Source: Best Buy
Best Buy and others find great customer experiences start with data insights
Retailers have long been emphatic about how necessary data collection is. How that’s achieved, however, along with what data gets prioritized and how that affects the customer experience were frequently missing from public-facing presentations.
It’s safe to say that retailers are now open and able to communicate all the above and the “Building Better CX Through Data-Driven Insights” session at Shoptalk 2022 was a testament to just that.
Barkha Saxena, chief data officer at Poshmark, highlighted during the session her company’s data-driven culture where the expectation is that no decision will be made without supporting data.
Ms. Saxena oversees a long list of data-related priorities, including analytics, machine learning, data engineering and data tools. Customer, seller and industry inputs are leveraged to optimize and elevate the interactions both shoppers and sellers experience. Every shopper is served a different product discovery feed based on that combination of data so that the content is both personalized and relevant. On the seller side, data also powers the impact of the experience, by way of the “my shoppers” insights tool.
Jim Ferolo, chief information officer of Maui Jim, spoke to the business challenges the brand has overcome thanks to differentiated thinking with respect to data.
Many of Maui Jim’s recent data-driven successes were the result of prioritizing the information needed by account executives. Near real-time data accessibility has been crucial. Getting executives inventory information practically on-demand, refreshed every two hours (reduced from 12-14 hours) and providing business visibility on their phones has eliminated significant bottlenecks in their model.
Jennie Weber, SVP of experience design & insights at Best Buy, shared that the retailer’s shopper insights continue to validate the frequently asserted hypothesis that consumers often begin their path to purchase by researching online before moving to brick and mortar to trial products and buy.
Ms. Weber uniquely highlighted the importance of employing qualitative data to “provide the color context” to a conventionally quantitative space. She said that it is still challenging to “piece together from a data perspective” how shoppers are bouncing back and forth between channels. This data is equally valuable to employees at headquarters and associates in stores.
Best Buy’s strategy, much like Poshmark and Maui Jim, is founded upon the belief that socializing the right buyer data across as many teams as possible is the key to continually improving the customer experience.
Discussion Questions
DISCUSSION QUESTIONS: Are there cases in 2022 where a retailer shouldn’t have a “data-driven culture”? How important do you consider qualitative data when designing the customer experience and how is it best employed?
Poll
Loading …BrainTrust
Ken Morris
Managing Partner Cambridge Retail Advisors
Evan Snively
Director of Planning & Loyalty, Moosylvania
It would be hard to argue against the value and importance of having a data-driven culture. However increasingly the hard part is figuring out how to prioritize which data are most important. Retailers need to be clear about which data is most critical to driving their operations – more data is not necessarily better. And I agree, qualitative data still has an important role to play in contextualizing results. For example, social media reviews can help identify in-store conversion barriers than can then be further explored/validated.
It is critical to align qualitative data with quantitative data. Without integrating both, you will not get the whole picture of your shopper. Sounds easy, but many are not doing this, or at least not as well as they could and should.
A data-driven culture is evolving into retail table stakes.
Companies are juggling too many complex market factors to base decisions on guesswork rather than facts. Data makes retail execution more accurate and efficient, helping retailers continuously improve the customer experience.
We always hear about the importance of knowing your numbers, so Best Buy’s attention to qualitative data stood out. Qualitative data can be a goldmine, as open-ended feedback on product reviews and consumer sentiment can help to explain the metrics.
Data-driven culture vs. data-driven business? Yes, perhaps this is semantics, but the customer almost never wants to feel like they are part of a database. Culture is certainly part of the shopper’s experience and selection process. But leave the wonks in the backroom, and build a culture that fits the needs of the “tribe” your store is serving.
Dion, very well said.
