The Retailer Spring Edition 2023

SPRING 2023

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3. Retaining customer relationships Data analysis can also help you identify at-risk customers to influence retention and repeat purchasing. According to McKinsey , 76% of people are more likely to consider a brand after receiving personalised commu nications. Customers want to feel heard and valued by the brands they shop at, without feeling like they’re just another transaction. Analysing purchasing behaviour to find patterns across customers helps you build a more accurate model, or profile, of at-risk customers. You’re then able to send more targeted communications to entice those Personalised shopping experiences don’t only apply to online customer journeys. Many high-end retailers like John Lewis and Harvey Nichols offer in-store personal shopping experiences. Using customer data, such as previous purchases, could massively improve a customer’s in-store experience. Showing them products that they’re likely to have an interest in buying can make them feel important, listened to and can save them time, which today, is priceless to us all. Customers are much more likely to return to retailers where they have a seamless, professional and, ultimately, enjoyable experience. customers back into the purchasing cycle. 4. Personalised shopping experiences

Is upskilling in data analysis the answer? Retailers are facing harsh challenges that have surfaced since the start of the Covid-19 pandemic. And like many retailers, you may want to implement some of the above solutions for improving sales but lack the necessary talent within your teams. So how can you acquire the data skills needed to better understand these changes in customer behaviours? And equally important, how can your business afford to fund this talent acquisition in such a demanding hiring market? Government Levy-funded apprenticeships in data analytics could be the answer.

Kate Shropshall kate.shropshall@cambridgespark.com

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81% of consumers have changed their behaviour because of current economic