Data has long been used in the retail sector to influence decision making around stock control, shape pricing strategies, and develop the customer experience. Importantly, writes Michael Poyser (pictured below), chief analytics officer, Ecrebo, data can also be used to gain insights into customer behaviour, which can be used to influence two key areas: customer experience and loyalty programmes.

As part of understanding customer behaviour, the need for successful, targeted, and effective strategies is critical – especially for those retailers competing in a crowded marketplace, against both traditional retailers and the likes of e-commerce giant Amazon. This omnichannel playing field is not level. In fact, one of the key challenges retailers face is ensuring customers receive a quality and consistent experience across each of the different touchpoints they have with the brand, no matter the channel, whether that is in-store, via email, online, in an app, or through a call centre.

Remaining relevant in an omnichannel world

Despite an increase in online shopping activity (there has been an increase of 51.8% in the buying of non-food items online and via mobile), the physical store is still important. With 84% of sales transactions still taking place in-store, the physical environment has an important role to play in the future of retail.

The point of sale presents retailers with a significant opportunity to engage with their customers. It is here that retailers can gather data about their customers in terms of what they are actually buying and their purchasing behaviour, all in real-time. It is this data, and how it is used, that will enable retailers to capitalise on the potential presented by the point of sale, an additional and largely untapped marketing channel.

Real-time data can be used to personalise offers for customers – regardless of whether they are members of a loyalty scheme, heavy buyers, or infrequent shoppers. The right technology at the POS can deliver meaningful communications for every shopper who passes through. It is just a question of how that data is analysed and used.

It’s all about personalisation

Retail offers are driven by quality, timely data. In the long term, this data enables the retailer to devise discounts and promotions based on items and categories that are relevant and important to the individual customer. The days of mass marketing ‘spray and pray’ tactics are long over, thanks to the use of data. Accurate and quality data about customer buying behaviour feeds into offers – and enables retailers to deliver targeted promotions, offers, and rewards based on previous behaviour and shopping habits.

Michael Poyser, Chief Analytics Officer, Ecrebo

But looking at the shorter term, the use of real-time data changes the game. At the point of sale, specifically, personalisation can be elevated to deliver more benefits to both retailer and consumer.

Retailers can return offers based not only on past purchases, but also on items in the basket, harnessing the data generated at the point of sale. Retailers can extend offers in the form of coupons or messages on till receipts, which can include stretch spend offers, discounts on new or regularly bought products, promotions on complementary products, or value-adds like product care information.  

Real-time data and the power of the POS

The use of real-time data isn’t just important for loyalty customers. Yes, it makes loyalty schemes work more effectively, but it can also be used with great effect to bring customers that aren’t signed up to loyalty schemes or infrequent customers back into store. Similarly, these techniques can also be used for retailers that do not have a loyalty scheme at all.

This all happens at the point of sale. In conjunction with the right technology, data is collected from shoppers. This can then be used to track their behaviour and send them on a journey, the aim of which is to provide an improved customer experience and relationship, which can ultimately increase spend with the retailer.

When it comes to those shoppers who aren’t signed up to a loyalty scheme, this presents a significant opportunity for retailers to capitalise on a largely untapped market. Consider, as an example, that only 65% of adults in the UK belong to a supermarket loyalty programme – which means there is great potential in the remaining 35% who aren’t members.

But how does it work? The software can use anonymised data linked to a specific series of coupons within the point of sale system. These are delivered over a period of time and are created based on that shopper’s purchasing behaviour, such as what’s in their basket, frequency of visits, or transaction value. Using this data, offers will be relevant and can include promotions of new or complementary products or straight-up discounts on historically purchased products.

For example, if the first offer in the journey is a discount on a product in the basket, once it is redeemed at the POS, that data is then used to generate the next offer. This could be a stretch-spend offer, another in-store coupon, or a cross-sell promotion.

While this is going on, the technology at the point of sale is processing the data gathered in real-time (spend, basket contents, and frequency of shop) to generate more relevant and personalised offers for the customer.

Real-time means real benefits

Moving away from the immediate use at the point of sale, real-time data can also be used to build up a more comprehensive view of the customer and their behaviour and purchases. From a retail perspective, historical data can certainly play a role in marketing campaigns and refining offerings, but it is the real-time element that sets successful retailers apart from competitors.

When it comes to campaigns, for example, there is often a time lapse between customer segmentation and execution. As a result, what was relevant last month is perhaps no longer so. But how can retailers get around this? By using machine learning to automate the process, the delay between segmentation and delivery can be minimised.

With the right software, relevant and personalised offers can be placed in the hands of the customer more quickly, prompting a faster return on investment. In addition, this approach can help the retailer save money and conserve resources, as campaigns based on current data have a much better chance of success.

Bringing automation into the equation can also help retailers make that leap into trigger-based marketing and campaigns.

As the name suggests, these campaigns are kicked-off when certain criteria are met or based around date-specific activity, such as Halloween or the kick-off of the Premier League season. For the most part, retailers see them as promotions with definite ends. However, by using the right software, multiple highly targeted campaigns can run simultaneously. This has particular value for retention campaigns, which will yield benefits the longer they are active. As customers lapse, offers are sent, based on the most up-to-date information.

There is little doubt that data has a critical role to play in the retail sector; and it’s one that will only grow in the future. But, when used properly, innovatively, and in real-time, it has the power to elevate retailers, help them improve brand value and deliver the kind of seamless, personalised, and consistent experiences that customers today demand. It will help drive these customers back into store, and keep them coming back, which will ultimately impact revenues and growth.