How do you define Big Data in grocery from your perspective?
We start by defining data from a Customer perspective – put most simply, it’s about everything a Customer does in any typical digital day. Data is created by Customers from the first log-in of their morning to check email or Facebook or to download the newspaper, then throughout the day as people make phone calls or surf the web, and, of course as they shop online or in a physical store. Our smart phone and our automobile each track its own path and position, creating even more data. At each activity, Customer data is being stored or collected.
The classical definition of Big Data, per Gartner and IBM, starts by describing its volume and velocity (and adds other ‘v’ qualities like variety, veracity, and variability) – and by this definition, grocers certainly generate a tremendous amount of big data. For us, the most important data is about its ‘C’ qualities – Customers (who individually control the data), Connected (from many sources in a whole person view), and Conversation (with Customers in a way that demonstrates a retailer’s loyalty to them).
For grocers, the ‘original’ context of Big Data was the transaction logs enabled by checkout scanners – and grocers have been using some of this voluminous and fast data for a many years (at least since the 1980’s) in the form of category management or logistics decision systems. The emergence of cheap(er) data storage solutions and the corollary introduction of loyalty cards in the 1990’s enabled grocers large and small to link transaction log data to individual Customers or households – the data then did not get any ‘bigger’ really, but it did get more collectable and more personal.
It’s these concepts of collectable and personal that make Big Data so big today, and its understanding and use so hopeful and frightening at the same time. Data is collected and stored about everything a person does in every typical digital day.
What kinds of Big Data do small-to mid-sized grocers have available to them?
We think that asking what a grocer might do with their available data is asking the wrong first question – the real power of Big Data comes from starting not with the data, but with a more strategic question like “what insights do we need in order to improve the Customer experience, and what data would best give us those insights?”
From these strategic questions, grocers can define all of the data and the technology they need to deliver a better Customer experience. And this creates the real competitive advantage regardless of size – the right slices of data (big and small), clear insight from the right analysis, and action that changes the experience in store for the better.
Most small and mid-sized retailers already have a strong start toward answering that larger strategic question, provided they employ scanner or electronic till (EPoS) technology, which creates rich database of its own. (EPoS data is ‘big’ in terms of its volume, variety, and velocity, and it is a ‘structured’ asset because it comes from a single source in a standard format). Transactional EPoS data, even that without ‘personal’ Customer identifiers like loyalty cards and the like, can be mined for insights that improve business decisions and the Customer experience in store. For examples, EPoS data can reveal insights on trip missions and how Customers use the store, as well as to inform pricing, promotions, assortment, adjacency, and macro-space decisions.
The business benefits of unlocking grocery EPoS data insights should not be underestimated: this data is a highly leverageable asset, perhaps not of loyalty ‘gold’ quality, but certainly of other precious mineral value when used to improve the Customer experience.
EPoS data alone, however, cannot be used for personalization of offers or communications nor can it be linked to other Big Data from activities that Customers might do in their typical digital day.
Are these grocers dealing effectively with this Big Data – that is, is it an advantage to their business?
Unfortunately, we see very few grocers of any size effectively using data in most any form, much less Big Data. It is estimated that less than 20% of data that retail organizations already have is effectively understood or utilized, and most of what is used is around the supply chain. So, applying insights from data toward improving the Customer is extremely rare – that’s why there is so little loyalty in spite of so many loyalty card programs.
Those few grocers who are effectively applying insights from Big Data – and there are some strong examples among small and mid-sized companies – are creating better value for their Customers and stronger relative financial results. The evidence is very clear that Customer data-led decisions and practical actions that are felt in the store increase competitive advantage and improve business results, particularly when the right kind of organizational change has been instigated to sustain a Customer-based culture.
If not, why not? What has to be done to make it an advantage?
Customers’ lives have been transformed by technology. Shopping trips are more complex, diverse, and unpredictable – certainly no longer in a straight line from home to store and back again. Out of a kind of fatigue born out of sameness of offerings and just sheer volume of marketing, Customers are tuning out of retailers’ messages, both consciously and unconsciously. Grocers must face into the truth that “we don’t know what we don’t know” in this new retail world of the digitally-connected consumer, distracted and disloyal.
To survive, grocers must understand what drives loyalty and what creates experiences and propositions that matter to Customers. And Customers are telling us what is important to them via the data – if we can but connect the many sources of ‘big data’ to understand what they need, deliver the right actions to improve their shopping experience, and have the proper personalized conversations to let them know that we care.
The first step is to ask the right questions like “what insights do we need in order to improve the Customer experience, and what data would best give us those insights?” As a second step, I believe (and it is my own experience) that grocers need the help of expert guides to optimize the data assets they currently have and to help harvest the other data assets that they need (retail organizations are not engineered to this well internally). Thirdly, get expert support to conduct the right, efficient analyses that deliver simple, practical, and actionable insights. Next, teach the organization a Customer language so that the insights are executed with understanding and commitment. And finally, change the culture as necessary to sustain the changes in the Customer experience in store
Raley’s in Northern California is focused on creating a World Class Customer experience; they have started this journey by understanding their Customers better than anyone using their own transactional and shopper card data, and by connecting this with Customer comments, and even by listening to their Customers on a social media platform. Raley’s uses Big Data insights to inform and help their Great People Who Care, and to make Customer-led decisions in marketing and category management.
(A portion of this discussion was printed in “The Little Book of BIG DATA”, published by the Shopper Technology Institute, 2016., p. 5)