The Retention Rate

The most important number in any lifetime value table is the retention rate. This is the percentage of newly acquired customers in each segment who will still be buying from your company 1 year later. Before database marketing, few companies knew what this number was or what to do about it. I worked with an insurance company whose retention rate in the first year was only 54 percent. During this year, the company made absolutely no effort to make contact with its customers or to build a relationship with them. Lifetime value computation showed that an increase of 5 percent in this first-year retention rate would increase profits by $14 million (see Table 1-1).

Table 1-1 : Effect of 5 Percent Increase in the Retention Rate

	New customer	Second year	Second year
Retention rate		54%	59%
Customers	130,000	70,200	76,700
Average revenue	$2,900	$2,900	$2,900
Total revenue	$377,000,000	$203,580,000	$222,430,000
Acquisition/retention	$192	$ —	$36
Commission	$959	$769	$769
Total	$1,151	$769	$805
Total cost	$149,630,000	$99,970,000	$104,650,000
Net revenue per customer	$1,749	$1,476	$1,536
Net revenue in total	$227,370,000	$103,610,000	$117,780,000

The cost of getting this additional 5 percent increase was estimated at $36 per customer, or a total of $3 million, for customer communications. The beauty of using a database to do lifetime value analysis is that you focus on things that you can change by marketing strategy and that you can prove the value of each strategy in finite dollar terms.

Using database marketing, the company would not have to commit the $3 million in the hope of getting this increased return. It could use the database to set up test and control groups to see if the communications would produce the desired results. It could select 5000 customers to receive the communications (at a cost of $180,000) to see if their retention rate could be increased by 5 percent. If the strategy worked, then the next year the company could apply the successful methods to all new acquisitions, spend the whole $3 million, and pocket the $14 million. (Table 1-1 and all the other tables in this book can be downloaded free from www.dbmarketing.com.)