For most companies, the cost of acquiring a new customer is far more than the cost of retaining an existing customer—often 5-10 times more expensive. Moreover, 61% of small business owners have reported that more than half of their annual revenue comes from repeat buyers.
Those impressive numbers confirm the 80/20 rule to be true (20% of customers bring 80% of the business); and, thanks to the substantial amount of customer data businesses now have available, many businesses are shifting their primary focus to these customers.
If a business is to retain current customers, then its marketers must truly understand repeat customers' needs to improve their overall experience with the brand and gain their long-term loyalty.
For most marketers, it is no longer a challenge to collect customer data: Analytical technologies have given us the tools to understand a customer's actions at every point of interaction with a brand. But many marketers are still struggling to transform that analytical data into relevant information that can help improve customer loyalty.
Fortunately, there are steps marketers can take to harness data and keep churn rates at a minimum.
Companies have been using data science as a secret weapon to generate quickly actionable information that improves customer retention. If you're interested in significantly decreasing your customer churn rate, here's how to use the power of data science to define a process that will help your brand keep the customers you've already worked so hard to obtain.
Step 1: To identify churners, define your business model
Take the first step (it's free).
You may also like:
- Five Rules for Growing Customer Loyalty Even as Coronavirus Disrupts Supply Chains
- Transparency and Trust: The Key Links Between Data Regulation and Customer Experience
- Top 5 Critical Components of Great Customer Experience
- Five Reasons Companies Ditch Big-Name CRMs (And Go With Startups' Instead)
- How Are Customers Reacting to Your Loyalty Program? Four Issues to Avoid