Someone in Singapore sent us a copy of a promotional letter she had received:

Tantalising cashback offers

That is a lot of hassle to get (maximum) $30 cashback.

  1. You need to make a minimum of 8 qualifying contactless transactions (and it is not mentioned which transactions will be qualified)
  2. You need to be one of the first 1500 eligible cardholders to do so (again it did not tell what constitutes an eligible cardholder).

It is already very generous from the bank’s part, you might say, as the maximum budget for this campaign is $30*1500 = $45,000.

let’s do some maths

Well, a different way to look at it is – you will get on average less than $30/8 = $3.75 per transaction, if you meet the criteria.

And each transaction should be on average $3.75/15% = $21 to maximise the cash back.

And if you use your credit card mostly for coffee at say Starbucks, you spend on average $6 per order. You will need $30/0.15/$6= 34 cups of coffee. For each cup you get $6*0.15 = $0.9 discount.

And you have to be the first 1500 to buy at least 8 cups of coffee. Whether this will be incentivising enough really depends on the users’ belief: how likely will I be one of the 1500?

However, if you are buying coffee every morning anyway, it will just become a ‘why not’ decision – that is easy to make.

Common traits of incentive schemes that work

When I was running Easy Taxi in Asia, we tried hundreds of different permutations of incentive schemes, for both drivers and passengers. Each incentive scheme would carry its own objective or combination of objectives (e.g. to drive more adoption, to increase dollar amount per transaction, to attract news users.)

The ones that tend to work well have the following commonalities:

  1. Easy to understand
  2. Easy to act on
  3. Attractive enough and
  4. Cost less than they appear to
  5. Hard to game the scheme

And overall, nudging users towards the actions you want them to perform.

The scheme mentioned in the screenshot above would fit into criteria 1) and 5), but not necessarily 2) 3) and 4).

But then of course, another important point is every incentive scheme has to be tested. We could have a lot of theories (like what I wrote above) but nothing beats real data and correct interpretation of that data.

With results from the test, you can then decide whether to scale up/down, adjust or scrap altogether the schemes.

Thanks for reading The Low Down (TLD), the blog by the team at Momentum Works. Got a different perspective or have a burning opinion to share? Let us know at [email protected].


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Jianggan Li is the Founder & CEO of Momentum Works. Prior to founding Momentum Works, he co-founded Easy Taxi in Asia, and served as Managing Director of Foodpanda. The two years running Rocket Internet companies has given him a lifetime experience on supersonic implementation, and good camaraderie with entrepreneurs across the developing world. He holds a MBA from INSEAD (GMAT 770) and a degree in Computer Engineering from Nanyang Technological University. Unfortunately he never wrote a single line of code professionally - but in his first job he was in media, travelling extensively across Asia & Europe, speaking with Ministers & (occasionally) Prime Ministers. Apart from English and his native Mandarin, he is also fluent in French and conversational in Cantonese & Spanish. He tried to learn Latin (for three years) and Sanskrit (for six months) as well. In his (scarce) free time, he reads, travels, hikes and dives. Pyongyang, Tehran & Chisinau are among the interesting cities he has been to.