Written by Tony Loxton
Imagine you’re a golfer. Every week you play a round of 18, with the goal of improving your handicap. How will you know if you’re improving if you don’t keep track of your score? You won’t. To improve, you need metrics by which to track your progress. This concept doesn’t only apply to sport, but to the retail industry as well.
“But we do track our performance! We have all our yearly sales data!” is what most retailers will say. While there’s no doubt that sales numbers are important to an organisation, Seth Godin highlights a problem that many companies (including retailers) fail to recognise when they focus on only one metric:
Measurement is fabulous. Unless you're busy measuring what's easy to measure as opposed to what's important.
Seth Godin, Measuring without Measuring
For those of you unfamiliar with Seth’s work, he is an entrepreneur, best-selling author, and speaker who is known across the world for his books on business, marketing and personal growth. In his blog post, Measuring without Measuring, Seth explores how companies pick a specific metric (which is often the low-hanging fruit when it comes to measuring statistics) to the detriment of other important factors that might be a bit harder to track. He highlights this in an example of the security systems banks use to prevent fraud:
Simple example: I regularly get an automated phone call from the bank with an urgent warning. But even when I answer the phone, the system doesn't let me ring through to an operator. Instead, I have to write every detail down, then call, wait on hold, prove it's me, type in all the information, and THEN explain to them that in fact, the charge was mine.
And this department has no incentive to fix this interaction, because 'annoying' is not a metric that the bosses have decided to measure. Someone is busy watching one number, but it's the wrong one.
In the example above, Seth discusses how banks may be reducing fraud and fraud-related costs with these spot checks, they aren’t looking at another critical factor: customer satisfaction. This highlights how companies are so focused on achieving goals around a specific metric, that they fail to understand the greater context.
In his book, Conversion: The Last Great Retail Metric, Mark Ryski also explores the idea that many companies use specific metrics without understanding their context. In a section of the book titled Improving your average, he refers to an analogy by Paco Underhill in Why We Buy on batting average in baseball. Batting average is seen as a critical indicator of a batter's performance, but not how he achieved it – the context of the number, whether he achieved it from 100 or 1000 at bats, is ignored.
Ryski goes on to discuss how, in the context of retail, he prefers to refer to the "batting average" as performance versus opportunity. Traffic equates to sales opportunities for retailers, while customer conversion is their performance relative to their sales opportunities.
In the following section of the book called The Framework, he highlights another critical factor that many retailers often don't take into account: sales performance is relative. A store that only has 500 customers per day is going to have lower sales number than a store with 1500 customers per day, but many retailers are so focused on the sales numbers they forget to take this into account.
For a retailer to truly understand their sales performance, they can calculate it with this simple formula:
Prospect Traffic x Conversion Rate % x Average Sale = Sales
Or more simply put, the number of people entering your store, multiplied by the percentage of people that are buying, multiplied by the average amount they spent on a sale. This simple formula covers all the critical information a retailer needs, but is largely ignored simply because retailers don't have traffic and conversion data.
For example, one store might only have sales of $2500 dollars per week, compared to another store that has sales of $5000 per week. At first glance, it would seem obvious that one store is outperforming the other. But once you look deeper at the traffic and conversion rates, a more accurate but complex picture develops.
The store bringing in $2500 dollars per week processes 50 transactions on average, with an ATV of $50. This store has traffic of 750 customers per week, indicating a conversion rate of 15%. Then you have the store that brings in $5000 per week. This store processes 100 transactions on average, also with an ATV of $50. However this store has traffic of 1750 customers per week, indicating a conversion rate of 5.72%.
What appeared simple immediately becomes a lot more complicated. While one store appears to be earning less money on a weekly basis, they are converting a much higher percentage of customers than the store that is bringing in a larger amount of money every week. Further investigation into this could reveal the causes of this difference, such as demotivated staff, poor management or increased competition. But this would likely go unnoticed by most retailers, who when tallying up the sales numbers for each store for the week, would pat the higher-earning store on the back and say "well done, carry on".
For retailers to truly maximise the potential of each store, it is vital that they take advantage of the right metrics.
If you’re a retailer and are interested in growing your understanding of traffic and conversion, Blix offers a complete foot traffic and analytics solution. To find out more about our product or to get in touch with one of our staff, get in touch today.
In chapter 1.1 of his book Conversion: The Last Great Retail Metric, Mark Ryski..