwear

Customer retention & loyalty

+22%

more contribution margin

More orders don't automatically mean more profit.

We followed A/B tests all the way into the merchandise management system. The variant with 43% more orders still delivered 22% more contribution margin after returns.

Case lesen 4 Min.

International vacation rental providerTravel

Customer centricity

+15.3%

Revenue per visitor