Brick-and-mortar retailers have a long legacy of product-centric marketing and driving traffic to a location. Big box retail stores were built on reaching the masses through broadcast media.

Customer journey marketing and personalization is built upon marketing to the “unit of one” — the individual. Instead of frequency and reach of mass media, retailers now need to focus on collecting individual customer data across time and place. That requires Big Data and analytics that most legacy systems were never designed to analyze. It also requires investments that stretch many retailers’ capital and budgets.

However in the age of omnichannel consumer behavior, CRM trumps market segmentation.

One of the keys here is to focus specifically on the unique characteristics of store engagement technologies. The newest machine learning/A.I. capabilities I’m seeing in the marketplace can drive new insights in store-level shopper journeys, including the pure integration of the digital experience analytics with store data insights. In-store customer experience analytics, predictive customer intelligence and other tools are indeed becoming requirements for marketers and e-commerce to leverage today.

The basic requirement for brick-and-mortar retailers to implement these tools is to know who the customer is. E-commerce retailers have this information by default. The Costcos of the industry know this because of the membership model. Once the traditional retailer can identify each customer, it knows who bought what on what day and time and with what other items, and can then put these tools to work for them just like e-tailers and Costco.

As it relates to analytics and the use of new insights based on data, I think the key challenge is the operationalization of insight and the adoption by business stakeholders who are aligned with the different stages of the shopping journey. In my experience data science and analytics teams need better ways to activate their work. Ensuring consumers experience the value of analytics at the physical store level first requires that employees who have those face-to-face interactions leverage new insights as part of their day-to-day work. Making the use of analytics as transparent as possible — to either people or systems — is where I think brick-and-mortar retailers should focus their attention. In many cases this is simply too hard, costly and impractical for many retailers struggling with slow to no growth and slim margins who at the same time are pressured to test, experiment and transform their businesses while forces like Amazon continue to disrupt the retail industry. There’s no better argument in my view for adopting cloud solutions enabled with the kind of… Read more »

Various innovative technologies are available in the market to enable brick-and-mortar retailers to integrate shopper analytics, map customer journey, measure conversion rates, allow “infinite shelf” and personalize in-store interactions. Adopting and implementing these technologies in a physical environment is more challenging than online. One of the main barriers is identifying the shoppers. To do that shoppers must agree to be identified and the retailers need to give a good answer to the question, why should the shopper agree — what’s in it for him?

I’m going to jump in here and take a slightly different path. Customer journey is more about mapping out the potential journeys of your brick-and-mortar shoppers and then meeting them at critical touchpoints along the journey to give them what they want. Be it the right interaction or something to ease the process and make the experience more delightful. Although we do have data to personalize, a ME level of personalization is not always needed to move the customer journey along. It is about choosing the data that fits the touchpoint. But that’s just my 2 cents.

To fully integrate analytics to get a better view of consumers, all retailers and manufacturers need to be diligent about understanding their consumers and retailers and manufacturers need to collaborate to identify their joint consumers at every retail location. This is a huge task but the best strategy for successfully selling a manufacturer’s product to the consumers who enter a particular store.

There is a tremendous amount to be learned by modelling typical customer journeys — especially looking for points that stop the journey, divert the shopper or draw their attention to bring them in. But digital experience shows that obsession with customer journey (a tool for maximizing immediate digital sales) tends to build short-term revenue at the expense of long-term strength. Traditional advertising, for example, communicates with three groups: those ready to buy, those who will buy in the next 12 months and those who will buy in the next three years. No amount of online hypertargeting reaches those second two groups — they are not exhibiting behaviors that can meaningfully identify them. We should also remember customer journey modeling has been used for decades of retail research work with in-store customer tracking and other excellent research tools. The only thing new today is adding in big data. But before we expect that adding big data to the mix to make a radicalizing difference, I recall my friend Shahin Khan’s big data observation: That the ratio… Read more »

