retail markdown strategy
Portrait of author Tom Summerfield
Tom Summerfield

Customer Development Director (Global)

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How to optimize your retail markdown strategy

By Tom Summerfield on June 18, 2020

As the high street begins to reopen its doors after what feels like a lifetime in lockdown, retail businesses are now faced with some big decisions to make, particularly around stock, pricing and markdowns.

Primark recently admitted that there’s an enormous £1.5 billion worth of unsold stock across its warehouses at the moment, and they’re not alone. In recent months, merchandising teams have had to work harder than ever to try and steady the ship in terms of supply and demand, but not all orders from suppliers could be cancelled in time.

The big question, now, is how do retailers shift all of that excess, terminal stock that has been gathering dust in the warehouse throughout the COVID-19 pandemic? This is the short to medium term battleground for most retail businesses.

Sales bonanzas?

This will no doubt be the go-to solution for many businesses looking to shift terminal stock as quickly as possible. But, is dramatically slashing the prices of those unused spring wardrobe essentials really the best approach to take? While this stock does need selling, it’s imperative for businesses to get rid of this surplus in the most profitable way. To do this, retailers must ensure that the margin lifespan of every single product is maximized, avoiding unnecessary discounting by taking a “right price, first time” approach to their discounting.

Optimizing your markdown strategy

Step forward artificial intelligence (AI), and a data-driven approach to defining your pricing and markdown strategy. Of course, merchandisers, traders and planners making data-driven decisions around pricing strategy is nothing new. But doing this without AI isn’t easy; many teams find themselves entrenched in legacy processes and disparate business systems, with the bulk of their working day spent number-crunching in spreadsheets, relying on time-poor personnel and ‘gut feel.’

This is where AI can play a crucial role in helping to make better, data-driven decisions that drive tangible commercial outcomes. By leveraging data, in any format or structure, from across the entire retail business – whether it’s customer, transactional or website data – AI can forecast the predicted demand of products to a higher degree of accuracy. We call this a Predictive Demand View. With this AI-powered view, you can truly plan for profit and make more informed pricing decisions.

Businesses can utilize AI-driven markdown scenario analysis to identify the optimal pricing for each product. The technology recommends an advisory “perfect price range” on an individual product level, based on a wide range of factors and demand signals that wouldn’t normally be visible. This helps merchandisers with their markdown decision making and ensures that initial markdowns aren’t too severe.

The results can be truly amazing. Our merchandising solution, Inventory Intelligence, was recently utilized by a leading UK multi-channel retailer. By applying AI-powered pricing recommendations to a segment of its inventory across online and in store, the retailer has enjoyed some huge results. Utilizing price range suggestions on just 15% of the stock file, the merchandising team was able to optimize its markdowns to drive a huge saving of $3 million (£2.4 million). To put this into perspective, this figure equates to additional margin worth approximately 1% of the retailer’s overall turnover. Demand Intelligence is also leading to increased team productivity and significant time savings, with AI effectively super-powering the end user’s output.

We’re at a crucial juncture in retail at the moment, and making the right decisions to maximize your business’ profitability has never been more important. Using AI, you can super-charge your merchandising team’s output and make smarter, profit-driving decisions to navigate this important period successfully.

Pricing | Retail

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