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How can data analytics improve account retention?
Reading time: 4 min.
1. Identify customer needs

1.1 Customer needs are what you should focus on first in order to build long-term strong relationships with customers.

1.2 Good approach - based on data about the customer's needs, take appropriate business steps.

1.3 Please try not to fall into perception traps - build a big picture based on multiple reliable data sources and different interpretations.

14. Based on the analysis, formulate hypotheses, design and test solutions.

2. Personalize communication

2.1 Each of us always likes to feel sincere personal attention and care - treat the customer the way you want to be treated.

2.2 The balance between a certain level of automation and personalization allows you to effectively work with both current client segments and new ones.

2.3 Formulate your hypotheses for improving communication using data obtained from several reliable sources - this way you can protect yourself from falling into traps.

3. Measure satisfaction

3.1 A good approach is to constantly monitor how the client perceives the relationship with you.

3.2 The client’s perception of reality can be represented by a number of indicators and metrics, each of which has one or another significance as part of the larger task of improving account retention

3.3 Based on the specifics of your business, industry, your goals and pain points, identify key metrics that reflect your client’s satisfaction, constantly monitor, document, analyze and make decisions.

4. Optimize performance

4.1 Regular demonstration of your value to the customer in the language of metrics and indicators, numbers and facts allows you to build and develop healthy long-term partnerships

4.2 Focus on those metrics that are most important for a particular customer. Please don't create thousands of pages of reports for the sake of creating reports, don't overdo them and don't clutter them - keep them simple, clear, professional and effective.

Key points

1. Working with data competently increases the likelihood of making successful business decisions and strengthens customer relationships.

2. Use multiple reliable data sources: don't become hostage to one source.

3. Use analysis methods that are most suitable for the specifics of your business.

4. Based on your analysis, formulate hypotheses and run experiments.

5. Based on the results of experiments, make decisions about implementing the best solutions.

6. Please remember that this process (3,4,5) is cyclical and continuous.

Good luck!
Methodologist of Guidbase
Author
Guidbase
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