Data in retail. Top 10 innovations – how are Brands and Retailers collecting and then using data to drive in-store performance?

Brands and retailers are more interested than ever in data collection to learn about their customers. But what are they doing with this data, and how can they use it better?
25 januari 2021

Smart bricks-and-mortar retailers are using data analytics to make the in-store experience as bespoke as possible to local shoppers. This includes leveraging data such as long-range weather forecasts, household expenditure and property prices. They can pick the goods most suited to local markets, and even choose the clothing range to display front of store based on a Bank Holiday weather projection. And that’s just the start …

Top 10 data innovations

Here are 10 great examples of retailers using data in innovative ways

  1. In-store screens where customers can sign in and search their order history and wish list, providing valuable insight for sales assistants. When it comes to clothing, this can be enhanced with smart mirrors where customers can request different sizes, and customise styles in different fabrics. This combines personalised boutique shopping with the flexibility of e-commerce.
  2. Use of machine learning and algorithms to help fashion retailers analyse customers’ purchase history via loyalty cards to recommend hemline lengths and styles (skinny, cropped, bootleg, shorts …) and preferred necklines.
  3. Developing a relationship with customers that goes beyond the transactional, inviting them to exclusive events such as new-season launches they can boast about on social media, expanding brand awareness.
  4. Ensuring that investment in tech is always aligned to the bottom line. One retailer using data analysis in stock control discovered that a product assumed to be a best seller was only actually selling at full price for a third of the time. (1) This meant that profits were low despite high volumes sold, leading store managers to concentrate instead on more lucrative lines.
  5. A High Street teen brand is using online data gathering to boost in-store experience and revenue, even though only 15% of its sales come from e-commerce. By launching new ranges online and tracking shares, likes and comments it can carry out market research without the expense of hiring survey consultants.
  6. The benefits of working with flexible in-store experience experts who can provide modular displays is underlined by the data-centric approach employed by one lifestyle retailer popular in seaside resorts. It is using long-range weather forecasts to decide store by store whether to display shorts or rainwear for the next Bank Holiday.
  7. Data-driven incentivised discounts. Here’s an example: if you spend an average of €30 a week, the retailer might incentivise you to spend more with a coupon offering €10 off a spend of €50+. This depends on the speed of cloud computing to generate the coupon in the second between completing the payment and printing the receipt – applying Amazon-style personal history convenience in a bricks-and-mortar store.
  8. Gearing up your point-of-sale system to deliver insights into vital metrics from basket sizes and sales trends to profit margins and customer counts. You can plan for seasonal variations in demand to better manage cash flow, and use flexible modular displays to offer customers a more relevant in-store experience.
  9. Analysing previous sales and inventory is crucial to running future promotions and mastering intelligent stock ordering. Data is the gateway to identifying last season’s bestsellers, the shoppers with the most to spend, and the designers and suppliers most popular with your customers.
  10. Introducing foot traffic analysis software can be another game-changer. These tools use beacons and people counters to provide data on how long customers spend in different parts of the store and how many people pass through. If the back of the store is neglected, staff can probably shed light on the reasons why and you can freshen up your displays and décor there to draw customers in.

Key takeaway - involve your customers

If there is one key takeaway about data mastery to improve sales, it is that the most effective data collection campaigns come when brands and retailers make their customers part of the process. Ways to do this include encouraging shoppers to share their likes, dislikes and spending habits through online and in-store conversations, surveys, invitations to in-store events and point-of-sale incentives. Talking to in-store experience experts can help you leverage these possibilities to the full.

Making data gathering a partnership with your customers not only helps you get to know each other better, it also builds all-important trust.


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