The first use of analytics I can remember comes from an episode at the very beginning of my early career as a trade journalist. I was in the middle of nowhere in the Tennessee hills talking to an independent operator. It was pouring rain and he said, “well, guess today is Research Day.” I asked him what he meant and he explained, “See when it rains, folks’ shoes get wet and they track that water into the store. I just look at the puddles to see what they’re interested in and when I see a dry spot I know I better change something.” Primitive, but effective. This has nothing to do with “omnichannel thinking” — a retailing oxymoron in my mind. What it does have to do with is the fact that as a cultural anthropologist might note, “Smart animals use tools and the smartest animals use tools better than their peers.” There are a wide variety of new metrics and analytical tools available. The trick is to not fall in love with any one… Read more »

In the last few years, many retailers have taken a more strategic approach to optimizing the shopping experience for their customers. The first step is to embark on a customer journey mapping exercise to understand how customers interact at each touchpoint during the customer journey — when and where do they shop (mobile, online, in-store or catalog), when and where they purchase and where they like to receive their merchandise (in-store or delivered to their home). Once they understand the current and ideal shopping journey for their customers, they are in a much better position to address what they need to do to make this shopping journey, or journeys, seamless, personal and frictionless. The key to the ideal customer journey is personalization. Providing the same experience for all customers is not a differentiator. However, personalizing the experience based on analytics and “customer context” to create a unique, personalized experience for each customer is a differentiator. To provide this experience really requires retailers to embrace real-time retail. Creating a single real-time channel that reacts or flexes… Read more »

I think retailers have a lot to gain by thinking about the total customer journey, for example someone who might browse online but buy in-store or vice-versa, someone who searches for product reviews multiple times or sees an advertisement and researches the product on their mobile.

The store is a great way of marketing the brand and products to customer, engaging with them and offering unique experiences, but it can be difficult to gather the level of data about the customer journey that you can online. But if you have that information about your online customers you can use it to enhance in-store offerings, alongside data that you are able to collect from the physical space. Lots of companies are now tackling the analytics in-store issue so I think retailers are going to have more and more data to work with in the future and that will present opportunities around improving the journey and offering personalisation.

Brick-and-mortar stores actually have more potential data points to pull from than those that are purely online. The data is not only from member data, but foot traffic, camera data, sentiment analysis, etc. Retail executives can borrow a page out of the customer journey play book that e-commerce companies have been using for years and overlay store-generated information over the top.

When the first transactional shopping website went live 20 years ago, the future of retail threatened to become a battleground between bricks and clicks. Today’s reality is very different; the battle cries have been replaced by courtship and now marriage, thanks to consumer behaviour. Shoppers have turned out to be channel agnostic, wanting a frictionless customer experience in which quality, price and service are consistent, whether they shop online, mobile or in-store. To my mind, it makes absolute sense for physical retailers to collaborate with e-tailers to build platforms that combine the strengths of both sets of business processes, resources and skills. Walmart, Tesco, Sainsbury’s, Amazon, Alibaba, to name but a few, have all recognised and acted on this belief. Physical retailers have their established product supply chains, store estates, distribution and logistics, in-store team experience, visual merchandising expertise. E-tailers bring with them cloud-based agility and speed, order fulfillment, digital infrastructure, customer knowledge, personalisation and deep data insights. The challenge for both becomes one of engaging with the right partner(s) and transforming operations by deploying… Read more »

There is tremendous potential for retailers to learn about their customers from their journey through the store. Many retailers I’ve talked to recognize this and are more constrained by the execution or implementation of the technology needed to deliver on this treasure trove of data. After that, the issue becomes who in the organization is best suited to take action on this data. Is it marketing, merchandising, IT, or operations? Or should it be all of the above? Culture tends to take over at this point, and that’s where it all falls down for many retailers today. Legacy processes and silo-ed organizations are often to blame. If we made a list of retailers who are better at this than others we would see that the top of the list consists of younger and/or smaller retailers who haven’t been burdened by their size and age to develop a culture that works against the benefits of data. This is of course counter-intuitive since we would expect larger retailers to have the necessary financial and people resources required… Read more »