Algorithmic retailing: a strategy for growth in a difficult market. By Ed Betts 

Inflation is a huge problem for consumers reticent to spend and retailers struggling to stay afloat. Looking at the UK, the rate of inflation is in slight decline, that is not as positive as it may seem: inflation itself remains at the kind of peak the country has not seen since the early 1990s. The ONS’ headline statistic, the Consumer Prices Index, suggests that despite inflation slowing, the average price of retail goods rose 8.7 percent in May 2023, down from an 11.1 percent peak in October 2022. Kantar data is even more pessimistic, reporting that like-for-like grocery price inflation sits at 16.5 percent in mid-June – the lowest rate in 2023, but the sixth highest in the past 15 years.

Inflation rates may be dropping, but this has no impact on the average consumer. Prices on the shelf are increasing despite the best efforts of retailers – and the public is responding. Seventy percent of households now express significant worry about food and drink inflation, and many have switched their entire shop to deep discounters in the face of continual price rises.

Joining the dots of big data
Inflation affects every aspect of a business. Employee wages are growing, suppliers’ costs are increasing, supply chain and premises expenses have maintained significant highs. Retailers are on a knife-edge, balancing significant expenses against the demands of a public hungry for lower prices while still looking to receive a prime customer experience. The choice is to either fight every fire individually, using the time, effort, and expense of high-level employees to solve tiny problems piecemeal, or to find a modern retailing solution which allows the internal focus to stay on strategy.

Algorithmic retailing (AR) – the term used by Gartner for the use of AI in retail to drive automation and recommendation systems – is an essential tool in the fight against inflation. It connects big data – every vital point from the shop floor to the stock room to the supply chain, and beyond to live market data – with algorithmic AI, which is able to analyze that data quickly, precisely, and independently. Algorithmic retailing enables the automation of processes and planning through strategic guardrails and thresholds providing a way to smoothly turn a go-to-market strategy into reality, and intelligently share data between all business units to ensure their alignment.

Deep insights through deep learning
AR is a tool which, once trained and established, knows the important figures more intricately than a human ever could. It aids broad strategic changes, but also enables business adjustments and predictions to be made on a microscopic level, based on data points which may otherwise be missed. It is perhaps the most powerful strategic tool available to today’s retail businesses, and a vital solution to the inflation equation.

The ability to free up human bandwidth by, for example, determining the pricing of lower-impact items through an AI model allows the strategic focus to be put on in-demand items, essential in a high-inflation environment. The CPI is calculated based on the contents of an average shopping basket; knowing the precise impact of pricing on less critical items may be exactly what is required for retailers to invest in lowering prices on the CPI’s staples and keep customers happy.

Predict, discover, test, respond
Algorithmic retailing’s insights are as granular as they need to be. They can offer anything from a sweeping oversight to minute-by-minute analysis of an individual product. Since we cannot assume that the effects of inflation will be the same across every product line and on every supplier, an algorithmic approach allows product verticals to be separated, analyzed, and acted upon individually. Changing market dynamics, however slight, need not lead to panic; with all the data available and an algorithm ready to respond, an effective response is readily available.

AR can build predictive models based on market data. It backs up proposed changes by generating detailed simulations, taking past data into account. Every strategic decision is then ready to be confidently put in place, having already been fully tested. Those areas where the fluctuating market clashes with existing strategy can be quickly identified, and the solutions found. ONS statistics show that inflation has been highly unstable over the past few years, yet the agility offered by AR creates the opportunity to pivot on a moment’s notice and make the most effective response to changes as they happen.

Retail AI is not equivalent to the AI currently being popularized by text-generating neural networks; AR’s live calculations are based on rigid data and sharp calculations, not on educated guesswork. Its automations must follow strict guard rails, ensuring that prices and orders stay within defined limits. Caution and calculation are the tools that will fight inflation, and the extra advantages of AR make it a critical piece of the puzzle.

A robust strategy for present and future
Fighting inflation and, indeed, staying afloat while the markets demonstrate significant turbulence means delivering better value to customers. A business backed by algorithmic retailing techniques can access that value more easily and with more agility than those entirely reliant on the human factor, making fewer costly mistakes thanks to a robust ability to test and refine strategic shifts before they are implemented. Without the aid of algorithmic AI, revising pricing strategies is a resource-heavy task that’s fraught with risk; with AR on board, it’s a straightforward procedure.

Once the current inflation crisis has subsided, retailers that have retooled and refocused their strategic outlook will emerge healthier than ever, ready to form new strategies and make the most of a healthier market. And if the graph happens to spike once more, they’ll be well placed to keep costs low where it counts and drive competitive advantage.

For a list of the sources used in this article, please contact the editor.

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Edward Betts is General Manager – Retail Lead Europe, Retail Express, a leading provider of merchandising solutions and services for retail, wholesale, and consumer packaged goods (CPG) manufacturers. It uses its deep industry understanding and expertise to provide business solutions that meet the evolving needs of merchandising and category management departments delivering improved productivity and enhanced financial results. Through its AI-powered end-to-end Intelligent Merchandising™ solution, Retail Express addresses the complex problems of advertising, marketing, promotions and pricing in retail, providing one version of the truth across the organization and departments.