How retail can capitalise on data growth
The retail industry has always been data-rich. The ability to identify consumer spending behaviour and preferences in-store has been commonplace for years. Furthermore, the move of consumers online has only increased the richness of the data available to retailers; whether it is their own data, from clicks on their website and items in their baskets, or third party data, from social media sites and cookies tracking consumers’ clicks elsewhere.
Until the introduction of Open Banking, click data was where the richness ended. Open Banking is a series of reforms that allows consumers to opt-in to share their spend data, such as individual bank transactions, regular payments they make, and companies they buy from, with authorised providers. An example of Open Banking put to use is budgeting apps: consumers share their spending data in exchange for a breakdown of where they spend their money. Another, arguably better, value exchange would be for consumers to share their spending data to effortlessly obtain cashback as they spend with, and are loyal to, specific retailers, but that’s a subject for another article.
It is fair to say, insights derived from Open Banking spend data are a game changer for the retail industry; not only because it unlocks a multitude of competitive advantages and business development opportunities, but because of the considerations afforded to data privacy (in addition to specifically giving consent to share their spend data, consumers must also re-authorize access every ninety days).
In the aggregate, spend data insights offer a real-time view of the market; this can be broken down by sector, location, or even to a view of a company compared to their competitors. It becomes possible to easily answer questions such as: How is the market performing? What is my share of the market? Are there any emerging trends? What is the current ratio of sales in store vs online?
Companies can also gain a true view of their customers. Without the need to rely on expensive and often subjective surveys and interviews, combined with social media and Google analytics, it becomes possible to build reliable personas that are a true reflection of customers. Not only can retailers understand the type of consumer that shops with them - their age, financial situation, where they live, their hobbies and interests - they can also understand how they shop both with their competitors and more generally. Do your customers shop as regularly with you as your competitors? What is your share of wallet and how is it evolving?
Individual customer-level spend data provides a holistic view of the customer and is also incredibly valuable. Imagine you’re a coffee chain. What if you knew that Alice buys coffee, she spends £100 on coffee each month but only £20 of her £100 is with you. What if you also knew that Bob buys coffee, he spends £20 on coffee each month and it’s all with you. And finally, there’s Clarice - she doesn’t drink coffee at all. Spend data insights can be used to hyper-target and optimise marketing campaigns; they reduce the amount of time and money wasted targeting consumers who will never buy from you, like Clarice, consumers who are already completely loyal, like Bob, thus enabling additional marketing budget to be spent on customers that will actually result in incremental revenues, like Alice.
It’s important to note that the benefit of spend data does not reside solely with the retailer; it can be used to significantly enhance the customer experience through personalisation. In an increasingly digital world, where consumers are bombarded with adverts for stuff - stuff they already bought weeks ago, stuff they have no intention of ever buying, stuff their partner searches for when they borrow their computer - retailers who provide legitimately relevant content will have increasing success with consumers.
It’s not just about smart marketing, though. Spend data insights could be used to personalise a website experience or loyalty programme. Imagine you’re a department store. If you knew that Derek, despite searching the internet for motor bikes, was actually a new dad, you could prioritise family-related pages over leather jackets. Or what about Ezra, whilst they might spend time procrastinating on Rightmove and Zoopla, they have only just started saving for a house deposit; instead of giving them offers for sofas and kitchen tables, you could give them a little help to buy their everyday essentials, enabling them to save for that deposit more quickly.