In this post, we will share why only using competitor data to inform your pricing strategy is a red herring that will cause more harm than good to your business; and the key to fully optimising the prices of your products online or in your physical stores, is to use competitor data, as one of many data sources to make pricing decisions.
What is a competitor-led pricing strategy?
A competitor-led pricing strategy is where your own prices are dictated by the prices on your competitors’ websites and/or in physical stores. In this strategy, it is common for the market leaders to be used as the benchmark.
The assumption is that these market leaders will likely have the best buying power, and will therefore be able to price most aggressively. It is also often perceived that potential customers will be checking the most well-known websites in the relevant sector, to double check they’re getting a good deal. The assumption here is that if your prices aren’t competitive against these sites, your products simply won’t sell.
A competitor-led pricing strategy is a common starting point for retailers seeking to optimise their pricing. The process usually begins with the retailer themselves eye-balling and recording the price of a set of core products against their main competitors’ websites, and as this starts to become unsustainable, due to the size of the task and ad hoc nature of doing it manually, a third-party specialist in competitor price collection is engaged.
There are a number of options out there, from complicated custom web scraping tools that collect and match prices undetected, to those that extract competitor pricing from online marketplaces such as Google Shopping, Amazon, and eBay. In its rawest form, the data that is provided is the ‘Competitor Site Name’, ‘Competitor Website Link’ (of the matched product), ‘Product ID’ (of your matched product), The ‘Competitor Price’, ‘Currency’ (if applicable), ‘Collection Date/Time’, and ‘Your Price’.
If the data alone is provided, it is then up to the retailer to implement either a manual process (often spreadsheet-based) to act on this information in the form of their own counter price change. Increasingly, the third-party specialist in competitor price collection also supplies repricing software with their offering. Here, the retailer can set certain rules or parameters.
They will need to decide on both minimum margin criteria, and where they wish to be in the marketplace, e.g. the cheapest, middle of the road, or most expensive (premium). The repricing software will then work automatically, so that if a change in your competitors’ prices is witnessed, the software will implement the rule, and update your websites price.
Why you should stop stressing about your competitors’ prices
The real dangers spring from the fact that competitor prices are not an indicator of demand. If you rely solely on competitor data, your prices will not reflect the willingness of the customer to pay a certain price, but rather the minimum margin you’re willing to make. Due to this, following your competitors’ prices, can lead to some harmful impacts to your bottom line.
Only recently, ASOS, a leading online fashion retailer, issued a profit warning that cutting prices to match rivals had led to a negligible increase in sales (that tipping point of taking the margin hit on a product to see volumes soar was far from reached). This sparked a 40% fall in the share price. This highlights that competitor-led pricing is risky and unforgiving.
If you’re a key player in the market, the irony is that your competitors are more than likely collecting prices from you too. If both you and your competitors rely too much on competitor data, you may continually undercut each other until one of you blinks and cannot accept any more margin erosion – a classic race to the bottom.
This is what is also known as a price war, where margins are squeezed and none of the participants win - except the consumer getting the cheap deal. The double irony is that in automated competitor-led pricing, by increasing the price, your competition may also follow you, driving the overall margin you both make upwards rather than down!
Our own analysis at BlackCurve tells us that amongst the competitors of our retail customers, pricing changes occur in batches, normally at repeatable and predictable monthly intervals. In waiting to follow these price changes, you’re missing out on optimisation opportunities throughout the month, and a chance to become the pricing leader.
Furthermore, our analysis shows us that on average there is a 30% overlap in products that our customers sell versus their nearest competitors. This means that a purely competitor- led pricing strategy would perhaps see lots of price changes day on day, week on week or month on month, but the pricing changes would occur only on this smaller 30% of inventory.
This leaves the prices of 70% of the inventory unchanged for an awfully long time. It is in this 70% where you actually have the most opportunity to make money. The decisions to buy these products are not competitor-led, and therefore if you’re not changing the price of these products, how do you know they’re priced optimally?
What are the alternatives to competitor-led pricing?
We’re by no means saying that you should ditch competitor data completely. There will always be a subset of products that you have to absolutely be on the money for. This is typically on branded goods that are widely available, as it doesn’t matter where you buy these products from, they’ll be the same. Something like a can of WD40 or Dyson Vacuum Cleaner come to mind here.
If you only make use of one additional data set on top of competitor prices to support decisions, we strongly recommend the use of sales history data. This is because, on these products, customers vote with their feet, and a small price increase can lead to a massive drop in sales, or worse, you sell too well, having given away margin unnecessarily by pricing them too cheaply. In analysing your sales history, you can spot these signs.
Once you have identified the subset of products that you need to be competitive on, the true price optimisation can begin. Analysing your sales history across your entire product set will help you to identify opportunities to increase or decrease price across all your products. A simplistic pricing approach in the 70% of your inventory that may have remained untouched from a pricing perspective until now, could be to increase the price of high performers and monitor the effects, or decrease the price of low performers.
Beyond that, you can make use of stock level data, website traffic data, weather data, and more, to help identify that pricing sweet spot. People buy from you for a whole number of reasons - not just because you’re the cheapest. Sometimes being the cheapest can actually harm your brand. Customer service, brand recognition, SEO and more, are all drivers of demand, and relatively independent of price. Match a lower priced competitor on products driven by these factors, and you’ve unnecessarily sacrificed margin.
How can I make use of the alternatives?
To simply say, “go away and make use of sales history and more to make pricing decisions” is hard. What website traffic should I take note of, and what website traffic should I ignore? What stock level data is relevant, and what is not relevant? These are perhaps some of the questions that may be springing to mind right now. We know it’s hard, because we’ve spent more than 3 years developing a solution to help you make use of a plethora of data sources to make smarter pricing decisions.
Our Pricing Optimisation Platform for retailers blends the flexibility of a rules-based engine with the power of Artificial Intelligence. On day one of using BlackCurve, we provide a Rules Engine for you to set up your own pricing rules for the products that you know inside out. At the same time, our Analytics module can help support you to determine where you have an opportunity to tweak these pricing rules.
For the products that you would like help in optimising, this is where BlackCurve’s Artificial Intelligence (A.I.) Engine comes in. This module analyses your competitor prices, sales history and more, in real-time, does all the mathematical numbers crunching, and provides suggestions to change price, alongside an explanation of the reason behind the change. The Rules Engine and A.I. Engine can even be set up to run automatically, updating your website prices at an interval of your choosing, so you can sit back and watch the improvements roll in.
Our latest Pricing Study has shown that by adopting Pricing Optimisation Software, customers seen the following results:
- A 10% improvement in sell through. This means that our customers are selling more of their inventory than they had been prior to using BlackCurve. How many of your own lines remain unsold currently throughout the year? Price Optimisation likely holds the answer to moving this stock, and this can sometimes come from a price increase.
- A 12% improvement in revenue as a direct result of margin optimisation and the sale of previously unsold stock.
- Opportunities to increase inventory by over 15%. The automation of pricing decisions frees up time for retailers to think more strategically, and we’ve witnessed our customers being able to widen their product offering on existing lines and/or enter into new categories.
- A 9 times return on investment.
The time has come to stop looking over your shoulder, and stressing about your competitors. Whilst it is important on certain products that you’re on the money and competitive, it is critical to use data sets such as sales history, website traffic and more to make pricing decisions and to avoid harming your business from unnecessary margin reduction.
Analysing these data sets for thousands of products to spot opportunities to change price can be hard, and therefore we recommend Pricing Optimisation software such as BlackCurve, that provides huge scope to make immediate and recurring benefits.