Customer Analytics – Make data-driven Decisions

Customer Analytics brings together all your customer information in one place. Analyse customer structure and behaviour, product groups and channels, and much more. Gain valuable insights and use clear dashboards to make data-driven decisions.

Header graphic: DYMATRIX Customer Analytics

Measurable and visible Impact: This is what our Customer Analytics offers

With our powerful analytics and clear dashboards from Customer Analytics, you have all the important key figures at a glance – from customer behaviour and campaign performance to sales potential. Discover how customer groups are developing, which channels are particularly successful and how you can identify trends early on to make informed decisions. Analyse your products in a targeted way and identify new revenue opportunities – tailored to your goals. Customer Analytics is web-based, so you can access your reports quickly and easily at any time. Export or share dashboards directly from Customer Analytics, for example, to use them for presentations.

USP graphic: Gaining a holistic understanding of the customer
Holistic Customer Understanding


Gain deep insights into your customers' world – from the development to the performance of individual product groups and sales channels.

USP Graphics: Marketing performance is easy to measure
Measurable marketing Performance


Discover important trends at a glance – thanks to clear dashboards that vividly visualise meaningful KPIs such as CTR and ROI.

USP graphic: Being able to make data-driven decisions
Data-driven Decisions


Identify key correlations between customer and product groups, as well as across channels, to uncover valuable optimisation potential for your campaigns.

USP graphic: Meaningful visualisation of customer data
Meaningful Visualisation


Discover important trends at a glance – thanks to clear dashboards that vividly visualise complex KPIs such as CTR and ROI.

USP graphic: Seamless interface to the CDP
Seamless Interface to the CDP


Customer Analytics has direct access to our Customer Data Platform (CDP), so you can get the most out of your data.

USP graphic: Standardised reports and individual analyses
Standardised Reports and customised Analyses


Use our handy standard reports that are ready to use immediately, or create customised analyses according to your requirements.

Standard Reports or customised Dashboards – the Choice is yours!

We offer practical standard reports that you can use immediately. But customised analyses are also possible. Wondering how you can use this in practice? We present our most important standard reports.

Customer Engagement Analyses

What do my customers look like? How are they developing? How is their behaviour changing? 

Keep an eye on sociodemographic characteristics such as age structure, gender distribution, geography, etc. Gain insights into important sales figures and new customer developments. Set important key figures in a time frame and identify current trends, e.g. increased rates of returns, cancellations or terminations, or declining sales trends in certain channels or product groups.

Screenshot of the customer analytics interface with customer engagement analyses and intuitive display

Campaign Performance Analysis

How many people were reached? How did the segments react? How did the performance of the purchasing channels compare?

Evaluate individual measures such as mailings or complex campaign routes quickly and easily. The KPI dashboard shows you all the analyses at a glance. Detailed analyses reveal more about your customers' click and purchase behaviour. Analyse the campaign response of different target groups: the clear reporting allows you to immediately see which measures are working and where there is potential for optimisation.

Screenshot from the customer analytics interface with analyses of campaign performance

Sales Channel Insights 

What are the important drivers? Sales development? Key KPIs? Customer structure per channel? Differences between channels?

Identify correlations at the level of individual branches/destinations and the web shop as well as the website. Compare the customer quality and performance of the branches/destinations with each other and over time. Which locations need more support, for example, even though they basically have a good customer structure?

Screenshot from the Customer Analytics interface with analyses of various cost centres in the sales channels

Product Insights

What are the driving and control functions from a product perspective? Customer structure per brand/range? Cross-selling/upselling? 

Analyse the connection between product brands, customers and buying behaviour. Identify the customer structure underlying the buyers of a brand and define the target group of your brand campaign as accurately as possible. Identify the sales potential per brand, e.g. in seasonal rhythms per customer group. 

Screenshot of the interface from the Product Insights of Customer Analytics

Understand Customers and optimise Campaigns!

Get off to a flying Start with our Customer Experience Platform

Create a customer experience with maximum business impact! Our platform, which offers you not only valuable customer insights but also the complete package from customer profiles and marketing automation to AI forecasts and CRM to web analytics and onsite personalisation, is the right solution for your company.

Infographic: Customer analytics as part of the customer experience platform

Data Science Consulting

Our data science services offer tailored support in the fields of analytics, machine learning (ML) and AI. We help you to reliably understand and evaluate your data in the CXP!

Your DYMATRIX experts for data science consulting
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FAQ

Frequently asked questions about Customer Analytics.

Customer Analytics provides deep insights into the behaviour, needs, desires and expectations of customers that are gained from analysing data. They provide companies with valuable information about how customers interact with their products or services, what they prefer and what factors influence their purchasing decisions. 

  • Demographic data: Information such as the customer's age, gender, education and income.
  • Behavioural data: Data on purchasing behaviour, product usage and interaction with the brand.
  • Psychographic data: Insights into the customer's lifestyle, attitudes and motivations.
  • Feedback and opinions: Direct feedback from customers in the form of ratings, complaints or suggestions.

DYMATRIX offers solutions in the field of customer relationship management (CRM) and marketing automation, including tools for customer insights and predictive analytics. Here are the fundamental differences between these two offers:

DYMATRIX Customer Analytics

  • Objective: The objective of Customer Customer Analytics is to gain a deep understanding of customers. This includes collecting, analysing and interpreting data about the behaviour, preferences and needs of customers.
  • Functions: This tool focuses on analysing historical data to identify patterns and trends that provide insights into customer behaviour.
  • Application: The insights gained help companies optimise their marketing strategies, improve customer experience and increase customer loyalty.

DYMATRIX Predictive Analytics

  • Objective: The objective of Predictive Analytics is to predict future customer behaviour. This is based on the insights gained and the application of predictive analysis models.
  • Functions: This tool uses algorithms of machine learning and statistical models to predict future actions or decisions of customers.
  • Example of use: The predictions can be used for a variety of purposes, such as predicting customer churn, the next purchase, or identifying potentially lucrative customers.

In summary, the CXP produkt Customer Analytics is designed to collect and understand data. With this tool, you analyse what characterises your customers and how they behave. The CXP Predictive Analytics product aims to use these insights to predict future behaviour and events using AI. The two tools complement each other by providing data-driven insights into current customer behaviour and, building on this, predicting future actions.