Loyalty experts agree that program members will be more engaged after their first reward redemption. Low point value rewards, commonly referred to as micro-redemption, were introduced to get new members redeeming quickly. The growth of micro-redemption options has paved the way for new types of loyalty programs with historically low margins, such as CPG and media companies.

Traditionally, micro-redemption has been dominated by rewards with a low monetary and low perceived value such as digital downloads, coupons, gift cards and donations. In recent years, more progressive programs have flipped the paradigm on its head by offering play-to-win high-value rewards, better known as sweepstakes or raffles. The idea is simple: a program member exchanges their points for an entry into the contest. As the cost of the reward is spread across all entries, the program can aggressively price the reward. A few examples of this include My Coke Rewards, Kellogg’s Family Rewards, Huggies Rewards, Swagbucks and Dailybreak.

Loyalty trends: Achievement rewards
The prevalence of mobile engagement has led to a rise in achievement rewards, due to its...

This new reward format immediately raises an important question: are chance-to-win rewards effective in driving engagement and loyalty? From my perspective, the engagement is undeniable. Anyone who has run a program with sweepstakes entries (myself included) will tell you it’s one of the best ways to drive points usage and engage low-balance members. Determining if this will create loyalty is a much harder question to answer. A common concern is that members will be upset when they don’t win the contest, thereby decreasing their loyalty to the program.

Like most great questions, the answer can be found in the musings of some of my favorite behavioral economists. The research to answer this question lies within Prospect Theory’s value function 1 which incorporates the following behavioral principles:

  1. a person’s decisions are coded in gains and losses, with neutral equivalent to zero
  2. when coding decisions, the impact of losses are greater than gains
  3. the marginal value of both gains and losses decreases with their magnitude

Ran Kivetz took this theory to new heights in his study on the effects effort has on risky choice2, which examines people’s preference for sure-small rewards over large-uncertain rewards within the context of a loyalty program.

Kivetz argues that the effort requirements of a loyalty program raise reward expectations, shifting ‘status quo’ away from neutral/zero. He built on this theory to show that:

  1. the presence of effort makes it more likely the that someone will prefer sure-small rewards over large-uncertain rewards
  2. the preference for the sure-small reward is significantly weaker when the person is intrinsically motivated enough to complete the task without a reward
  3. the attractiveness of large-uncertain rewards is amplified when positioned as a free ‘gift’ or ‘bonus’ as opposed to a reward they must earn

This research leads me to believe that the most important success factor of play-to-win rewards is their pricing strategy. Play-to-win rewards appear to be most effective in a situation when the effort required to earn them is very low. They become even more desirable when the member is asked to perform an action they would have done without being offered a reward.

Program owners are constantly looking for new ways to drive acquisition and engagement within their program. While the concept of a ‘bonus reward’ upon registration has been widely tested, the risks of training your members to expect free rewards have outweighed the benefits. Perhaps the best use case for play-to-win rewards is to engage users shortly after registration with a ‘gift entry’.

The major caveat with all of this research is that the perceived effort and intrinsic motivation will differ greatly amongst your members. As such, there is a place for both small-sure and large-uncertain rewards. Just remember to price and position the rewards carefully and deliver them with appropriate context.

  1. Kahneman, Daniel and Amos Tversky (1979), “Prospect theory: An analysis of decision under risk,” Econometrica, 47 (March), 263–292.

  2. Kivetz, Ran (2003), “The Effects of Effort and Intrinsic Motivation on Risky Choice,” Marketing Science, 4-22 (Fall), 477–502.

Back to blog