The process consisted of three phases.
We gathered all the relevant data regarding products, their popularity, prices, variants, as well as conversion rate and other transactional data. Our goal was to understand what exactly are the value drivers and how significant they are from the clients’ perspective.
For example, we wanted to know how much people are willing to pay for an additional garage, bathroom, or basement. So, we ended up with a list of about 25 similar factors that we included in the analysis.
Then, we went on to do the same with the competition. Once we had a comprehensive set of data, we could compare portfolios, prices, discounting strategies, and many more crucial angles.
First, we took all the available internal data about products and sales. Then, we created a data science model to detect and analyze similarities between our client’s offer and competition. We ended up with over 200 mln SKU comparisons that helped us prepare a list of precise instructions on how to deal with each and every product. As a result, over ⅔ were set to have their prices increased, and ⅓ decreased. Essentially, at this point, we created a brand-new pricing.
The analysis turned out to be a complete game-changer in terms of how the client approached the entire portfolio. The model not only helped the client set the prices but provided the company’s team with a simple, scalable process for pricing in the future.
The implementation was the cherry on top. We prepared a detailed schedule for all the significant changes to make sure the client’s team has all their need to move forward. Of course, we were still there to answer any questions or assist the team throughout the process.
Before we move to the results, we simply have to shout out the dedicated project team at Extradom and the financial director, Joanna Wróblewska, who worked with us closely during the entire process up until the final technological handover.
We’ll move on to the numbers soon, but before we do that, we have to talk about an even more important aspect in the grand scheme of things: capability building. After the project, we left Extradom’s team with both the know-how and analytical tools to efficiently expand their business in years to come.
But how does it translate to financial results?
Our initial prediction for an average order value (AOV) increase was about 6%. In the end, we achieved approximately 12-13% growth.
At the same time, the conversion rate remained stable despite a significant pricing increase.
Most importantly, the client maintained growth despite highly adverse market circumstances.