Understanding how your customers respond to changes in price is one of the most valuable insights a business can gain. Done right, price sensitivity testing can help you improve profit margins, optimise pricing strategies, and gain a competitive edge in the market.
But running a pricing experiment without the right foundation often leads to unreliable or misleading results. That’s why it’s critical to first complete a price sensitivity assessment—a structured, five-step approach that helps you understand where and how your customers are sensitive to price. Once that groundwork is done, you can move into the experimental phase with confidence.
This blog walks you through the second stage in this journey: how to design and run a good price sensitivity experiment. The steps below are simple, practical, and structured in a way that helps you generate insights you can use.
How to Set Up a Price Sensitivity Experiment?
1. Define a Clear and Measurable Objective
Every strong experiment starts with a clear goal. It’s important to define what success looks like before you begin. Make sure your objective is specific and measurable.
For example:
“We want to increase the product margin by 5% over the next month.”
This gives you a clear target to aim for and evaluate against later.
2. Split Your Data into Test and Control Groups
Once your objective is defined, the next step is to create two groups:
- Test group: where the pricing changes will be applied
- Control group: where pricing remains unchanged
You can split the groups by product, sales channel, or customer segment. The most important thing is to ensure fairness. A good experiment isolates pricing as the main variable, avoiding influence from unrelated market changes.
This makes it easier to tell whether any margin improvement was due to your pricing strategy or other external factors.
3. Avoid Bias in the Setup
Bias can skew results. If you already know that customers on one platform are more price-sensitive than others, you should not treat all platforms or customer segments the same.
Each segment may need a slightly different setup. For instance, Amazon customers' expectations should be different from those on another platform where pricing behaviour is less sensitive.
Being realistic about these differences helps you create more accurate experiments and avoid misleading results.
4. Choose the Right Timeline
Not every experiment needs to run for the same amount of time. The right duration depends on your business model.
- You might start seeing results within a week in B2C (business-to-consumer) setups like online marketplaces.
- In B2B (business-to-business) environments, it can take longer, sometimes a full quarter or even six months, to gather meaningful insights.
Don’t rush. Give your experiment enough time to play out properly based on the type of market you’re testing.
5. Evaluate Results and Learn from Them
The final step is to measure what happened:
- Did the test group meet the objective?
- How did the control group perform in comparison?
- What’s the difference between the two outcomes?
These answers help you understand the real impact of your pricing experiment. More importantly, they help you learn. If some products behaved differently than expected, dig deeper. Maybe your model needs more variables. Maybe some customer segments need to be treated separately. This is a continuous learning process.
Do you want a free demo to try how SYMSON can help your business with margin improvement or pricing management? Do you want to learn more? Schedule a call with a consultant and book a 20 minute brainstorm session!
