In these tough economic times, companies are placing even greater emphasis on balancing the seemingly competing aims of increasing revenue while reducing overall expenditure. One of the key strategies, put simply, is to encourage existing customers to spend more. The challenge, though, is just how to do this? How can marketers ensure repeat business, and how can they extract a bigger share of wallet?
Many organisations utilise a loyalty scheme in an attempt to better understand and connect with their customers; both Waitrose and Superdrug – amongst others – have launched programmes this year. The big question for organisations today is: how successful can loyalty schemes be at really driving retention and delivering cross-sell/up-sell opportunities, and can they truly offer significant ROI for marketers?
What’s clear is that loyalty schemes can certainly be expensive, both operationally and promotionally, driving significant value from the bottom line, especially in those simply offering straight-line rebates. Even Tesco, one of the first exponents of a loyalty card in the UK, recently announced that it is halving the value of points offered to customers on its successful Clubcard scheme, whilst British Airways is rolling its Executive Club programme in with IAG sibling Iberia’s scheme, in an effort to reduce operational cost.
In order to secure retention and provoke cross-sell purchasing, organisations are looking to leverage greater insight and understanding of their customers’ buying behaviour in order to better identify patterns, define more accurate segments and stimulate predictable responses. As competition in the marketplace becomes ever fiercer, marketers are devoting more attention away from the front-end activities (like creative execution), and are instead placing it on back-end activities such as data mining, complex statistical analysis and behavioural modelling.
Of course, there’s no secret in this; the importance of accurate targeting should come as no surprise to any marketer. But what is clear from research is that even today, with all these tools, marketers aren’t as accurate as they may think. A recent survey conducted by YouGov in conjunction with Featurespace revealed that even for marketing that purports to be targeted, more than half of consumers (54%) believe it is anything but: still being presented to them at the wrong time, often with irrelevant offers or promotions.
Perhaps most worryingly for marketers, the survey also identified that even when marketing is accurate, appropriate and timely, only 42% of consumers receiving such an offer would even consider themselves ‘more likely’ to buy a product. In a world where even perfectly targeted offers might not work, the game needs to change and marketers need to find a way of gathering deeper insight, a greater customer understanding and even finer accuracy of behaviour prediction.
So what does this mean for loyalty schemes? Without top quality analytics of the data collected, many schemes are destined to always offer a poor return on investment. The answer is not to try to create more accurate segments – it is to do away with segmentation altogether. Marketers need to offer customers promotions and rewards based not on group activity, but on their specific individual behaviours, using real-time data.
Fortunately, there are already solutions available that enable marketing analysts to deploy the kind of highly complex, extremely granular and exceptionally accurate predictive behavioural modelling they need for their campaigns – all without the need for a PhD in Statistics.
These simple-to-use, configurable applications allow marketers to utilise powerful mathematics and statistical modelling that accurately get to know their customers – ‘learning’ what makes an individual tick from the entire history of that customer’s relationship, refining its own accuracy over time, and using real-time data from live feeds. Marketers can now get faster, more accurate predictive insight into, for example, customers with the highest probability of churning (and when), those with a high propensity to respond to a specific offer (and at what level and when), and individuals who are most likely to deliver the highest lifetime value, even at early stages in the relationship.
The future success of loyalty schemes will not be dependent on the level of points they offer, or the specific details of the deals they provide. It will depend on whether or not such programmes can do away with segmentations and start to treat customers truly as individuals. Marketers still need to be able to market to their customers’ needs with deals that are timely, relevant and appropriate, but it is only when they are individualised and accurate enough that they will overcome the 42% barrier.
