Modern companies try to acquire new customers and to maintain existing ones by providing better products and
services at the right moment for the best price. Especially in the digital age better customer communication
and personalization through digital channels becomes crucial. It is a commonly known fact that
personalization significantly reduces acquisition costs and increases the efficiency of marketing. Thus,
the companies struggle for providing personalized customer experience throughout the whole customer journey.
Today, the quality of marketing and sales processes increases and the new technologies from the area of
data analytics facilitate this development significantly. Enterprises extend their existing systems through
analytical CRM and start dealing with predictive personalization, personal recommendations and
highly effective digital marketing campaigns.
However, customer experience management is a complex data-driven analytical process. Building up a
structured automated and intelligent customer monitoring, segmentation and targeting continues to be a big
challenge. Exactly in this context, we provide our “Customer Segmentation” self-service analytical
solution, which embraces all the essential analytical approaches and steps for effectively managing the customer
journeys in the company.
The solution is based on structured customer lifecycle management, continuous client state and transition
monitoring as well as intelligent targeting recommendations. Our main focus lies on business indicators
like customer cohort, sleeping/active client, churn/retention rate, loyalty level and favourite product category.
To achieve that, we operate with typical KPIs like average order value, purchase rate and pace,
CLV, ABC and RFM. Such essential tasks as 3600 customer profile creation, multivariate customer
segmentation, continuous KPIs monitoring, response and churn rates estimation as well as best personal offer
recommendations are automatically executed within our solution.
The input data requirements are straightforward. The transactional data (derived from ERP) and
customer profile data (derived from CRM) are sufficient. The whole solution is easily extendable through
machine learning and data mining components for better client scoring, microsegmentation, uplift modeling,
response prediction, cross and up-selling recommendations.
As a result the company gets a structured customer base, lifecycle transition rates, up-to-date customer segmentation,
automatic detection of customer churn and retention. Since the solution is based on continuous monitoring
of business KPIs, it avoids biased conclusions and provides comprehensible recommendations. These include
recommendations for marketing campaigns, personal targeting and price markups; moreover automated campaign
management and evaluation is continuously executed. Therefore, the use of our solution leads to a significant
increase in sales and customer loyalty, reduction of customer churn and better positioning of the brand.
Use the ADEAL approach and care for your customers better!