Strategic pricing is an underrated element of ecommerce success. You can have class-leading service, exceptional products, and a finely-honed brand identity with various positive qualities — but if you don’t get your pricing right, you’ll have a very difficult time competing. And getting pricing right is far easier said than done. One thing for sure is that having relevant data in hand can help you make better decision in terms of your ecommerce pricing strategy.
Set your prices too low and you’ll fail to achieve the level of profitability you need to keep going, let alone expand, plus you’ll set a dangerous precedent that will make it tricky to raise your prices in the future. Set them too high, though, and you’ll be ignored in favor of cheaper sellers — and just one excessive price can lead someone to assume that you’re always overcharging.
And with the online marketplace being saturated with sellers, it’s hard to get pricing right: but this is where data enters the equation. The more relevant data you can gather, the better you can make your ecommerce pricing strategy. In this piece, we’re going to look at why, so let’s get to it:
It’s helping with contextual pricing
A large supermarket chain can have numerous stores throughout a country, or even overseas, and those stores will typically have prices that differ somewhat due to regional differences in disposable income and commodity costs. Buy a candy bar from a large store in an average town and you’ll pay much less than at a small store from the same chain in an expensive area.
The implications for ecommerce are obvious when it comes to overseas listings, because data about sales in another country will help you effectively tweak your prices — but surely ecommerce stores don’t have regional variations since they’re practically decentralized? Well, you need to factor in hybrid retail, the growing pursuit of merging ecommerce and regular retail.
Online sales systems can hook into in-person sales through tech like Shopify’s hardware POS setup, keeping all the sales and stock counts in line, and this opens up interesting new pricing possibilities. By placing sales data into proper context, you can figure out how best to tweak your prices to suit different environments.
It’s enabling dynamic pricing systems
Manual work is fine, but not ideal when you have a million other things to do, so anything you can automate is going to make your life much easier. What if you could automate your pricing, at least to some extent? Well, you can through the use of dynamic pricing, keeping up with slight changes throughout the online marketplace.
Dynamic pricing systems have been around for quite some time. They monitor merchant listings across the web to trace pricing fluctuations, and adjust your prices accordingly. You can also set specific parameters. For instance, you might want to ensure that your price for a particular item stays within a dollar of the average, or pointedly undercut everyone else to be the cheapest.
There are numerous dynamic pricing systems to be found online, and every CMS with any popularity will have a variety of options compatible with it. Just search for your platform of choice along with “dynamic pricing” and you’ll be able to find something suitable.
It’s making A/B testing more sophisticated
Whether you’re setting prices contextually or using a dynamic pricing engine, you need some way of gauging the efficacy of the changes. When you lower your prices to match your rivals, does it raise your sales as you might expect, or does it damage them? You might discover that reducing your prices actually makes things worse through making your brand seem cheaper.
The point is that you can’t easily anticipate how a particular action will ultimately affect your sales, and you need to carefully track the consequences. Thankfully, the massive rise in cross-system integration options makes it easier than ever before to form comprehensive impressions of what your changes achieve and drill down into specific issues across your organization, systems, channels, and applications.
By paying close attention to this carefully-collected data (filtering out all the junk metrics), you can discover interesting correlations and figure out what — if anything — they mean. You can then use that information to make informed changes and continue the process of iterative improvement that’s so important to continued success in ecommerce.
The existence, collection and analysis of rich ecommerce data is enormously useful for all manner of things, but particularly for pricing strategies. More information is always better, and modern sellers are taking advantage to establish dynamic pricing rules, define astute contextual differences, and test with great breadth and consistency.[vc_column width=”1/4″]
About the Author:
[vc_column width=”3/4″]Rodney Laws is an ecommerce platform specialist and online business consultant. He’s worked in the ecommerce industry for nearly two decades, helping brands big and small achieve their business goals. You can get his advice for free by visiting EcommercePlatforms.io and reading his detailed reviews. For more tips and advice, reach out to Rodney on Twitter @EcomPlatformsio.