Retail pricing is risky business. Price products too high, and customers are happy to take their money elsewhere. Price too low, and the product loses its value and struggles with brand degradation. It can be tough to find the sweet spot between padding the bottom line and enticing consumers to purchase your product. Retailers that have found middle ground are using automated pricing intelligence, paired with a competitive strategy.
What is Pricing Intelligence and Why Does it Matter?
Pricing intelligence consists of tracking, monitoring and analyzing pricing data to understand the market and make educated pricing changes at speed and scale. Because product pricing changes often, retailers need to constantly monitor their relative price position and incorporate changes within a dynamic strategy. However, this doesn’t mean lowering the price just because a competitor does.
So, what’s the point? With the right insight into which competitive products are selling at a premium price, retailers can act in near real time with discounts, “buy one, get one” deals and similar offers that get consumers excited, or thinking about making the switch from a competitor.
There are three main steps when it comes to pricing intelligence; following them can help retailers set themselves up for long-term growth.
Step No. 1: Use Automation
In the current unified commerce era, retailers and brands need ultimate visibility into their competitive landscape.
The traditional model of monitoring for price changes manually is inefficient, time consuming and often inaccurate. Not to mention, the vast amount of existing data makes it difficult to scale. Often, there are too many SKUs to check, and by the time a manual review has occurred, the landscape has changed yet again.
Data collection also needs to be scalable. As a company grows, so too do its number of SKUs, channels and competitors to monitor. This is where automation comes in handy, as the retailer won’t have to repeat those time-consuming and slow processes over again.
Price monitoring in the modern era means using algorithms to understand which products are the same and similar, even when product titles or images don't match up. Each retailer may have a different website layout, structure and naming convention, but with the help of algorithms, they can get more accurate pricing information across selling channels faster.
Conversely, algorithms aren't perfect. If a website's layout or structure changes and the algorithm can no longer locate the price, then it will have to be rebuilt to function again. This is where it helps to pair technology with a human touch. Retailers should look for partners that offer both robust technical capabilities and white-glove customer support.
By automating competitive pricing analysis, retailers can receive accurate pricing data in a timely manner. This frees up valuable time and resources, eliminates potential human error, and provides relevant and accurate information.
Step No. 2: Create an Effective Pricing Strategy
First and foremost, identify direct competitors in the same category as well as competitors with similar or the same products. It sounds shocking, but many brands and retailers lack visibility into their own markets — i.e., they don’t know who all of their competitors are, what their competing products are, and how their pricing compares.
Second, take a look at historical pricing trends. Over time, retailers can start to see trends and recurring behaviors within their competitor set. How often do competitors have sales and promotions? When do back-to-school promotions typically start? Do prices rise or fall around major shopping holidays? Historical data provides an inside look into the lessons and successes of pricing behaviors. By keeping an eye on market trends and behaviors, retailers can make quicker data-driven decisions and outperform their competitors.
For example, say you’re an emerging clothing brand. Competing with big, established brands, any bit of intel is a big deal for you. You want to know which of your competitors sell basic tanks, when, and with what promotions and shipping options. This creates opportunities for you to offer something similar — or more creative — and try to persuade consumers to make the switch to your brand instead.
Lastly, get ready to analyze the data and make it scalable. Invest in advanced software that will provide clear visuals like graphs and not just Excel spreadsheets filled with numbers. Visualizations are powerful tools for presentations, making complex data actionable for the business user.
Step No. 3: Take Action
Pricing intelligence is nothing without immediate action. However, time and again, retailers collect and analyze all of this pricing data, and then let it sit and build up over time. Data that sits with no corresponding plan of action quickly becomes irrelevant.
If a retailer collects a heap of data about the price of ski jackets in December, but analysts review the data in May, it’s way too late. Not only are the prices irrelevant five months later, but who’s buying ski jackets in the middle of spring? Retailers need to act on data as the market changes, not six months later. When a retailer notices a spike in ski jacket sales in December, it needs to react at that time, whether it’s creating its own sale or sending out promo deals and coupons. The benefits of acting on more accurate data faster can mean a spike in sales and acquiring new customers.
Retailers, it’s time to implement a dynamic pricing strategy that has the ability to shift based on the latest and greatest competitor insights. Use pricing intelligence to manage your relative price position in the competitive landscape, anticipate margin pressures, and boost revenue at the category level. If you don’t, it’s certain your competitor will.
Andy Ballard is the CEO at Wiser, a company that collects and analyzes online and offline data with unmatched speed, scale and accuracy for brands, retailers and more. Follow @wiserdata.
Related story: Why Online Retailers Should Reprice Within Reason
Andy Ballard is the CEO at Wiser. Wiser collects and analyzes online and offline data with unmatched speed, scale and accuracy for brands, retailers and more. Follow @wiserdata.