You shouldn’t offer the lowest prices for all the products to entice customers

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It may seem an illogical statement, but I stand by it. When you fight for the customer’s attention every second of the day, you may think that everything is fair in war. However, let’s admit that competing with such giants as Walmart or Amazon price-wise can simply kill you. In most cases, your pocket is not deep enough to handle the battle.

Big names have better chances right from the start. They have more beneficial terms with vendors, more money for marketing, more funding for such incentives as same-day delivery, to name a few. So, no matter how loudly you scream “Love me, buy from me, my prices are the lowest!”, it wouldn’t last long. Just because the market can always offer something cheaper.

But it does not mean that you should give up. There are some pricing strategies to keep attracting customers and selling at the prices which can help you stay afloat and even grow. In this article, I’d like to cover one of the strategies which is powered by the use of machine learning-powered pricing analytics software.




Source: Photo by Artem Beliaikin on Unsplash

Price is something which attracts shoppers in the first place. But, as we’ve established above, it cannot be your sole differentiator. What can you do, then? I’d suggest building your brand and bet on private label items.

Your reputation makes customers choose you over bigger supermarkets, as buyers also look for expertise or advice when they shop. Once you have a solid reputation in the market, you are free to offer products at slightly (or much) higher prices, since buyers would come to you anyway. It works for such categories as beauty items or pet supplies, among many others.

Selling private label products is another direction you can head to. As you might have noticed, the market for private label items is growing (which is a sign of many companies seeing the potential to grow there). In fact, it is expected to reach $220 billion by 2020. Amazon and Walmart, similarly to other market leaders, have been offering such products for years — and are constantly increasing their number.

I hope you would agree that such an approach sounds wise. Once you have defined your key products, you can start answering the following questions. What prices should you apply for every one of these products? How about other items of the assortment? Should they be priced lower or higher? That’s where machine learning kicks in.

Machine algorithms are better to use for two groups of products which can be sold at a higher price:
Exclusive. Here the algorithms will recommend the optimal price which would allow you to maximize revenue.
Items which you share with your rivals, but which are not necessarily cheaper. Usually, buyers would choose to buy such products at your store as they trust you more than your competitor. Here the algorithms will suggest raising prices depending on your brand reception.



In other words, AI-backed pricing allows you to earn money on products which you can surely sell at a higher price. This will let you compensate for the lowest prices for those items which should be the cheapest to persuade customers to buy from you. These are the products which you and your competitors have in common (to price these items, you can stick to competitive price monitoring and rule-based pricing). As a result, you’ll keep your margins, while retaining shoppers.

All in all, I would suggest refraining from selling everything at the lowest price possible. Otherwise, you’ll just burn out really fast and will be forced off the market. Why do that if you can employ machine learning to stay competitive and grow?

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