(1) Which of my previous customers will buy again if I mail them?
(2) How many catalogues do I need to send them to maximise profitability?
(3) Are there lapsed buyers in my file that can be reactivated at a lower cost than other forms of
Traditional circulation planning methods involve using database characteristics such as Recency, Frequency and Monetary. Now we are pleased to say that these models can be improved upon.
This model ranks your entire customer database according to their propensity to respond to mailings. This allows you to select the most profitable customers to mail. It will also determine the correct number of catalogues you should send them, eliminating waste and maximising profit.
As well as a tool to optimise house file mailings the model also provides other benefits:
It easily identifies the "VIP" customers who respond at extremely high levels and with high order values, yet tend to get treated just like anyone else. The process identifies problems with data hygiene - duplicates, incorrect addresses, incorrect application of mailing flags etc. The analysis does not take a long time to complete and can therefore be applied to every mailing to the buyer file, without disrupting mailing schedules. For most mailers the data extract is straightforward.
Once we have the data, we will analyse a recent campaign and prepare a presentation of the results for you. There is no charge for this. You can then decide whether it is worthwhile using the model for your next campaign.
In addition, we offer the following services:
· Develop predictive models to determine the best recruitment methods for your business
· Provide a thorough matchback service so that you can track where your orders are coming from
· Work with you to develop processes that optimise your data hygiene, eliminating unmailable records and duplicates
If you are interested in making your data work harder then click here.
Copyright ©2006 Ray Morris-Hill Associates
The LMH Database Model
Developed and marketed in partnership with Dean Lundell