Discount pricing strategy: how to prevent overstocks and stay profitable in 2024

The Nature of Overstocks in eCommerce

Imagine this: you’re running a home decor eCommerce operation (replace it with anything sourced from China or just anything seasonal). You placed orders for new collections in 2021 for 2022-2023. People were still in occasional lock downs redecorating their households out of boredom, so you estimated demand and sales on a good, optimistic level.

Then logistics bottlenecks happened. Instead of arriving at the end of 2022, as planned, your order arrived in the middle of 2023. Let’s omit the fact that you’ve spent 3-4 months practically without stock but then in the middle of the year, you suddenly faced an opposite dilemma: your warehouse is full of stuff you have to get rid of faster. Because you already have a new batch arriving in 2 months.

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Why Doesn’t Discount Pricing Strategy Work Anymore?

Logistics bottlenecks

What do you do? Sure enough, you slap an aggressive discount pricing on very seasonal item of your stock knowing full well that even a 70% discount now is better than a 30% discount later when you would also have to carry warehousing costs for the stock that nobody wants.

But guess what? 9/10 of your competitors are facing the same problem.

Because logistic bottlenecks are for everyone. And probably every purchasing manager in the world has read the early post-pandemic signals in the same way: demand is growing; we need more stock.

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Cross-vertical Competition

So, what’s your next step? It feels like you’re cornered, eh? What most of your peers would do is to apply even more aggressive discount pricing with the “spray and pray” mindset (— 'There should be some level where shoppers would be convinced that this is a once-in-a-lifetime chance to purchase a couch/table/bike/lawn-mower').

But here’s the catch: all your competitors do the same, and you all end up in an over-discounting spiral.

Moreover, companies that you don’t consider to be your competitors go down the same path — they offer discounts. You see sales signs everywhere: vacuum cleaners, apparel, tools, gym equipment (yes, that one was also stocked hoping consumers would carry on with exercising at home).

The only vendors who don’t offer discounts are vet clinics — and you know it because the last time you tried to take your dog, adopted during the pandemic, to a vet check, you had to schedule 3 weeks in advance, and the bill was 30% higher.Again, consumers can’t buy everything — even if they want to. So you, the one who sells curtains and bed linen — start competing with DIY, groceries, fashion, and sport sellers for consumers’ attention.

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Economic Slowdown

In addition to the overstocks problem being global, you see very troubling signals from ONS: they say that inflation is slowing down.

But so does the economy. Demand just doesn’t grow. People just don’t want to buy more. They save; they reduce consumption. They are very uncertain about the future, and they don’t want to risk.

Price Elasticity of Demand

Eventually, you look at the numbers, and you have to admit that your products have become less price elastic. Discounts don’t impact sales the same way they used to impact even last year (and you thought that was a tough spot, now it looks like it was heaven!).

What can you do next? You can carry on with your over-discounting strategy, spray and pray, hoping for the best.

Or you can adopt a more strategic approach to discounting and see if you can at least prevent the same scenario from being played over and over again. This strategic approach is called Progressive Discounting price optimisation.

Eventually, you look at the numbers, and you have to admit that your products have become less price elastic. Discounts don’t impact sales the same way they used to impact even last year.

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Progressive Discounting Price Optimisation

Price optimisation is a process where you optimize your prices based on

• historical data and
• your business goals.

If it was not for overstocking, you might have been interested in optimising your prices for higher profit margins. Many Aimondo customers who don’t face overstocks in this life-and-death type of way still use this approach.

Margin-related price optimisation is not that hard actually. All you need to do is monitor your competitors stock and prices. If some of them go out of stock — you instantly increase your prices to match MSRP. You use opportunities. If they increase prices — you follow up.

But what if you want to optimise for sales velocity AND margin?

You can use another strategy that implies gradual progressive discounting. The idea behind it is to do several things:

1. Calculate every product’s price elasticity of demand coefficient. Not theoretical one, but the one it has right now — in the current economic context and given the fact that all sellers have gone crazy with discounts. You can even include weather data in the equation, if you want.
2. Calculate optimal selling price for the product at every single point of time, including discounted price, when do you have to start offering a discount, what discount do you have to offer, how to increase your discount, etc. All this to help you exit stock at a predictable pace.

Progressive discounting price optimisation is a pricing strategy created especially for real-time market conditions where you calculate the current price elasticity of demand coefficient and the optimal selling price at every single point in time, considering that it may change within days or even hours.

Dynamic Price Optimisation for Progressive Discounting

Sounds like a fabulous plan, right?

As a Pricing/eCommerce Manager, you know how to perform all these calculations. Good old Excel spreadsheets to the rescue! You throw in the historical sales data set, build a linear regression model, and easily calculate your Price Elasticity of Demand (PED). Now, you can predict your sales using this data-driven approach and can easily calculate how a new discount level will impact your turnover velocity…

It’s a beautiful scenario. And it might work. If only consumer behavior, market context, competitors' behavior, and all other factors were static. You could use them once to build a prediction and run with these results for at least 12 months.

Unfortunately, this is not a realistic scenario. You know well that market conditions change dynamically every month and week, if not every day. Wilco stores have closed—a threat to jobs but an opportunity for other sellers. Ocado has launched a Price Match program—an opportunity for consumers but increased competition for medium-priced grocery stores.

To adapt to these changes, you have to adjust your predictions dynamically. This will help you optimise prices and offer gradual discounts based NOT on assumptions you had 12 months ago but on the insights you have today.

Wilco stores have closed—a threat to jobs but an opportunity for other sellers. Ocado has launched a Price Match program—an opportunity for consumers but increased competition for medium-priced grocery stores. To adapt to these changes, you have to adjust your predictions dynamically.

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If you operate a B2B business or a very small eCommerce store this is still doable using Excel. But if you have a catalogue that consists of more than 1000 items you have no other way out than to use a special tool for that.

Not necessarily Aimondo. We have several amazing competitors who do a great job in predictive analytic and price optimisation — Pricefx , 7Learnings and others. They are very good. Probably, the best. However, Aimondo Progressive Price Optimisation module has been developed specifically to serve the needs of medium-sized eCommerce players. We don't cater to banks. Or to travel platforms. We focus our efforts on building the best solution for eCommerce to help companies avoid overstocks and get their sales velocity under control. That was lost because discounting price strategy is very different in 2023 than it was even in 2021.

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