It would be interesting to know if all of the data that is now available is helping retailers build relationships with customers that are more efficient. Meaning — in the old days customers shopped only what they could literally see, feel, touch, listen to, etc. (Not including catalogs of course.) Now they can shop extensively online at home or in the store with their phone. What does the retailer now know about the shopping and editing and final purchase decision that they didn’t know before? Does all this data mean that customers buy more, more often, over time because the retailer is so much smarter than before? Do the best customers have higher lifetime value because their shopping habits are known so much more deeply? Has more choice resulted in more sales per customer? Or do more retailers offering more choices confuse customers and spread their purchases over more outlets and channels? Is there a sales or margin metric that validates an improved customer experience versus smarter content?
Data quality is really determined by sample size. If the sample is too small, the data will be suspect. So, capturing all the data is key. Too many of us make assumptions on partial or bad data, and that leads eventually to sub-optimal performance.
I think a better way to frame this conversation is as a “customer-focused culture” with data providing essential research to best serve the customer. Retailers should use every insight and every IoT data point they can—especially RFID for inventory visibility—to avoid disappointing the customer with stockouts when they’re ready to buy.
Feeding key customer insights to employees on the sales floor only helps the cause if it doesn’t interrupt the flow of the interaction with the customer. That’s when distilling petabytes of data into simple screens becomes essential.
I think most retail watchers would say that a data-driven culture is table stakes yet a conversation I had just this week challenges that assumption. A tension between data-driven and technology-driven cultures has arisen within some retailer organizations. One would think that they go hand-in-hand yet prioritization can make all the difference. Hiring decisions are often based on skills and experience with data or technology, accelerating the culture clash. The focus on data sharing is on point, yet casting a corporate vision for how data and technology will interact may be even more important.
I feel like this is a bit of a Joe Science Award-worthy revelation. But it’s true that getting good, quantitative data – that is meaningful, an important distinction – about the customer experience is very difficult. And this is doubly true of the customer experience in the store. While it’s true that retailers can be more data-driven than they are about this, and that is easier to achieve today than it was five, 10, or 20 years ago, retailers need to be careful that they don’t mistake data gathered about the digital part of the customer experience (which is rich and plentiful) as something representative of the entire customer experience which leverages the store a LOT. You can only analyze what you measure, and if you are unable to measure a large part of the customer experience, for whatever reason, you’re going to make potentially huge mistakes in your conclusions.
One of the very few instances where data may not be as vital to an operation is in how to address customers before, during and after a sale. My favorite QSR comes to mind, Chick-fil-A, with their incredibly friendly associates who always respond to a thank you with “my pleasure.” Don’t get me wrong, I’m sure CFA is using data to justify, tweak and enhance certain aspects of their customer interaction training, but you don’t need data to teach anyone the Golden Rule. That said, companies like Best Buy, Maui Jim and Poshmark are good examples of companies moving up the analytics maturity curve, where context about what the data says is as or more important than the data itself. Moreover, having the analytic capability to stitch together the customer journey from offline to online to app, back to offline and yet again to app, can unveil nuances about customer purchase intent, habits and truths that lead to changes in assortments, pricing and inventory. These capabilities are found in data driven companies and they are seeing tremendous insights pop into every corner of their business.
Data-driven vs. Consumer data-driven is the big difference in usefulness. Numbers alone are not sufficient, albeit necessary. Understanding the consumer experience comes from hearing what the shopper has to say and how they feel and what motivates them. That’s where qualitative data (well executed) comes in. I can’t imagine any retailer being successful without the use of at least “some” data.
Saying you are a data-driven culture and actually being able to discern meaningful insight from that vast collection of customer touchpoints often falls flat. Meshing first-party data with larger trends uncovered from third-party sources is an area where I have seen companies fail. They get too in the weeds with their brand experience and lose sight of how those behaviors fit into the bigger consumer ecosystem.
Also, companies who are trying to be truly innovative might have some supporting data, but likely will need to take a leap of faith that their product can shape future behavior. Not everything in business can be a “sure thing,” but that is where the excitement lies.
