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Pricing in a Pandemic

Updated: Jun 3, 2020

Where do we go from here, and how can technology help?


It’s a time of year retailers usually look forward to: the weather shifts, a long weekend arrives, and Britons turn their attention to spring styles fit for special events. But this year is different. We’re staying at home and we're barely wearing the trousers we already own. As one high street clothing supplier put it: the 2020 “spring/ summer season has been cancelled”.

Fashion and seasonal retailers are evaluating their options – they’re cancelling orders, packing away landed inventory, and bracing for an unprecedented summer sale season.

At Sparkbox, we’re focused on helping our clients make data-driven decisions during these uncertain times. As stores reopen and demand shifts, it’s impossible for merchandising teams to predict what might happen next. We’re using our underlying forecasting technology to model scenarios and anticipate sales by region and channel as the pandemic unfolds.

Today we’re sharing some of our suggestions for pricing in a pandemic, which we hope will be helpful to our retail friends and colleagues as we start to think about emerging from this crisis.

1. Protect your customer

At this time especially, customer needs must inform business decisions. In recent weeks, we’ve seen great examples of retailers working hard to secure supply and deliver food and essentials at a fair price. This isn’t the time for profiteering, it’s the time to build trust by doing the right thing.

2. Cash is king

Focus should now be on converting inventory to cash as quickly as possible. This will be a difficult shift for merchandising teams who are historically goaled on margin. Some great but seasonal product will need to be discounted deeply, and those tough decisions should be made as quickly as possible. Retailers that emerge successfully from this will have prioritised cash generation and returning to seasonally relevant assortments quickly.

3. Don’t race

Except in the provision of essentials, don’t waste time and resources trying to match or follow competitor’s pricing activities. Focus on your own business and on mitigating your own stock risks. More than ever, you don’t know what level of inventory your competitors are trying to clear, so don’t follow them in a price race to the bottom.

4. Avoid guess work

Even under normal trading circumstances, it’s incredibly difficult for humans to process historical data and predict future sales trends. New technology can help – and it’s quicker and easier to deploy than you might think.

Machine learning is good at estimating demand because it can quickly crunch large data sets to understand how customers respond to changes in variables like store openings, stock levels, and promotions. Forecasts generated by machine learning models can be used to evaluate scenarios, allocate inventory regionally, and inform orders and cancellations.

In the coming months, retailers will need to clear lingering inventory while maximising margin on patchy new season stock. Sparkbox can be set up remotely in just a couple of weeks, reacts quickly to trading trends, and provides merchandising insights and advanced visibility to risks.

5. Find the silver lining

In every crisis, there are opportunities. Promotional strategies must usually consider margin goals and long-term impact to customer price perception, but this pandemic presents a chance to clear stock in “one time” offers. Customers will understand there’s good reason for special sales at this time, and these can be used to reset inventory positions without impacting customer expectations for the long term.

Forecasting technology that can inform pricing, promotion, and merchandising decisions now will continue to add value well after the pandemic is over. Going forward, retailers will seek to be leaner than ever, and data-driven merchandising will play a key role in maximising profitability while minimising inventory.


If you have any questions or if we can help with anything at this time, please reach out to our team at

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