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Valuable insights drive growth for online retailer

 
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Understanding your target market is key for any marketing activity, however, truly getting to know your customers has the potential to uncover insights that can transform your business.

Customer insights are all about analysing data to better understand your customers, helping you make better decisions about how, when and what to sell to them as well as improving their overall experience with you. 

Seven Feet Apart is one of Britain’s leading online retailers of quality shoes. Founded in 2017, the business had a successful first year and was keen to build on this success by deepening their understanding of their customers and learning more about their attitudes and behavior.

To begin to understand their customers in more depth, Station10 was engaged to perform an initial analysis of their existing setup which included data from web analytics data (Google Analytics) and their e-commerce platform (Shopify).  From this, we were able to create a plan for building a more extensive data platform to understand, identify and segment customers to target with the right products at the right time.

What we did

Having already performed our initial analysis, we scoped out additional data sources to add to the existing ones to provide a more comprehensive analysis of Seven Feet Apart’s customers. We combined and analysed a variety of data sources including web analytics data, e-commerce data, email marketing data (Dotmailer), returns data and demographic data.

The key objectives of the customer insight analysis was to provide answers to the following business questions:

  • Who are our existing customers and where are they located?

  • How are customers acquired and what drives them to purchase?

  • Who are our most valuable customers?

Our first step was to gain more insight on Seven Feet Apart’s customers using Experian Mosaic Shopper Segments. This is a customer classification tool which helped us to understand likely customer characteristics, which would enable Seven Feet Apart to effectively communicate with them, with relevant messaging, across multiple channels. The tool highlighted a number of customer personas, a crucial part of understanding who customers are, how they shop and where they live as well as insights into their careers, aspirations and values. This process also lays the foundations for lookalike modelling (identifying new people who behave like current customers).

From this, we then created a score for every customer using all of the data (order value, order frequency and order recency) we had available to identify who the most valuable customers were.

The results

Once our analysis was complete, the initial business questions we set out had been answered. Now we were able to dig deeper (also analysing behavioural data such as marketing channel engagement and device preference) and provide useful insights to support Seven Feet Apart’s growth. We could provide these insights by exploring a new set of questions:

  • How are the most valuable customers acquired and retained?

  • How do the most valuable customers shop?

  • What drives the most valuable customers to purchase?

  • How does this differ from everyone else?

“As a consequence of the research and insight Station10 undertook and developed, we have immediately begun to evolve our business” - Matt Bagwell, Co-Founder

Our insights allowed Seven Feet Apart to understand who their customers were and in turn transform their marketing to reflect this. Since launch, for example, the retailer had been targeting people in the 30-45 age bracket. However, our research uncovered that there was a highly valuable group of customers in the 45-60 age range. This led to several strategy alterations including:

  • The demographics of models in campaigns

  • The range of products and how they were styled

  • Greater focus on ethics and sustainability

Finally, and arguably the most valuable insight relates to the affluence of customers. Seven Feet Apart were already targeting the AB1 group but our research showed that the most valuable customers were at the most affluent end of this demographic. This led to a change in pricing strategy with prices being raised to test elasticity of demand. This didn’t have any negative impact on conversion rate showing that customers in this demographic are willing to pay higher prices. 

Conclusion

In depth analysis and customer classification has proved to be invaluable for Seven Feet Apart, enabling more targeted marketing and an increase in profitability. Matt Bagwell, co-founder of Seven Feet Apart, commented “We are very grateful to have the confidence to make these changes based on evidence over instinct. We look forward to seeing the results of this new work and sharing them with Station10”

Could you be driving more value from your data? Get in touch with Station10 to find out how.