Comments on: Customer Retention Metrics http://www.tangyslice.com/2008/11/11/customer-retention-metrics/ sharp. social. accountable. Wed, 16 Dec 2009 16:11:30 +0000 http://wordpress.org/?v=2.9.2 hourly 1 By: Marketing Analytics » Lifetime Value http://www.tangyslice.com/2008/11/11/customer-retention-metrics/comment-page-1/#comment-1680 Marketing Analytics » Lifetime Value Sun, 30 Nov 2008 15:59:24 +0000 http://www.tangyslice.com/?p=73#comment-1680 [...] had a recent post about customer retention metrics.  To his list, I would add lifetime value.  There are many ways [...] [...] had a recent post about customer retention metrics.  To his list, I would add lifetime value.  There are many ways [...]

]]> By: Lynne http://www.tangyslice.com/2008/11/11/customer-retention-metrics/comment-page-1/#comment-1622 Lynne Tue, 25 Nov 2008 03:16:32 +0000 http://www.tangyslice.com/?p=73#comment-1622 Like Limeduck, I was going to suggest a concentration ratio or some variant on the Pareto principle. In addition, I would suggest lifetime value (LTV) as a customer retention metric. For a cellular phone company I estimated the lifetime value of its customers by calculating the discounted value of their expected future revenue with the company. This addresses some of the issues raised by Limeduck and enables you to segment customers based on future value as opposed to their value in the past. Like Limeduck, I was going to suggest a concentration ratio or some variant on the Pareto principle. In addition, I would suggest lifetime value (LTV) as a customer retention metric. For a cellular phone company I estimated the lifetime value of its customers by calculating the discounted value of their expected future revenue with the company. This addresses some of the issues raised by Limeduck and enables you to segment customers based on future value as opposed to their value in the past.

]]> By: limeduck http://www.tangyslice.com/2008/11/11/customer-retention-metrics/comment-page-1/#comment-1521 limeduck Fri, 21 Nov 2008 18:30:40 +0000 http://www.tangyslice.com/?p=73#comment-1521 I think there's something like concentration ratio that's interesting. What % of revenue do you get from the top x% or top N customers? If that's a high number, it might be worth tracking your retention metrics separately for top customers and the rest. But what's lacking in most of your metrics above any also in my suggestion here is predictive value for retention. What figures can you derive that can tell you which customers are more likely to stay or leave *before* they do, and can you intervene positively on the latter cases? Net promoter is one, but are there others that are more actionable in a given business? I think there’s something like concentration ratio that’s interesting. What % of revenue do you get from the top x% or top N customers? If that’s a high number, it might be worth tracking your retention metrics separately for top customers and the rest.

But what’s lacking in most of your metrics above any also in my suggestion here is predictive value for retention. What figures can you derive that can tell you which customers are more likely to stay or leave *before* they do, and can you intervene positively on the latter cases? Net promoter is one, but are there others that are more actionable in a given business?

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