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Extradom is quite a unique type of e-commerce that offers blueprint and other custom architectural designs with the option to build them on a client’s property. Their goal is to make the experience of building property as convenient as possible. Their offer is aimed at future house owners and expanding companies that want to build new facilities.
Technically, it’s fair to call Extradom e-commerce. However, their unique offer makes their job quite challenging. Returning customer rate is close to zero, the sales cycle can take more than a year, and there certainly is quite a lot of direct and indirect competition that wants their piece of the cake. And the worst part is that the cake got much smaller last year. Why’s that?
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The Valueships team made a complex process feel smooth and easy. At first, I thought that with products like ours (and such a market), it would be challenging to determine prices using statistical models, but in the end, it turned out that it can be done and works. We got more than expected in terms of financial results, and we feel much better prepared for the future thanks to all the pricing know-how and tools we received.
Well, the year 2022 brought a wide range of economic problems for almost every industry, but the housing market in Poland has taken a particularly big hit. Material and property prices increased significantly, and banks became more hesitant to give mortgages, resulting in an over 50% drop in the total number of mortgages compared to 2021.
For example, comparing BIK reports, the market data from September 2021 showed PLN 8.2 billion in volume, while the data from September 2022 was PLN 2.2 billion in volume.
The situation for businesses like Extradom was becoming more and more dreadful. It wasn’t only a matter of growth at that point.
Extradom’s key goals were to increase revenue and Average Order Value (AOV). More specifically, Extradom wanted a more scalable and profitable pricing strategy and a team that would help them implement it in an orderly and timely manner. We also had to focus on boosting the EBITDA, which was a goal of the Private Equity fund.
Up to that point, the client was using a simple cost-plus pricing model with a lot of uncontrolled and aggressive discounting. They realized it was far from ideal and looked for pricing experts to help them find a more suitable and efficient approach.
What’s crucial, they weren’t just looking for a few smart-asses with a PowerPoint presentation. They needed someone who would go to the trenches with them and assist them on every step of the implementation.Price setting is incredibly challenging in this market due to subjective indicators influencing decisions, such as aesthetics and emotions. Overall it is a big challenge to understand what should and what should not drive the price.
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.
+12-13% AOV growth
Stable conversion rate despite a significant pricing increase
Maintaining growth despite very unfavorable market conditions
Know-how and analytical tools for Extradom team
