Customer loyalty is a much more bankable asset than recruiting new. It is a measure of trust and a mark of quality in your products or services and, in fact, a stronger marketing tool for you. When you move with a large number of loyal customers through times and seasons, prospects will want to know why and, in the process, you get conversions.
It is, therefore, important to review your customer retention rates through modern analytics for improvement while using AI to grow business. Here is how to properly evaluate customer retention rates and improve them using key performance indicators.
1. Customer Retention Rate
Customer retention rate is the basic indicator and most important for tracking loyalty. Simply put, it is the percentage of customers that remain loyal to the company over a given period. The determinant factor in calculating CRR is your product lifetime and the period under review.
If you deal with recurring products that require periodic replacement or resupply, you must monitor customer’s activities continuously for retention. In this case, calculating CRR is easy as you divide the number of customers at close of period less new customers by total number at the start of the same period.
Digital marketers can use big data platforms or CRMs to leverage customer data, thus collected for better evaluations. A simple but concise set of instructions on the system can pick up key performance indicators driving customer loyalty.
Digital marketers should go beyond CRR calculations and evaluate these in terms of revenue generation over the time they stay loyal.
2. Use of Decile Analysis
An important KPI is a revenue generated by a long-time customer identified as customer lifetime value. Decile analysis is simply a grouping of customers in segments to identify the top performers in revenue generation and hence profits.
Once, as a digital marketer, you have identified this category, it becomes easier to lay strategy for long-term retention. On the face of it, the decile percentage might be low rarely above 10% but accounting for over 60% of total sales and accruing profit.
To get customer lifetime value of individual customers across the decile segments, you work out the calculation as below,
CLV = average order value x average number of repeat purchases x average CRR
This method focuses mainly on revenues generated and one may throw in another term – the dollar retention rate (DRR). This looks at the lowest purchase value they make say annually, giving you the figure in dollars that keeps renewing every year.
3. RFM matrix and repeat purchase
Repeat purchase rate (RPR) measures the frequency of customer returns to your store for fresh orders. Using this background, you can create an RFM matrix into which you enter RPR data for analysis.
RFM here stands for Recency being the number of purchases by a customer in recent times, Frequency of those purchases, and Monetary value meaning the customer’s spending threshold.
Using this matrix, a digital marketer can segment customers according to buying habits and devise ways to keep them on board with appropriate incentives and discounts.
This matrix also helps in evaluating the share of wallet, which is the percentage of the customer’s spending in your market niche.
If a customer buys a product that is replaced every month and returns only three times a year, it could mean they are buying from competition for the other nine months. Having this knowledge helps you fence off your customers from venturing to the competition for the same products.
4. Using the Net Promoter Score
The net promoter score metric measures customer satisfaction and how well your products or services are ranked. Digital marketers use questionnaires or promotional surveys to collect responses from their customers on whether they (customers) could recommend the company to others.
A favourable NPS score could mean the business benefits from indirect marketing through satisfied customer recommendations. The NPS score will group your customers into three categories that comprise detractors – those ranking you at 1-6, passives scoring 7-8, and promoters who will tick you off at 9-8 on a scale of 1-10.
You will then aggregate the results to get percentages and one above 50 is an exceptional indicator of the performance of your products as the average is 45 in e-commerce. NPS is a good tool for marketers as it is simple, consistent in format, has a comparable metric, and carries a great impact on brand acceptance.
5. Churn Rate and Defections
Previously loyal customers who appear once and disappear for long times or altogether cause great concern to digital marketers striving to retain loyalty online.
A tool that can help identify potential defectors before they move will assist marketers to intervene in time to retain such valued customers. If a company has in place a big data platform, a Recency Sales (RS) matrix can be incorporated to help compile helpful data.
The RS matrix calculates the time taken since last purchase (Recency), the total number of periods absent, and total sales over the absent period since the first purchase divided by the total number of times a purchase was made.
If the recency number is higher than the first statistic, there is a high potential for defection. Another simple way to calculate churn rate is to take the number of customers at the start of the period fewer customers at the end of the period and divide by customers at the beginning of the period multiplied by 100.
Regular customers form the backbone of your near stable and assured revenues. It, therefore, makes great business sense to put as much effort in retaining existing customers as it does attract new, if not more. Digital marketers must develop a long-term strategy for customer retention and overall growth.