“15% off on a bill of Rs 1500, where at least Rs 250 is the billing per person. The discount is applicable on your next bill and this offer stands valid till midnight tonight. Please show your Driving License/ PAN Card/ Voter ID Card/ Birth Certificate/ Any visible Birth Mark to make the claim.”
“A purchase of Rs 150 gets you 1 point and 150 points accumulate to a discount Rs 1. Points will expire every 15 days.”
While being dramatized for effect, I am not off the mark by much in quoting the “customer loyalty” schemes of typical companies. For this, they would pester their customers (who are ready to strangle them anyway due to the buffoonery at the billing counter) to fill out a mile long form and the promise of a “loyalty card”. For the 1-2 cards that I have, the only perks I have experienced are 225 SMSs per week and a strategically placed telemarketing call at 3.15PM on a Saturday. What luck!
These companies have taken value based segmentation to a crazy level and have introduced an unbelievable amount of crassness into their equation with their customers. The structure of these programs is designed to drive away even the most fanatic and hardened brand loyalists. They are also an insult to one’s intelligence and self-esteem.
Now, what exactly is the problem? It is the stance of customer loyalty architects to first see proof of customer value before loosening their tight fists. My humble submission is that this is COMPLETELY WRONG! Waiting to see if the customer will purchase an enormous value and then rushing into a tight embrace is sure to make them hold their nose in disgust.
It has to be the other way around. Loyalty begins with showing some faith and making the customer feel valued and special. And herein lies the conundrum. Obviously, everybody is not special. What is the best way to accurately predict who will turn out to be a goose that will lay many golden eggs. Fortunately, predictive modeling and data mining techniques can be brought to bear to answer these vexing questions.
Customer Life Time Modeling techniques can leverage existing transactional, demographic and lifestyle information about customers and then predict the most profitable pathways to becoming Most Valuable Customers in the portfolio. They can also surface out unique nuances about micro-segments. These MVCs, which can then be used to bring out very customized and personalized experiences. Nothing gets a relationship going better than personalized attention. Data-driven customer relationship management and personalization enable companies to place well informed, strategic bets on emerging MVPs among customers and lock them in early into long lasting very profitable relationships.
Proactively placing customers into expected value groups will make sure that they get nurtured from a very early stage. All customer touch points, campaigns, discount offers, even a phone call or a mailer needs to be aligned to these value segments in order to be able to bring about a cohesive, well-defined positioning of the company in the customer’s mind. This also enables the observation and then eventual prediction of value migration.
The expected response to this would be that there would inevitably be some wrong bets as predictive modelling is not magic or being psychic. Sure, but on balance, almost always, being proactive is so much better. It can also be reasonably argued that this advance show of early love would actually stimulate interactions from those customers who initially may not have planned on staying on for very long. And thus begins a virtuous cycle that will swing higher and higher.
The ability to genuinely surprise customers with a little extra in this otherwise cynical, crowded market will be a game changer. Customer Life Time Value Analytics can be the secret sauce of a very appetizing dish.
The author, Karthikeyan Damodaran, is a Consulting Services Delivery Leader at BRIDGEi2i – A company on a mission to unleash the power of analytics and transform the lives of enterprises and individuals alike. We believe that the solutions to almost all intractable problems lie buried inside the data. BRIDGEi2i has the ability and experience to mine a wealth of unstructured and structured information to help businesses identify prospects, target them through the right channel, maximize cross-sell and up-sell opportunities and thereby enhance the lifetime value of customer relationships. To know more visit www.bridgei2i.com
The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position or viewpoint of BRIDGEi2i.