Hyken’s idea is for companies and their employees to make an extra effort over the next four weeks to create loyal customers. “This isn’t about being good. It is about being great. Creating loyalty is about a continuous effort that creates customer confidence,” he writes.
If you have ever come into contact with the world of customer service, you will know that perpetual promotion of positivity among customer-facing staff is the default setting. From small daily rewards for hitting targets to larger bonuses for exceeding customer expectations, call centre staff need all the incentives, hugs and marketing input they can get.
So is there anything the data industry should be doing for ICLM? One idea might be to take a good, hard look at how customer loyalty is measured and modelled. During last week’s Financial Services Customer Data Summit, the concept of customer lifetime value as a robust model was questioned by Graham Flower, head of customer data at HSBC.
His argument is that the duration of the relationship being used is too long, with too many variables, to be a reliable indicator of just how much each customer will contribute. Taking a shorter perspective will be more accurate and also more closely matches the near-term goals of the organisation.
This has an affinity with what Hyken says about customer loyalty. He says: “People think customer loyalty is about a lifetime. It isn’t. Customer loyalty is about the next time – every time.” For customer services representatives, that is a good reminder not to be complacent about the ties a caller might have with their company.
For data practitioners, it also opens an interesting window – what data needs to be captured about the customer that is truly indicative of their loyalty? A lot of moves are currently afoot in sectors where customers are highly mobile and have extensive choice to move beyond the behavioural and transactional data conventionally used in loyalty modelling into the attitudinal dimensions.
Loyalty is after all a mindset as much as a behaviour. So this month could fruitfully be spent thinking about loyalty models and data sets to support what colleagues in customer services are trying to achieve.
Whether that is the best way to spend April is another issue. But I have my own suggestion of a special calendar event for the data industry. From now on, let’s make every 29th February Data Suppression Day. Since one in four pieces of data is typically inaccurate or out-of-date, choosing this leap year-only day seems appropriate for getting extra attention for this often neglected issue. See you for the celebrations in 2012!