No matter how effectively a company retains its customers, every organisation must expect a level of natural attrition as customers move on or grow out of particular products or services. The ongoing efforts of companies trying to acquire new customers are saturating business and residential consumers with messages, offers and incentives, making it more difficult to cut through and reach a target audience with a relevant message at the right time.
As the costs of effective advertising and direct marketing are substantial, marketing managers are under pressure to improve response rates. Acquisition campaigns must not only return high response rates, but high conversion rates as well – particularly for customers who will be profitable long term. In this environment it is essential that marketers effectively target smaller groups of potential customers with relevant and timely messages.
An acquisition model can help with this by targeting a desirable population who are more likely to convert and be valuable long-term. Through modelling, Datamine can identify prospects who are most likely to respond to or accept an offer and become valuable customers. Such a predictive model ranks prospects based on their similarity to existing valuable customers, respondents, or target segments.
Typically, an acquisition model will at least double the response rate achieved by a random mailing.
How does it work?
Calculating customer profitability, or customer value as a proxy for profitability, is usually the first step in an effective acquisition programme. Using a variety of product, transactional and behavioural information, Datamine can calculate each customers’ profitability (see specific solution for profitability and value analysis) and build a profile for the most profitable customers. By knowing who the best customers are, their demographic profile and transactional characteristics, you can gain insights into the types of people you want to acquire.
Another base modelling group that can be used are the responders to past campaigns, which are analysed in order to maximise positive response for future campaigns. Note that if going down this route, it is best to use past campaigns for the same product. Alternatively, a further modelling group can be any 'new customers', but be careful of any bias.
The customer profiles created during this process can also be used by a marketing team and their advertising and direct marketing agencies to develop strategies and communications that will really hit home.