The Role of Data in Customer Retention    

4 min read

Many organizations put all their effort into acquiring new customers rather than working to retain them. But a business’s success lies in retaining customers, and analytics is playing a crucial role in improving customer retention.   

Retaining customers can be profitable from 25% to 95%  

With this article, we will see how companies are winning by leveraging existing data to improve the lifetime value of customers.   

Why is there a need to retain customers?   

The goal of customer retention is not just to keep customers for a long time but also to build valuable relationships that will last for a longer period. Here are some of the reasons why customer retention should be a priority for your business:   

  • The existing customers generate more revenue than the new customers.   
  • Retaining customers requires fewer resources as compared to acquiring new customers.    
  • With your loyal customers, you can bring in new clients. It also fosters views on social media, reviews, and also feedback that will help in increasing the accountability of your brand.   

Why are analytics so important?   

With the latest tools and technology that we have, it has become easier to gather users’ details and analyze buying patterns. For any business now, positioning their business has become much more feasible. Let us learn what you can achieve through analytics:   

1. You can understand your customer’s behavior   

The tools can capture the client’s information from the CRM platform and know about their shopping patterns to improve the shopping experience. Information about customer behavior and customer profiling, when applied to your marketing campaigns, can give you excellent results.   

2. You can assess customer engagement   

With analytics, you can figure out how much a user is engaging with your content. You can see where he is spending most of the time on your website and what time he is likely to leave your website. You can see when the customer is most engaged in the whole buying cycle.   

3. Work with predictive models   

You can build a predictive model using the analytics on how the user’s behavior, buying pattern, product usage, and Customer engagement rate. If you find any change in the above parameters, you can rectify it with the appropriate resources like product recommendations, rewards, or marketing campaigns.   

It can be difficult for you to manage these many variables but with the right data analyst, things will become easier for you.   

4. Personalized content   

If you are trying to sell a single campaign to everyone, it will not work positively for your company. With the help of analytics, you can determine what your product demand is, the high-paying region, and other factors that are different for different sets of audiences.   

Customers are 80% more likely to do fixed deals with businesses having a personalized approach towards them.   

5. You can evaluate your marketing campaigns better   

With the help of analytics, you can define your ROI better and easily evaluate your campaigns in Realtime. You can see how the campaigns are taken by the audience, and if you see the campaigns are not working as you wish, you can edit and make changes to improve the performance.   

When you know what your audience requires, you have a better opportunity to design your campaigns and grab the audience’s attention.   

What are the types of customer retention analytics?   

1. Perspective analysis   

It helps in determining a specific type of question or how to improve decision-making. In the case of customer retention, the perspective analysis will include the best offer analysis.   

2. Predictive analysis   

This is the most common type of analysis used by companies. This forecasts what can happen in the future, like the best offers, churn rates, or renewal risk analysis.   

3. Descriptive analysis   

It can take time as compared to other customer retention analytics. The descriptive analysis gives you a description of the historic events that have happened with the campaign or the product. It is very useful in the market analysis as you can determine the difference in patterns.   

You can see how the trends have changed and how you can improve them further.   

4. Diagnostic analysis   

This type of analysis is suggested when you want to diagnose the cause of something. like you want to analyze the churn rate or the reason why your campaign didn’t go well. For instance, your campaign couldn’t work properly because your audience is not interactive when you post your content.   

How can you improve customer retention with data analytics?   

1. Develop a data roadmap for reducing the churn    

As implemented by Brain and Co, 30% of the executives do not know how to implement the data they have. For deploying data as your beneficiary factor, you must know how to make the most of it. To be successful, companies need to know how to make use of the data they have. Secondly, they need to know the changes required as a result of the data.   

For developing a roadmap, these are some simple steps that you need to take:   

  • Ensure the KPIs you have determined are automated, scalable, and repeatable.   
  • Analyze your business with the stakeholders and determine the top three problems you want to solve with the help of data.   
  • If things are not going as planned, check if the problem lies in the data or how it is being used.   
  • To remain on the determined track, assess your process every three months.   
2. Focus on your high-quality leads for retaining them   

You can easily retain your new customers if they are like your older ones. If you have data about your older customers, it becomes easier to determine what works for your new audience.   

This can only be possible if you have data regarding what worked for your customers before and do you have your target audience.  


3. Use text analytics to get better analytics   

To get deep analysis, make sure you analyze your free-text responses and open-ended surveys. You can use text analysis solutions that use sentiment analysis to determine the pain points of the users.   

You can analyze your free-text responses and open-ended survey questions. Make sure the data you are getting; you are making complete use of it to understand your user.   

4. Segment your customers to find the right kind of audience.   

You can use analytics to determine different segments of people that engage with your product or service. Analyze insights of every group and see what is working for each group separately. You can adopt different communication and business strategies with each group.   

You can analyze your customer’s demographics, lifestyle, products purchased, and pattern of purchasing. With these analytics, you can also determine the customer value that is critical for the success of your business.   

You can see the usability and time sensitivity of your codes. With the help of analytics, you can see how many of your codes are redeemed in the morning, afternoon, or night. This will help you position your marketing strategy better.   

Additional tips   

  • Have multiple data points to gather the accurate information   
  • Add social proofs wherever you can   
  • Always turn your act   
Yashika from Acadle

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