“Customer acquisition, retention and value are closely linked with customer proposition design, which is one reason why the use of insight in acquisition…” must extend into product management. TML examines why…

Acquiring new customers is an important task for many companies. There are three main situations where this is so. The first is when customers first move into a category, particularly when they are likely to stay with the company they first use for most of their purchases in that category. Student banking is perhaps the best example of this (though increasingly students switch bank when they leave university), but others include frequent business flying (although many customers move into and out of this category as their job determines, they tend to stick with the airline they are familiar with unless they change their job and or travel pattern).

The second is where customers move into and out of the company’s product category fairly often. A good example of this is baby products, where a mother moves into the category with each new baby. The third is where customers in the category switch frequently. In this case, the customer is acquiring a customer from a competitor. The customer is usually experienced in the category, and has a track record of usage and payment. This article focuses on the latter situation, which is typical in motor insurance, credit cards and possibly current accounts and simple savings accounts, telephony (fixed line, mobile and broadband Internet, subscription television and general insurance (mainly motor and property).

Typically, businesses in the third position develop a very professional approach to customer acquisition. This includes using advanced customer insight capabilities. The reason they need this is that without it, they may end up acquiring the wrong customers e.g. ones with poor credit or payment histories, low levels of usage or high propensities to switch. They want to avoid the situation in which acquisition costs will exceed subsequent profitability.

Of course, not all the data these companies need to decide which customers to acquire is available before the company starts the acquisition process for a particular customer. Credit history can of course be obtained from a credit-referencing agency. Usage normally has to be obtained during or after the acquisition process, although post-code based profiling can help here. So does the period the customer has been with their existing provider (although if the customer’s last switch was from the acquiring company, the company should know – if its database management is up to it)!

Resolve the issues

So, it is important for such companies to resolve the following issues:

• Are the right people being contacted?

This is the topic covered above. Note that learning never ends, and it is a critical role of the customer insight function or supplier to keep recalibrating models according to experience, in particular to identify whether the selection criteria supposed to lead to the acquisition of more profitable customers actually did. Work at LBM shows that advanced segmentation techniques using geodemographic, lifestyle and/or usage data always adds value and continues to do so as experience grows.

• Are they being contacted at the right time?

This may relate to time of day, season or in relation to any contractual situation with their existing supplier (e.g. towards the end of a contract period)? Work at LBM indicates that all these aspects of timing are important.

• What is the value of data captured?

This is why an advanced and stable customer insight approach is required. The value of acquiring a particular data item only becomes clear as the pattern of usage is established. If the approach (techniques, processes, people etc.) to customer insight changes, this can destabilise the interpretation process. Also, they key here is to identify those data items which most successfully discriminate between positive and negative outcomes at different stages of the acquisition process, in particular decision maker contacts, contracting and activation. These are indicated in the accompanying diagram.

• What proportion of data is captured?

It is one thing to have a data capture strategy, but in most of the industries that are the subject of this article, the data is captured by contact centre operators. They are of varying quality, and customers are of varying receptiveness, so all the required data is unlikely to be captured from all target customers.

• How effectively is the data used?

The deployment process is also partly in the contact centre. For example, a company may determine that if the data shows that a customer is likely to be unprofitable, the best offers should not be made to that customer. But the contact centre operator might not follow instructions. The analysis might have shown that certain kinds of customers should be contacted only at certain times of day, of the week, but if these instructions are ignored the outcome might be unwanted.

• Can the mix of data be optimised for better call centre performance?

It is not just the value of the customer that needs to be taken into account, but the efficiency of the contact centre making or receiving the calls. The two have a delicate interplay, because efficiency in the contact centre achieved without the use of customer insight is usually at the expense of customer value.

• Can the data being acquired to support the process be acquired more cost-effectively?

There are many different and overlapping sources of external data. These need to be tested for their quality and value.

• Has the company used insight to identify the improvements it can make by deploying data better at different stages of the sales cycle?

This includes understanding how prospects with high likelihood get to the point of a confirmed sale, testing different marketing communications programmes for the type of enquiry they attract, identifying how to improve the mechanism for data capture, identifying how to recycle lost sales opportunities. It also includes the development and use of key performance indicators to compare data captured for customers who were called back with the data captured from the original call.

• What incentives do staff have to capture more data and/or more valuable data?

Incentives do not have to be financial – indeed this can cause undue focus on data as opposed to selling, but there needs to be some reward for improving data quality. This might take the form of management praise and awards for the quality of conversations.

• How well is data captured in the contact centre used for central decision making?

Too often, the flow of data into the contact centre does not continue into central decision making e.g. for making decisions on products, propositions and future communication campaigns.

• Have the company’s propositions been designed to take into account the likely profile of acquisition prospects?

For example, if a high number of potentially high value prospects have low credit ratings, the product needs to be designed with an option that can be profitably offered to these people. In credit cards, this might be more restrictive credit limits or earlier repayment requirements, while in mobile telephony it might be an attractive pre-pay option. Or if analysis shows that customers will activate if given the right product and promotional incentives, have these incentives been designed and tested?

In markets like those which are the subject of this example, customer acquisition, retention and value are closely linked with customer proposition design, which is one reason why the use of insight in acquisition must extend beyond the direct/database marketing process into product management, as per the last point above. However, the other point that we would like readers to take out from this article is the extent to which use of insight must suffuse the whole acquisition process, and not just be used for the initial profiling and targeting.

By Professor Merlin Stone and Dak Liyanearachchi

About Professor Merlin Stone

Merlin is one of the UK’s most experienced consultants, lecturers and trainers in CRM, database marketing and customer service. He is the author of many academic and professional articles and thirty books on marketing and customer service. He is a Founder Fellow of the Institute of Direct Marketing and a Fellow of the Chartered Institute of Marketing. The Chartered Institute of Marketing listed him in 2003 as one of the world’s top 50 marketing thinkers, while NOP World nominated him in 2004 as one of 100 most influential individuals for their input and influence on the development and growth of e-commerce and the Internet in the UK over the last 10 years. He is a Director of Nowell Stone Ltd, an organisational development and consulting company specialising in database marketing, CRM, e-business and associated areas of customer service and IT. He has also pursued a full academic career, involving senior posts at various universities and has a first class honours degree and a doctorate in economics. He is now Visiting Professor at these universities: Brunel, De Montfort, Luton, Portsmouth, Southampton Solent and The West of England.

Merlin can be contacted by emailing him at: merlin@merlin-stone.com.

About Dak Liyanearachchi

Dak is Director, Consumer Division, LBM, one of the UK’s leading suppliers of customer management and direct marketing services. He was recently appointed to this post, in which he heads LBM’s new consumer data and consulting division. The new division brings together LBM’s Data and Contact divisions to execute direct marketing strategies for LBM’s clients. By adding external data to the existing offering and then analysing it, LBM can identify what clients should be saying, and to whom, and through its Contact division, it ensures the message gets to them through the right channels. Before taking up this post, he was Global Business Development Director at Dunn Humby and before that Operations Director at Catalina Marketing. His consultancy work includes experience with Tesco, Asda, Somerfield, Hewlett Packard, Cadbury Schweppes and Coca Cola. He has a BSc (Hons) Business Information Systems degree from the University of Central England

Dak can be contacted by email him at: DakL@LBM.co.uk, or further information can be obtained by visiting his website (http://www.LBM.co.uk)