Promotions that offer an extra upgrade (e.g. a bigger size, an additional product) sell more if people need to pay a small amount for the upgrade (e.g. 1¢), instead of getting it for free.
It’s common to offer free product upgrades or throw in a free gift to make special promotions more attractive.
For example “Buy a large birthday cake today and upgrade to extra large for free”
But is this really the way to make the offer most attractive?
Take another example. You want to run a promotion to encourage sales of an electric toothbrush. Which offer would sell more?
- Buy an electric toothbrush for $30 and get 2 extra toothbrush heads for free
- Buy an electric toothbrush for $30 and get 2 extra toothbrush heads for 1¢
Let’s take a look.
When running a special promotion that gives an upgraded version of the product (e.g. a bigger size, an extra product), make people pay a very small amount for the upgrade (e.g. 1¢), don’t give it for free.
People will be more likely to buy it.
- Some types of promotions give a product upgrade (e.g. in size, in features) or add an additional product (e.g. an accessory) to encourage sales
- Charging a small token price (e.g. $1 or $0.1) for the upgrade – instead of giving it for free – increases how much people like it and buy it.
- The higher the token price (e.g. $2 instead of $1), the weaker the effect, although it must be more than 0 to exist (otherwise it would be free).
- For example, in experiments:
- People rated a digital camera + upgraded memory card special deal 39% better when the memory upgrade was offered for ¥0.01 compared to free. They rated it 34% better when it was for ¥0.1 and 22% better when it was for ¥1 (1 Chinese Yuan ≈ $0.15)
- 17.1% more people (90.7% vs 73.6%) decided to buy a can of juice when a special promotion upgraded its size (340 ml vs 163ml) for ¥0.1 rather than for free
Why it works
- We judge prices and deals using reference points and comparisons around us. For example, a $5 discount for a $15 calculator is more attractive than a $5 discount for a $125 jacket, even though we still save the same $5 in both cases.
- At the same time, research found that when the value of something is zero (i.e. free), we stop using it as a reference point.
- When an upgrade is offered for free, we judge the offer mainly using the price of the main or original product and rely less on the added freebie.
- But when the upgrade is for a very small cost, we take that into account and are attracted to how large the difference between the added value and the tiny price is.
This effect does not apply to pricing or discounting products on their own. In that case, free (or – even better – for $0) will perform better than even the smallest amount. For example, giving a burger for free will probably convert better than selling it even for as little as 1¢. This effect should work only if the burger is upgraded (e.g. large for 1¢) or bundled (e.g. get fries with it for 1¢).
Companies using this
- Generally, companies seem to lean toward using ‘free’ rather than small token amounts.
- For example:
- Stores in Malaysia used to promote Windows XP with a free future upgrade to Vista
- McDonald’s in Singapore offered free coffee to those who ordered breakfast online
- Packs of sodas, beers, or packaged snacks often come with 1 can or 20% extra for free
Steps to implement
- Consider the type of promotion you are thinking of launching.
- If it’s simply a price discount, this does not apply
- If the promotion offers more of or something on top of the promoted product, make people pay a very small fee for the upgrade
- At times, it might still be a good idea to offer something for free. For example, freebies are known to delight people.
Sometimes “fee” is better than “free”: Token promotional pricing and consumer reactions to price promotion offering product upgrades. Journal of Retailing (May 2016) by Wen Mao. School of Business, Southwestern University of Finance and Economics. China
Remember: This is a new scientific discovery. In the future it will probably be better understood and could even be proven wrong (that’s how science works). It may also not be generalizable to your situation. If it’s a risky change, always test it on a small scale before rolling it out widely.