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Best Practices and Trends
August 7, 2018
The New KPIs of Retail - Part I
How is your economy doing? Seems to be a pretty straight forward question, right? Well, of course, that depends on how you choose to measure it, based in part on your own situation. For example, if you're a US citizen and own a lot of stock, as the Dow is over 25k now, your sentiment might be more positive. If you don’t, it might not be as positive, as wages after adjusting for inflation have remained flat for quite some time.
If you were asked to select 10 KPIs to quantify an answer to how your nation is doing, what would they be? Perhaps some financial measures, like GDP, debt, and unemployment rate, for sure. Maybe something pertaining to quality-of-life indicators like life expectancy, upward mobility, crime, and healthcare. Some might argue for including KPIs for carbon emissions or immigration rates, so there can be many different perspectives on KPIs.
Measurement Doesn't Directly Imply Management
Individuals, and groups of individuals, see things through their own unique lenses, reflecting their values, their circumstances and their views. Similarly, the KPIs that a retailer chooses for their balanced scorecards reflects their corporate values and identity - and how they hope to refine that identity going forward through clearly defined goals and objectives.
The age old saying, you can’t manage what you don’t measure, doesn't go far enough in modern retail. Most retailers measure hundreds, if not thousands of performance indicators, but simply measuring liberally doesn’t imply managing, let alone managing optimally. Worse, as the business of retail continues to rapidly evolve, retailers often struggle to modernize not only what they measure, but also how they manage what they measure.
So in this retail blog series, I will focus on essentially two sides of the retail metrics coin – measuring and managing.
Now, keep in mind the difference between “leading” and “lagging” performance indicators, and that with a balanced scorecard approach to performance management, the former measures progress toward achieving strategic goals, while the latter helps explain the factors that underpin the former.
For example:
That said, far too often, complex reporting gives only the illusion of managed retail intelligence. Wow, look at all those numbers and charts! But yesterday’s KPIs aren’t modernized for today’s business realities. Lagging indicators are confused for leading indicators of performance, or they’re not associated properly with business objectives. Complicating these challenges are several game-changing trends in the retail analytics space.
Trends in Retail Analytics:
- The obsolescence of channels. Today’s retail experience is no longer about channels, it’s about customer journeys. For example, measuring store traffic and associated sales conversion in isolation to other customer touchpoints like social media, ecommerce and call centers implies that today’s retail customer experience is not as nuanced as it is. The often-referenced BOPIS (Buy Online Pickup In Store) is only one of many dozens of potential journeys that should be measured, with a direct line-of-sight through relevant KPIs, objectives, initiatives and strategic goals. But there are many other journeys, for example BCMPS (Buy from Call Center via Mobile Pickup in Store) or BMKW (Buy from Mobile Pickup in Warehouse).
- Rising consumer empowerment. An imperative in the age of the discriminating and smart-phone-wielding consumer is a deep understanding of what drives their behaviors and how to exploit that through more personalized shopping experiences, targeted assortments, offers, etc. These behaviors shouldn’t be limited to what they’re doing (their shopping habits), they should also include what they are saying (social media, contact centers, etc.). The age-old mantra “The customer is king!” is truer today than ever.
- Ubiquitous machine learning based on big data. Eclipsing the basing of decisions on groups of like stores, retailers today are basing more decisions on groups of like customers. I’m not talking about just grouping customers by demographics, or by past sales histories – who your customers are and what they’ve historically done is more informative when combined with what your customers are saying and what data science predicts they’ll do next.
Using Recency/Frequency/Monetary (RFM) Scores
To illustrate this, while many retailers might have historically scored their performance with a focus on Comparable Store YOY Sales, a more meaningful approach today might be a mash-up of sales performance by journey, segment, and Recency/Frequency/Monetary (RFM) scores. Below is an image pulled from the Oracle Retail Insights solution to measure customer journeys and RFM. For example, a wider bar in green indicates high RFM for both fast fashionistas and affluent youth segments.
Measuring Customer Journeys and RFM for Fast Fashionistas and Affluent Youth
So we’re evolving from asking ourselves “how much has each store been selling” to “to what extent are we optimizing the customer journeys that are most potentially profitable for each strategic segment?” Perhaps the former could be considered a leading KPI, but retailers lack critical context without the insights from the latter’s lagging measures.
I’ll close this post by asserting that identifying and deriving the right KPIs to shape a modern retailer’s identity and winning in today’s dynamic retail environment is only half the battle. What good are they if not properly put to use? You have to manage what you measure – that’s right, the other side of the coin that I spoke of earlier.
Want more? Continue reading my next retail KPIs Part II blog here, where I cover how Oracle Retail Home can address this.
Learn more about Oracle Retail Insights Suite, Merchandising Insights, Customer Insights and see why Gap Inc. has leveraged Insights.
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Amazing article how modern KPIs impact business rather than traditional KPIs