CLV: A customer is for life – not just for Christmas

• 
  

This slogan is something that most dog lovers are familiar with.  While we faithfully care for our dogs, want them to love us and to stay around forever, we struggle to replicate that same sentiment through our relationship with customers.

The good news is that marketing executives do see this as a priority for their organisation, according to an IBM report.

Loyalty programmes

Regardless, haven’t we as consumers all been at the receiving end of situations where that sentiment failed to be deployed?

I recently received a letter with a brochure from a retailer whom I regularly buy from.  It offered me, a “VIP Customer” 15% off my next purchase.  Feeling all warm and loyal inside, I went online and placed an order.  The next morning, I open my newspaper and a brochure falls out – from that same retailer, offering any random, unqualified, non-VIP person a full 20% off!  Imagine how I felt, and what I said to the customer services agent who took my call.  On the positive side, he immediately acknowledged that I’d been given an unsatisfactory experience due to poor campaign planning and applied the additional 5% discount to my order.  And I do like their products so I’ll let them get away with it.  This time.

Some lessons to draw from this little story:

• Organisations often invest more in acquiring new customers than retaining existing ones;
• A campaign appealing to ‘loyal’ customers may be successful, but the trust can so easily be broken if the “not just for Christmas” guideline is ignored;
• Appropriate mitigating action can save the revenue.

In many industries, switching costs are very low.  Increasingly, consumer protection bodies and governments are forcing vendors to make it easier for consumers to switch, while also making the true costs more transparent – e.g. in case of utilities.

In the above example, I didn’t ‘defect’, because I like the retailer’s products and because they dealt appropriately with my complaint, but frankly, I don’t care much what the label is on my electricity or broadband.  ‘Churn’ is therefore a metric that receives a lot of attention.

Use your analytics to retain customers

It should be easier to retain customers than to win new business (unless the offering really is providing poor value, of course).  Organisations who have customer accounts or loyalty programmes possess so much information on their existing customers, with which to understand what it takes to please and retain them.  On new customers, by definition, you have little if any information, so the tactic of choice seems to be “let’s just throw an offer of 20% out in the market, and see who takes the bait!”

Let me share some examples of organisations who successfully use analytics to enhance customer retention.  A major telecommunications company has grasped the opportunity and deploys predictive analytics on their customer data to increase customer retention while reducing costs.  They identify the drivers of dissatisfaction and churn –typically a complex combination of factors – and analyse who in their customer database are currently affected by those negative drivers.  1% of their customers are 3-4 times more likely to contact the call centre and call out a technician, and twice as dissatisfied as the average customer.  The organisation now proactively contacts those customers most at risk of defecting and offer mitigating action, rather than wait until the defection has happened.

Similarly, a gas and electricity provider is analysing patterns in customer behaviour, such as whether a customer asks for a change to their payment plan and to what extent that indicates an intention to defect, or perhaps an insolvency problem.  Focusing on one group of existing customers, the company reduced the churn rate by 7% and also reduced the bad debt ratios.  They furthermore deploy predictive modelling to understand the impact of customer lifecycles on their energy consumption in order to provide more accurate forecasts, thus reducing a key cause of dissatisfaction.

Customer lifetime value (CLV)

Calculating email subscriber CLV

CLV is another significant insight derived through predictive analytics.  This measure is useful when you do invest in acquiring new customers; you would ideally like to recruit more customers that are likely to end up in your high value segments.  By identifying what characterises those of high CLV, and what tactics originally got them on board, you can deploy look-alike targeting campaigns.

In the above examples I have focused on the benefits of predicting churn in order to increase retention – however, some customers you may actually happily ‘hand over’ to your competitors.  The customer who is a net drain on your profitability over their lifetime because of the excessive costs of servicing them, or because they only ever buy your ‘loss leaders’ and never your higher margin offerings.  That is not to say that you would stop selling to them entirely, but you might want to stop investing in retaining them, or acquiring them in the first place.  The CLV measure therefore also helps you prioritise who to target with your tactics.

In summary; customers can and ought to be (perhaps with some exceptions!) “for life, not just for Christmas”.  In today’s world, where most organisations possess or can easily acquire big data as well as advanced analytics technologies, they can gain a dynamic understanding of the individual that feeds into every customer engagement decision.  Businesses can treat customers in a personalised and relevant manner, leading to a long and mutually beneficial relationship.