How consumers’ spending data will help to personalise the customer experience and drive consumers back in-store

This article is brought to you by Retail Technology Review: How consumers’ spending data will help to personalise the customer experience and drive consumers back in-store.

By Dr Sam Short, Chief Data Scientist at Upside Saving.

Pandemic difficulties aside, today’s retail environment is challenging. Whilst the shift to buying online has been an easy one for consumers, it has presented new and existing challenges for retailers, especially those with an omni-channel presence.

Sure, more online sales means more revenue and more data for retailers. But it also means more returns, more postage fees, and more damaged-in-transit goods. This severely impacts retailers' bottom lines and also messes with their supply chains and stock predictions.

It stands to reason that the problem retailers are currently trying to solve is how to encourage consumers back in-store. Then, once they’re in store, how to get them to spend money. The solution lies with data and personalisation; marketing to the right customers, at the right time, with the right offer, which is hyper-personalised and can be redeemed in-store.

We should first agree on one thing; ‘spray and pray’ marketing won’t work. Or, better put, it will work, but it will be costly. It would be better to focus on personalising the marketing, offers and rewards or content, for the consumers who actually have a propensity to shop in-store. Some consumers won’t go back to shopping in-store, and that’s fine. The key is using data to figure out who these people are so that they can be excluded from a hyper-targeted marketing campaign.

But what data? The retail industry has always been data-rich and trying to understand customers and their preferences is not new. That said, the data that is currently used is predominantly a retailer’s own spending and click data, data from Google analytics, social media, and expensive and often subjective surveys and interviews. Whilst this data is great, it doesn’t give a complete picture of the customer. Existing data doesn’t show how a customer actually shops with competitors, or give a view of their financial wellbeing. Most importantly for the problem retailers are trying to solve, existing data doesn’t show if a customer has started shopping in-store again, or indeed has shopped in-store previously.

The key to unlocking a true understanding of customers lies in consumer spending data. Individual customer-level spending data provides a holistic view of the customer - their age, financial situation, where they live, their hobbies and interests, how they shop, where they shop, when they shop. Obtaining historical person-level spending data with full consumer consent, in exchange for cashback as they spend with retail partners, is a great example of this.

It is this kind of person-level spending data that can be used to hyper-target a marketing campaign. To illustrate this, imagine you’re a national coffee chain. What if you knew that Ahmed buys coffee, he spends £100 on coffee each month but only £20 of his £100 is with you. What if you also knew that Beatrice buys coffee, she spends £20 on coffee each month and it’s all with you. 

And finally, there’s Chris – they don’t drink coffee at all. Spending data can be used to hyper-target a marketing campaign. By not wasting money targeting consumers who will never buy from you, like Chris, or consumers who are already completely loyal, like Beatrice, you can focus the entire marketing budget on customers that will drive incremental revenues, like Ahmed. 

Once you’ve figured out who to target, the next step is to personalise the offering. For this example, imagine you’re a department store trying to encourage consumers to shop in-store with promotions and discounts. If you knew that one customer, despite searching the internet for motor bikes, was actually a new dad, you could prioritise family-related offers over bike accessories. For another customer, whilst they might spend time procrastinating on Rightmove and Zoopla, the data shows they have only just started saving for a house deposit. Therefore instead of giving them discounts on soft furnishings and kitchen appliances, you could give them a little help to buy their everyday essentials, enabling them to save for that deposit more quickly. 

In an increasingly digital world, where consumers are inundated with adverts; adverts for things they already bought weeks ago, things they have no interest in ever buying and things their partner browsed when they borrowed their computer, retailers who provide legitimately relevant content will have growing success with consumers. In order to increase return on investment through marketing, whilst improving brand perception and customer loyalty there is only one clear solution. The most efficient and effective way to do this is through the responsible and ethical use of consumer spending data.