How confident are you that the prices you have set are the optimal prices? If your prices were higher, would you make more money or perhaps cause customers not to buy? If you lowered your prices, would you get enough extra volume to increase your profitability? These are common questions asked within companies every day, but most often are not answered. Companies worry about their pricing strategy, but frequently just hope they got it right — or good enough. There is a better way. It is possible to move beyond hope as a strategy and build confidence in your pricing by regularly using A/B testing.
The basic concept behind A/B testing is to change the value of a single variable in an offer to consumers, and measure the results to determine which offer was superior. In the case of setting prices, A/B testing is simple. The test is to offer the same product to similar customers, but at different price points. At the end of the test period, measure the number of customers who bought the product or service at each price point, along with the total revenue, margin, and operating income. Then use the price that delivered the best results.
To make the A/B test valid (and therefore worth relying on), there are a few factors that must be incorporated:
- Separate the customers into like groups. If you think customers in one location are more price sensitive than in another, and then you offer the lower price to the price-sensitive location, you are biasing the test. Make sure the groups are similar.
- Only test one variable at a time. If you are testing prices, everything must be the same except the price. If you vary anything else, like color, quantity or even the way the product is promoted, you won’t know if your results are driven by the price difference or differences in the other variable.
- Run the test long enough to get a robust set of transactions that can be evaluated. If you run the test for too short a period, you will not have statistically valid results. If you run it for too long, you will be losing money on the transactions occurring on the inferior price. The proper duration will vary from situation to situation. The more transactions that can occur in a time frame, the shorter the time frame needs to be.
- Do your test on a sample of customers, not all customers. The more customers you include, the bigger the bet you are making. The whole reason for using A/B testing is to build confidence in your pricing decisions by obtaining evidence of what works in modest bets.
- You can test a third price point by making it an A/B/C test. All the same principles still apply, but you are offering different prices to three groups of similar customers.
A/B testing can be used to make decisions on a variety of customer options other than pricing. For example, it can be used to determine which placement on a web page results in the most clicks, or which product configuration is most preferred. It can be used to determine if promotions make a difference in sales by offering the promotion to some customers but not to others. In any of those examples, the point of A/B testing is to move beyond guessing and obtain data to make better decisions.
Data-driven pricing strategies are far superior to those based on hope or gut feel. Simple tools like A/B testing can help you develop those strategies.
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