Working with, not against, the psychology of customer loyalty

Key takeaways

  • Today’s loyalty schemes have an unsustainable focus on rewards with a financial value.
  • Customer-brand relationships could thrive on less conventional rewards, such as ‘surprise and delight’ moments.
  • Behavioural science can guide businesses to what customers want – and data analytics could flag when they want it.

In a recent article, I examined how customer loyalty schemes might not actually be fostering much customer loyalty. By focusing primarily on points-for-dollars structures, loyalty schemes in Australia and elsewhere could be missing valuable opportunities to cultivate emotional engagements between brands and consumers.

While the ‘loyalty’ aspect of loyalty programs might be a misnomer, the capability exists for a new generation of customer engagement program, one that combines analytics with behavioural science to promote consistent and positive encounters that are mutually beneficial for both parties.

Using these techniques, a company – let’s use a health insurer, for example – could simultaneously grow brand advocacy and inspire customers to engage with health and wellness-themed content and programs, potentially lowering the cost to serve and claims in one fell swoop.

The science of customer behaviour

When a traditional loyalty scheme begins rewarding a customer for their patronage, the transaction sends a signal to the market and customer that certain actions have value. This creates explicit and implicit customer expectations around these engagements, training them to expect certain levels of reward for their behaviours.

This pattern becomes problematic in a market mostly focused on discounting (such as Australia’s). With customer behaviour trained primarily on value exchange, perceptions of loyalty schemes rise and fall depending on price, creating a race to the bottom that puts brands and suppliers under pressure to continually discount and cut costs.

Put more simply, with the perceived value of the rewards scheme lower than the economic cost of the scheme itself, a lose-lose scenario is created for both the brand and the customer.

Further complicating matters is the crowding-out effect¹, where a fixation on monetary rewards overshadows other – potentially more valuable – intrinsic motivations. This can trivialise engagements.

Unexpected customer rewards

How can loyalty schemes be turned from blunt, discount-focused instruments into sustainable operations aligning customer behaviour with brand engagements? By resetting the game pieces around unexpected rewards.

Unexpected customer rewards work harder than their traditional, expected rewards counterparts. They keep customer expectations fluid and create room for more moments that surprise and delight. Using data analytics, a next-generation loyalty program could deploy such unexpected rewards in a structured way, addressing both customer needs and organisational outcomes.

What do unexpected rewards look like in action? Let’s return to the health insurer, which also runs a health club aiming to deliver a premium service. The club has several masseurs on its payroll, with massages able to be booked in advance. While the masseurs are primarily occupied by these bookings, periods of downtime are inevitable.

Because the health club must still pay for the masseurs during this downtime, they could be redeployed onto the club floor, delivering ‘surprise and delight’ moments in the form of short on-the-spot massages to non-booking clients. Such a service isn’t part of the standard membership package, yet it can drive disproportionately positive behaviour at zero incremental cost.

Rules of engagement 1: The first 100 days

When incentivising new customer behaviours, organisations should be mindful of certain hurdles identified by behavioural science. One example is the problem of creating lasting engagements rather than an initial spike of activity followed by a sharp decline.

While the literature is inconsistent on how best to do this, there’s an awareness that the first few months are disproportionately important in shaping a customer’s emotional engagement with a product or brand, setting the guidelines for the rest of the relationship.

As a result, many companies have a First 100 Days program in place, frontloading the engagement with perks and benefits to shape perceptions. (The health club would do well to leverage digital technology to know when new members are on the premises, specifically targeting them with the on-the-spot massage initiative.)

Rules of engagement 2: The peak-end effect

Another behavioural phenomenon is the peak-end rule², where the most intense part of an engagement (positive or negative) and the end of an engagement becomes the enduring memory of the whole experience. Here, surprise and delight is also well suited – especially if it’s targeted to respond to the defining moment of a customer experience.

Imagine you’re the accident and claims division of the health insurance company. While the department’s day-to-day offering is mostly perceived as intangible, a moment of truth arrives whenever a customer has an accident or incident. The insurer should seek to over-deliver in these emotionally taxing situations, leveraging surprise and delight principles to optimise the engagement during the peak-end moment.

Following the customer’s reporting of an accident, such as a car fender bender, the insurer could offer services beyond the core insurance product, such as complimentary taxi vouchers or a hire car – no paperwork or questions asked.

By unexpectedly improving the perceived value of the core offering at just the right moment, the customer will associate the intense emotional experience of the accident with the unexpectedly gracious response of the insurer, folding it into the memory of that experience and improving their advocacy.

The role of data analytics

Advances in digital infrastructure have meant that data analytics can help to trigger these surprise and delight engagements, by combining drivers of customer behaviour with an increasingly granular understanding of their activity.

By dual-wielding data and psychology in this manner, you can establish a scaled test-and-learn environment that systematically nudges customers towards certain incentives or behaviours, such as brand advocacy on social media. These can then be further measured and evaluated, creating a learning loop of constant refinement.

Beware the echo chamber

Analytics and behavioural science might help unlock new levels of granularity, however organisations should be mindful of too much personalisation. This occurs when hyper-targeting goes too far, creating behavioural ‘echo chambers’³ that lock customers into certain patterns or behaviours – essentially recreating the price fixation behaviours of current loyalty schemes.

Instead, customers should be given room for serendipity, evolving their interests and engagements with brands over time.

Surprise and delight 2.0

The loyalty program of the future is one of smart, unexpected rewards. Powered by sophisticated analytics, it knows the next best thing to offer customers – and when – framing the brand conversation in a way that delivers maximum impact.

Featuring a large number of permutations catering to multiple customer segments, this new engagement program approaches true personalisation, moving beyond basket sizes and purchasing histories to incentivise key behaviours for mutually beneficial outcomes.

With thanks to Dr Johann Ponnampalam, Adjunct Associate Professor of Psychology at Deakin University and Founder of Decision Design Consultancy.



References

  1. Motivation Crowding Theory: A survey of empirical evidence, Journal of Economic Surveys, 2000. https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=203330
  2. When more pain is preferred to less: Adding a better end, Psychological Science, 1993. www.jstor.org/stable/40062570
  3. BX2016, How we talk about nudging: A conversation with Cass Sunstein, Harvard Kennedy School Center for Public Leadership