opinion
Many people would give their right arm to posses the ability to see into the future, especially with the world economy in such a precarious position With no end to the current recession in sight, being able to predict what's going to happen in the weeks, months and years to come would be a welcome and valued skill.
Wishful thinking perhaps, but that's not to say that the idea of predicting the future isn't a relevant one; especially when applied by organisations to individual customers. Specifically, 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 to improve vastly the efficiency of its marketing and communications activity, as well as the customer's experience of the brand. Everything from customer acquisition to retention strategies can be refined, by using the predicted value of each customer as a gauge for investment in the relationship.
What might surprise many is that predicting customer value isn't reliant on a crystal ball and extraordinary senses, and that an appreciation of value can in fact be an obtainable and reliable working practice.
Value management starts with the development of a dynamic model, which combines relevant and available factors like 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 recognised explicitly as components in the value calculation. However, as the value is deployed as a management tool, becomes better understood and more data are collected on customers, the model can be further refined, and complexity added.
Many brands have attempted to predict individual components of value, such as response, cross sales and attrition; value management is crucially different because it considers the interaction of all these elements - a process that is much more effective than viewing them in isolation. In practice, this approach 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 brought 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.
The role of customer value in defusing the tensions between the heavy incentivisation seen in acquisition programmes against subsequent high attrition rates can be more fully understood by looking at an example like the general insurance market.
The general insurance sector appears to be one that, so far, has not been significantly hit by the effects of the recession. However, the commoditisation of insurance products and the subsequent influence of online aggregators have meant price has become a primary acquisition tool for many brands. Insurers are prepared to offer significant incentives in the form of discounts and cash-back offers as a means of attracting new policies. Of course, discounting heavily at the start of the relationship can be a foolhardy approach. But those insurers making decisions on opening offers based on a customer value model will be much better placed to get the opening incentives right, without giving away any chance of generating a future profit with the customer before they've even passed the acquisition stage. A customer value model uses full knowledge of propensity to renew, likelihood of claims and potential for cross sales over the lifetime of the relationship with each individual customer.
Extracting predicted value is then very much about customer retention, starting from the moment the first product is sold. As such, successful 'on boarding' programmes cannot simply be based on getting customers through the door; they must seek to establish the brand's service credentials from day one, building a rapport with customers and simultaneously capturing data that can be used as the basis of informed dialogue and successful cross-selling throughout the relationship.
Once the customer is on board an appreciation of value can then be applied with a long-term view, to inform customer management practices as a means of reducing attrition. Investment can be prioritised with particular customers, influencing everything from new offers and incentives to directing the most appropriate (and cost effective) service channels, and even identifying which customers to elevate to premium status. These interactions and dialogues need to be thought through with a clear notion of the value at stake; in practical terms, two separate but potentially more costly conversations may be more likely to deliver value over a single heavily sales influenced call.
However, it's vital that brands engaging in value management 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; but getting this wrong can have serious consequences in damaging this potential. A high value customer (with the potential to buy more) with low servicing needs may find themselves excessively communicated to because of these attributes; 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 that 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. 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.
Thankfully, the direction of digital marketing, embodying the principles of traditional direct marketing with the benefits of an understanding of customer data, fits perfectly with a consideration of customer value. For example, the entire focus of the concept of 'synaptic marketing' is on treating each customer as an individual, and interacting with them with a renewed focus on timing and relevance. Here, what is known about the customer in the offline world (perhaps through transactional and demographic information and channel preferences) is collated with instantly generated behavioural data from online sources or delivered through real time conversations in call centre. Adding customer value to this mix can ensure the resulting real time interactions with the customer are generated with the purpose of unlocking and building on this value, on a totally individual level.
In turn, this process can work to inform the value model. This prediction is only as accurate as the available data on each customer, so pulling additional data into the model from various sources on and offline, whilst presenting a challenge, also presents a massive opportunity in improving the assessment of each individual's value.
Underlining all of this is the need to set clear objectives, and to test and evaluate what works and what doesn't. 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 subsequently can be refined and improved.
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. All without a deck of tarot cards in sight.
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