Victoria Plum wants to make data-driven decisions by bringing together information from across the business to gain strategic, commercial insights and deliver the best experience for its customers. Discover how its technical and data teams started with one business problem and ended up with a scalable data platform.
Founded in 2001, Victoria Plum has been at the forefront of online bathroom buying for over 21 years, pioneering new and innovative ways to help make life easier for more than two million customers in the UK.
With its specialist delivery service, state-of-the-art distribution centre and fully accredited Design and Installation service, Victoria Plum sells exclusively online – meaning the business can pass on savings directly to its customers.
Victoria Plum is already using data effectively in its marketing department, but it wants to expand this level of data maturity to other parts of the business. Charles Lamb, Victoria Plum’s head of insight, explained: “We want to standardise and bring together data from across the business so we can work cross-functionally. We wish to understand how a decision we make in one area of the business impacts another.”
However, whilst there are pockets of data excellence and expertise within the business, the busy internal team does not have the resources or experience to create the data pipelines and platform required to bring their plan to fruition. Victoria Plum needed an intuitive, scalable solution that would show results quickly.
“Whilst we knew that we had a business problem to solve, the plan was something we still needed to create,” said Charles. The data team wanted to quantify the commercial impact of a particular promotional strategy on basket conversion rates and “ultimately understand how pricing impacts customer buying patterns”.
Victoria Plum already used GCP and BigQuery to store and analyse its marketing data. “A lot of our data best practices come from how we work with Google as a technology partner, so it made sense to build upon this rather than start from scratch,” explained Charles.
Google recommended several partners and Netpremacy was the favourite. “It became clear that we would work well together. We wanted someone to work with us throughout the process rather than simply deliver the result.”
Netpremacy worked with Victoria Plum’s technical and data teams to understand what was needed. Whilst Netpremacy would be responsible for the design and execution of the solution, Charles’s team made strategic decisions on what data to include and how they would define customer impact.
“There’s only so much data we have access to, so we have to think about how we’ll quantify something like customer impact through a specific data metric, and how we can interpret it once we have that information”, explained Charles.
Whilst the internal team defined the specific data to be used, Netpremacy’s first step was to evaluate the existing foundations of Victoria Plum’s GCP environment with a GCP health check. This would establish whether any changes needed to be made before the data platform was created.
Next, a data platform was designed and built on GCP and a data pipeline set up to transfer the data into GCP and BigQuery. Data sets were analysed, merged and transformed in BigQuery and Data Studio was used for data visualisation.
Throughout the process, Victoria Plum tested and validated the data pipeline and worked with Netpremacy to analyse any initial results. “It was a very collaborative process. Even when you outsource a project, it was important to me that we understood the thought behind it,” said Charles. The internal team balanced an understanding of the solution with time and resource constraints. “It was good for us to get the overview version to get us through the details quickly. By working together throughout, we reduced any surprises and the need for rework.”
The result: a data platform that delivered an answer to what the team asked.
The start of data in a single location. By bringing key information together, Victoria Plum can expand on the findings and look for actionable insights. They will be able to see the direct impact of new strategies in real-time by building on this example.
Shared knowledge. “What we have now is easy to build upon,” says Charles. “The biggest area that was new to us was the physical construction of the pipeline, getting information from A to B. We’re good at hypothesising business problems and analysing the data, but we now understand the ‘plumbing’ of the data too.”
Saved time. Rather than get into the details or invest time to learn a whole new skill, Charles’s team has had time to focus on the areas they excel at.
“We’ve learnt new skills to an extent but a lot of our constraints are around time and resources. Internally, we have to prioritise our customer-facing work so to have a partner to do this element has springboarded this project.”
“This is our first step towards getting key business data into one place and making it accessible. I want me and my team to be able to spend more time analysing business problems in real-time rather than looking back at previous results,” said Charles. “I’ll take this example back into the business and we’ll continue to test, measure and evaluate it. There are plenty more business problems to solve and data to bring into the environment – this is just the beginning for us.”