Using customer data to drive customer loyalty and sales

Data comes in many forms. It tends to get divided into quantitative and qualitative, although it can be more helpful to think about the quality of the data, whatever kind it is because that’s what determines how useful it is. Good quality data is robust and unequivocal, for example, if a customer spent X amount with a certain retailer over a period of time, that’s a simple, no denying it, fact.

If a customer buys shoes 90% of the time they shop with a particular retailer, that’s also an indisputable fact. But poor quality data is ambiguous or open to misinterpretation. For example, if you ask anyone what they would do in a set of hypothetical circumstances relating to a product or brand, your data tells you what people think they would do, it doesn’t tell you what they would do. This means that quantitative data is often better quality data, but it isn’t as simple as that either.

Customers asked to rate their satisfaction with a purchase using a number between 1 and 5 will not necessarily answer consistently despite how well they are instructed. One customer may feel perfectly satisfied and rate their experience as a 5. Another customer may feel similarly satisfied by their experience but may also believe in reserving top marks for an extraordinarily satisfying experience. The data may be recorded as quantitative, but it is not as robust a reflection of reality as data showing how much a customer spent over time.

Conversely, qualitative data that is a record of customers’ written feedback may provide a more accurate picture of each of the above customers’ level of satisfaction. This data isn’t as easy to search through if you have thousands of customers, but when you are looking at records relating to individuals, it can provide the vital details that complete a story suggested by other more easily searchable data.

Capturing meaningful customer data

Capturing good quality data about your customers is a gift that keeps on giving because quality data about recent activity can be useful both as soon as it is captured and long into the future as a means of comparison against new data. In other words, the more of the same data you can capture over time, the more easily you can distinguish patterns in that data. For example, the longer you record customers spend in your store, the clearer the pattern of his or her purchasing behaviour. It may take a while, with a customer who only makes a purchase every few months, for their purchasing behaviour to show a pattern, but when it does and it tells you what that customer is interested in then you can more effectively target that customer with products or services you know will appeal to them.

Another benefit from capturing data about a customer’s purchasing behaviour over a long period is it gives you the ability to spot deviations from the norm. For example, a customer’s monthly spend might suddenly go up or down, or the frequency with which they purchase shoes might rise or fall. While, on its own, data like this will probably not be enough to establish the underlying reasons for changes in a pattern of purchasing behaviour, it can be enough to guide further enquiry through conversation with a customer. When a retail associate learns what has changed for a customer this information can be used to improve their retail experience with your brand, making them feel more seen, more cared for, more satisfied and more loyal to your brand. However, no one will know to ask what has changed without an indication from other data to prompt the question.

Meanwhile, triangulating records of which branch a customer makes which purchases in, with social media posts containing photos of the customer and their mother, in which the brand is hashtagged, can inform a retailer that twice a year a customer visits their mother and takes her out shopping. Armed with that data, various options open up to the retail associates of that store to enhance and personalise that shopping experience, promoting sales and brand loyalty. There are many layers of data you can capture about a customer, within which you can then search for insights to help you to personalise their experience with your brand. There’s a lot of data you can collect about your customers’ relationship with your product or service. Such as when, what and on what did a customer-first spend with you? For some retailers, this alone has proven to be a big predictor of future behaviour, though it won’t always be.

Additionally, how much does a customer spend per shop, how much over time, how frequently over time and in what locations? What type of product is a customer most interested in, do they favour design or function, beta products or more fully developed, the latest fashion of end of line bargains? There’s also data you can capture that is more to do with a customer’s relationship with the brand. What is their preferred contact method, how do they like to be addressed, what is their contact history, have they provided feedback before – was it good or bad, do they follow or have they mentioned the brand on social media?

Finally, there’s data you can capture that helps store associates build a truly personal interaction with your customers, and avoid making every conversation about the brand or its products. What is their favourite colour, favourite music, pet’s name, job title?

To help store associates make the most of available customer data, KIT can create individual profiles for each customer, to record information captured at different ‘touchpoints’ in their journey to and beyond every sale. This includes products viewed or favourited online, as well as information added by the store associate. Using insights from this data, store associates are in a much stronger position to create deep engagement with these customers, nurturing customer loyalty and driving sales.

Easy to pick up, store and retrieve data on, KIT is the perfect tool for the modern store associate. It can also be used as an assisted selling tool, providing illustrations and information about products that allow the customer to feel in control of their research and choices, while the store associate plays the role of assistant. For more information about KIT and to arrange a full demonstration, please contact the team on +44 203 691 2936. You can also email info@instore.technology with any questions or to request more information, or if you prefer you can also complete the short form on our Contact page.