Okay. First question. Why would you want to a/b test the pricing of your products? Surely it goes against the foundations of customer centricity offering a product to one person at a different price to another customer? Doesn’t this get confusing when you consider purchase attribution? Will customers see one price and then come back and see a different price? All great questions, so let’s jump right in.
Why should you be a/b testing the price of your products?
Let’s consider Marketing 101. Remember, price is one of the key components of the classic marketing mix. And let’s face it, as consumers our response to pricing is being tested all day long. Whether you’re booking a hotel room or a flight, or purchasing a product at 3 for £10 when the usual price is £3.50… we’re running computations in our heads all day long considering whether we’re getting value for your purchases.
Testing pricing is not a new thing. Also consider the discount codes and seasonal offers you throw at your customers. For many brands, DTC brands in particular, you’re not simply competing against rival products. You’re competing against perceived value. It’s why so many SAAS companies tell you that their software is the equivalent price of a Starbucks coffee a day.
And the reason, as marketers, we test pricing is to find a sweet spot in terms of profitability and customer perceived value.
Your hypothesis can be as simple as ‘Will we increase profitability by decreasing our price from £15 to £13 due to the increase in product conversions?’. Yes, there are all sorts of further considerations to bring in to play, especially for businesses that are reliant upon repeat purchase. For now, it’s keep this at a simplified level – how much influence does price have on our ability to sell a product?
Product price modelling is all over the shop. Literally.
For most DTC brands in modern ecommerce price is no longer a static variable.
Here’s a question though, with discount codes you’re trialling impact on conversion and profitability through discounting. What if you used a/b testing to help better understand the impact of an increase in price? Even a minor increase in price, let’s say 5%, could have a significant impact on profitability for any high volume store. The earnings start to stack up.
The biggest challenge you face though is proving impact. Does changing the price from £20 to £22 actually impact sales conversion? You don’t know until you either shift the static price up (which will not allow you to run a valid a/b test as you’re looking at different timings) or split test.
How do you a/b test pricing on Shopify?
Like everything answer I give in the Shopify ecosystem….
“There’s an app for that”.
In fact, there are many apps that allow you to a/b test pricing.
My favourite is Dexter. The video below runs through how Dexter works;
What I love about Dexter is the ability to run to statistical significance. The reporting isn’t simply a ‘this price converting at x%’. You get real data to work from. You can also set the % of visitors that will view the alternative price, eg a 50/50 or even 90/10 split if you’re hesitant running a price variation to 50% of your audience. You will, however, need to ensure your product has enough reach (stock volume as well as page views & sales) to make this a worthwhile experiment. There’s little to be gaining running these tests on products where you see 1 or 2 sales a day. This is about products with existing sales volume and where you want to increase profitability.
Your results will provide you clear validity in terms of the overall success of the price test itself;
Dexter is priced based on your current volume of product page views. It’s a highly recommended app that will allow you to better understand the impact of price changes before you make any permanent price adjustments within your product range. Click below to learn more.
Dexter is a simple to operate a/b testing tool that allows you to learn the impact price variations have on revenues, conversion rate and ultimately profitability.
Run a/b tests on products with an existing volume of traffic where you'd like to better understand how any price changes (decrease or increase) have on your products prior to making any impactful changes.