There is no either/or anymore – all of retail is already a data-driven culture in 2022. The key – and this has been true throughout the history of business – is to pair objective, quantifiable results with human insights, intentions, and creative vision. Those things do not appear on an information officer’s spreadsheet. The customer experience is just as fueled by the humanity emanating from a brand as by the patterns and success of its processes.
I believe in data, and I applaud the descriptions of use in the discussion. It is good to see retailers buying into it. But hopefully, it doesn’t replace human input and becomes a crutch for making decisions.
Data can provide incredible insights that help a retailer understand what their customer wants and more. That can make customers feel like a retailer always has what they want, which is a form of personalization. That’s different than building a relationship that creates true loyalty. For that to happen, there needs to be an emotional connection. Data gets you so far, but your people do the rest.
Without question there is NO situation where a retailer should embark on a strategy, decide on a location or create a customer engagement strategy with out using data to inform those decisions.
What data should be used is another question. I believe that depends on the retailer, the product and their value proposition in the market. A luxury retailer who is focused on rich customer experiences and providing top end customer service, is going to have different data requirements than a convenience store looking to manage availability and drive loyalty. Retailers need to start with the customers, understand how they want to engage the customer, and then identify the data they need to deliver that strategy. This isn’t a cookie cutter situation at all.
I’m not familiar with cases where data cannot be useful. Data allows retailers to know when they reach an objective or show progress towards one. Without data any improvements are just plain luck and more importantly can probably not be repeated. Qualitative data is just as important and there has to be a balance. An over-reliance on one or the other tends to open gaps where the data is not relevant and poor decisions are made based on it (whether it’s quantitative or qualitative).
This is an example of the retail mantra, “know your customer” in sign technology. We can expect the use of technology that provides customer insights to continue to grow.
While this type of data has been available for years, many chains did not have the wherewithal, desire or skills to utilize it to their advantage. It is indeed a science that can be applied to human-to-human interactions in stores.
This was a key theme at the recent VP IT meeting. Retailers are overhauling the ways they interact with customers and conduct sales outreach; the retailers leveraging data the best are flying forward.
A data-driven approach to customer-focused problems is an absolute must. Data about customers, locations, online and in-store behavior as well as the data from new digital channels such as communities and sample programs. The key is for the retailers to be purposeful with this data to ensure that the teams are solving the most important problems and also respecting the privacy/personalization expectations of customers. Additionally, what plans are in place to collect and harmonize this data to make it trustworthy so all team members are using a single source of truth and drive data-driven decision-making?
It was an astute observation that there were not a lot of discussions about qualitative data, but understanding how your product is used by consumers can give you a leg up in closing experiential gaps as well as fuel new product development. Best Buy, unlike many other retailers, is frequently in people’s homes with the geek squad and also sells oftentimes very complex products so ethnographic studies appear to be well suited to them — but — the type of qualitative study really depends on category/retailer.
I don’t believe there are any situations in which a data-driven culture would not be helpful. However it is critical to ensure that an organization’s business decisions are not simply based on data; the human factor is still necessary here. Because data cannot be completely accurate, the insights are not completely reliable. The consequences of a bad decision (based on faulty insights) may not be apparent in the short term, but they could have severe consequences for the business in the long run. When it comes to qualitative data, an organization will need a lot of resources and specialization to effectively obtain and apply qualitative insights. Few organizations are capable of doing so.
Retail has for a long time been a blend of art and science but as more data becomes available, the tilt toward science becomes stronger. There are few areas where data cannot be used to improve things — but the difficulty is ensuring the data is correct and appropriate. An additional difficulty could be faith and user adoption.
The difficulty using data for experience design can be the 20% of cases, situations or customers that the data does not represent. These can be somewhat frustrating for customers. In addition, the impact of Survivorship Bias (where data collection is not possible because the customer chooses not to interact with the retailer) can be problematic. Avoiding this is an absolute must and approaches need to consider this.