Value management: Predicting the customer’s futureby
How can you predict the potential value a customer has and use that knowledge to improve marketing efficiency and the customer experience? Nick Evans looks into the future of value management.
Many people would give their right arm to posses the ability to see into the future, especially as the world economy is in such a precarious position. Wishful thinking perhaps, but what might surprise many is that predicting customer value can in fact be an obtainable and reliable working practice - without the need for supernatural divination.
If a brand is able to look at each customer in turn and predict the potential value that customer could deliver over the course of their shared relationship, it can apply this knowledge and vastly improve the efficiency of its marketing and communications activity, as well as vastly improving the customer's experience of the brand. Everything from customer acquisition to retention strategies can be refined by using the proposed value of each customer as a gauge for investment in the relationship.
Value management starts with the development of a dynamic model which combines relevant and available factors such as risk, cost, revenue and attrition, in order to derive a perceived 'value' for each individual consumer. When a brand first embarks on developing its value model, these factors may be crude but what is most important is that they are all explicitly recognised as components in the value calculation. As the value is deployed as a management tool, is better understood and more data is collected on customers, the model can be further refined and complexity added.
The bigger picture
Many brands have attempted to predict individual components of value, like response, cross sales and attrition. Value management is crucially different because it considers the interaction of all these elements, which is much more effective than viewing them in isolation. In practice, this process forces organisations to take a longer term view, perhaps translated as fewer customers who together offer greater value in the long term.
This prediction of customer value can be used to prioritise investment in each individual customer - an even more relevant course of action in the immediate economic climate. Many organisations are still investing heavily in customer acquisition but are now forced to conduct this activity at an even greater loss than ever before, most often because of the need to reduce prices and increase other incentives to get new customers to commit. Whilst this may help to get new customers through the door, it takes no bearing on whether instigating a relationship with them is ever likely to be profitable.
Instead, by taking a view on each customer's predicted value, the brand can refine its offer to each individual or even choose not to solicit certain groups if the value they offer is not a worthwhile prize. Understanding value at an individual level can help the brand to know how much of an incentive to offer.
However, this specific opportunity also presents a problem in that consumers, in general - and especially those bought in on price or incentives - are naturally promiscuous. The hard work really starts with the need to build a relationship with them to maintain their loyalty and, crucially, extract their predicted value.
Thankfully, our appreciation of value can then be applied with a long-term view to inform customer management practices (to reduce attrition) once customers are on board. Investment can be prioritised with particular customers, influencing everything from offers and incentives to directing the most appropriate and cost effective service channels, and even identifying which customers to elevate to premium status.
The right interactions
But it's vital that brands engaging in value management also understand that value cannot be guaranteed, and can be destroyed just as easily as it can be released. Successful release of value comes from designing appropriate interactions to unlock the customer's potential - getting this wrong can have serious consequences.
A high value customer who has the potential to buy more but also has low servicing needs may find themselves excessively communicated to because of these attributes, thus damaging the relationship if communication is not managed effectively - i.e. lots of 'push' marketing leading to the destruction of brand value and ultimately attrition. For this particular type of customer, a more refined approach to marketing - and one which focuses on inbound opportunities as a sales forum - can play a greater role.
What's also important to consider is that the value of two individuals may be identical but what constitutes this value may be very different. For example, one customer may have the potential to generate significant income but will be service heavy and, therefore, present a greater cost to the business. Another might harbour less in terms of revenue but present a lesser risk. It is this individual level knowledge that is fundamental in defining the most appropriate interventions to release value on a case by case basis.
Digital marketing which embodyies the principles of traditional direct marketing with the benefits of an understanding of customer data fit perfectly with a consideration of customer value. The entire focus here is on treating each customer as an individual and interacting with them through a renewed focus on timing and relevance. Therefore, by considering a customer's potential value built up from stored offline insight and instantly generated online behaviour, real-time interactions can be generated with the purpose of unlocking and building on this value on a totally individual level.
Underlining all of this is the need to set clear objectives and to test and evaluate what does and doesn't work. The principles behind direct marketing (test, test and test again!) must be applied. In doing so, everything from the value model to the way different segments and individuals are managed can be subsequently refined and improved on.
Tough times or not, using analytics and modelling to derive a value for customers can arm brands with another piece of evidence to help inform and enhance the way they interact with them. And because this value is a prediction, a true understanding of its latent nature can help brands positively influence value throughout their relationship with a customer, applying positive interactions to improve efficiency and profitability in equal measure.
Nick Evans is a consultant at Jaywing DMG
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This is a very beautiful expose' in as much as a agree to all the processes, frame work and the holistic view about the subject, my reservation is how do we determine the value to ascribe to the factors that make the value management of customers when most of these factors are not directily proportional, for example the time spent on maintaining relationship with customers does not determine how much the customer will spend but rather the service offer.