Strengthening customer focus - what solutions exist?
The best-known customer analytics solutions in the field of data science are the following quantitative methods: (1) customer segmentation and (2) customer value analysis.
Customer segmentation
- Classify customers according to characteristics (clustering)
- Create customer groups and segments for better understanding
- Implement marketing measures in a more targeted manner
- Generating long-term and loyal customer relationships
Customer lifetime value (CLV)
- The customer value results from the customer observation
- Specific customer differentiation based on behaviour
- Identification of "good" and "bad" customers
- Mapping a clear profile of customers' preferences and wishes
- Definition and calculation of a customer value for better estimation of costs
"With Customer Analytics vennoble the revenue of your business activity by prmore precisely the customers, who offer you added value. Identify identify dissatisfied customers dissatisfied customers at an early stage and minimise their churn rate.."
Dr Eric Trumm, Head of Data Science Workshop
What is Customer Analytics?
Customer analytics enables companies to better understand their customers. This requires not only a reliable data base, but also the know-how to derive the right decisions from it. On the basis of AI and data science, solutions are designed which solutions are designed that show decisive trends and patterns in the customer data along the customer journey and thus provide a sound basis for decisions. This allows potential to be recognised more quickly and targeted measures to be initiated directly.
Without customer analytics, this is what happens:
Lack of customer centricity
Needs become not recognised and not measured.
Rising marketing costs
Through a one for all communication policy results in higher and not attributable costs.
Decline in customer satisfaction
Without Customer segmentation remain individual needs remain unrecognised.
Rising churn rate
Dissatisfied customers cancel
Which software solution do we use for customer analytics?
Data management
Predictive analyses
Python/R in cloud environment (e.g. Google Cloud Platform(GCP))
Reporting/Visualisation
Customer tool (e.g. Tableau, Qliksense) or SAP Analytics Cloud
KNOWLEDGE
Useful information
Starrag AG was faced with the challenge of automating manual processes in the finance department, in particular the time-consuming preparation of monthly reporting. The decision was made to implement the SAP Analytics Cloud (SAC), supported by the expertise of s-peers AG.
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The success story highlights the challenges and initial situation of a project at the CSS Group dealing with the budget and projection process. Previously, these processes were carried out manually using Excel files, which led to time losses, susceptibility to errors and inaccurate planning. The aim of the project was to improve this process, enable precise planning and carry out efficient extrapolation.
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