How can technology help retailers cut discounting?

High street retailers are on the backfoot as slowing consumer spending and online-only retailers force net margins to the floor. But technologies, such as predictive analytics and machine-learning, could be the key to help the high street stock the right products, at the right price, in the right quantity to beef up their margins and bottom line.

While discounting is great for both consumers and retailers in the short term, it simply cannot be sustainable in the long-term. According to a survey of 500 retailers by Klarna Bank in Sweden, 53% say the “always-on” nature of sales is having a negative impact on profits. The research also found that 57% of consumers now expect regular sales. The bank says this means discounting has become a “much more fluid and unpredictable phenomenon”, so, what is to be done and can retailers break out of the discounting cycle?

Using machine learning to fight discounting

AI, machine learning and analytics applications can apply an infinite number of algorithms to spot real-time consumer trends or predict customer behaviours. “This in turn will help fight against unnecessary discounting,” says Rob Barnes, managing director in Accenture Retail.

“Additionally, analytics and machine learning can identify disconnects across retailers’ data, prescribe specific actions to take to solve these disconnects, and prioritise them by financial impact to the business. This allows the retailer to make educated decisions around which items should be considered for discounting, and what benefit the business will receive,” he says.

Optimising price

German fashion retailer Bonprix turned to price optimisation software to improve its margins. It used software from Blue Yonder to move from rigid price-conversion tables to an automated AI-based solution. This price optimisation enabled Bonprix to set prices individually and specific to the market as well as increase its influence in the international market with consistent or improved earnings.

Using predictive analytics to combat discounting

The failure to implement a data-driven discounting strategy runs the risk of undermining profitability by diluting brand positioning, increasing cannibalisation, and introducing stubborn consumer discounting expectations, according to Adam Hadley, CEO of analytics consultancy QuantSpark.

He says the main challenge for retailers is to understand at scale how its customers are responding to discounting.

“Important questions to ask are: how does a given discount affect volumes? How does the depth, combination, and duration of discount change customer behaviour? Overall is this truly profitable when considering the operational costs associated with implementing discounting programmes? How to identify at the SKU level where discounting could be beneficial and eliminate it elsewhere?” says Hadley.

Improving basket analysis

Sharing data with merchandisers, shop managers and marketers can help with a retailer’s basket analysis to combat discounting before it even starts. This predictive analysis can reap rewards.

Arcadia Group, parent company of several high street clothing retailers including, Burton, Dorothy Perkins and Evans, implemented a business intelligence platform from Information Builders called WebFocus. With the platform, the retailer could analyse how shop window displays drive additional sales of clothes within ranges and the best combinations of clothing within stores, avoiding the need for discounting.

How to prevent the need for discounting in the future

Hitachi Consulting’s retail lead Pierson Broome says there is a surge of interest in sophisticated sensor technologies such as LiDAR, whereby sensors automatically (and anonymously) track shoppers to see how they travel around the store and what they interact with.

“By tracing how consumers travel around a store, retailers can use intuitive visualisations of ‘heat maps’ and understand what customers might be missing – for example campaign promotion or full-priced items –, allowing store managers to re-plan layouts and ensure that their intended products are seen – and purchased,” he says.

Meanwhile, Nikki Baird, vice president of retail innovation at Aptos, says personalisation technology will drive a future where retailers do not need to discount.

“AI-enhanced forecasting and machine learning analysis of consumer behaviours will offer retailers insight on how to influence those behaviours. Most of the future technologies that will benefit retailers are already in play,” she says.

But Baird argues it is a lack of technology adoption which is holding retailers back.

“Crowdsourcing, IoT data, social media trends – these are great examples of technology that is already are out there, but they are not currently being leveraged to the best effect in preventing the need for discounting, and they certainly could be.”