The retail industry is undergoing rapid changes, with customer behavior and preferences changing in dynamic and unpredictable ways. Business owners now face numerous questions about what strategic decisions to make with the post-COVID reality in mind. According to Tomasz Woźniak, Future Mind CEO, the best place to look for answers is in customer data – which is why companies should not allow external platforms to keep it hostage.
There is a simple relationship between data and sales: if you want more people to buy more of your products or services, you need to understand what drives them to make purchases. Tracking and analyzing how customers interact with your company will allow you to determine their needs and preferences, and consequently to decide where to focus your marketing efforts and how to develop your offering.
That is not to say all your customers think the same way. The underlying purchase decision mechanisms will usually differ between segments, which is yet another phenomenon that you may discover after you gather enough data. Some types of segmentation like age or gender are obvious, but, in some other cases, the diversity of your customers’ attitudes may surprise you.
Why should you care about customizing your approach? Well, in the words of Tomasz, "imagine marketing to a vegan customer with discounts on pork shoulder." In some cases, failing to adapt your offer to different groups may leave a bad taste in someone's mouth – even if your pork is incredibly delicious. With 80% of consumers claiming that they are more likely to make a purchase if they receive personalized communications, sticking to cookie cutter marketing starts to look more and more like shooting yourself in the foot.
Many retailers decide against tracking their customers either due to a lack of resources or because they simply do not see it as a valuable investment – if you share that belief, we would advise you to reconsider. Some other businesses do make an attempt at gathering customer information. Still, they go in blind: without the right tools and know-how, tracking too few data points, or failing to properly analyze their database and reach useful conclusions.
According to Tomasz, "If you want to do a solid job of customer data management, you need a so-called Customer Data Platform – a system that will allow you to control, process, and, most importantly, analyze all the information you have gathered. That system will only be as good as its data input. If you use multiple sales channels, the quality of customer data may turn out to be quite low. Sometimes, it is better to do less but create connections between all the different data pieces, in contrast to being present everywhere but not knowing anything about your customers".
While some companies are lagging behind, the market is full of data-mature organizations that gather, process, and utilize customer information to improve their business outcomes. In many cases, a sustained investment in analytics allowed those firms to overtake the competition. Not only did they observe and classify their customers, but they could also foresee their future behavior based on previous choices. However, predictive analytics is now facing a crisis. And you can probably guess what the primary cause is.
As the COVID-19 situation evolves and new measures are being imposed, people's priorities keep shifting in ways that confuse algorithms and render pre-pandemic data nearly unusable. Databases are full of information on behavior typical for a bullish economy, when participants look to the future with optimism and maintain their ordinary routines. In the era of social distancing, however, consumers have suddenly cut back on spending and travel and increased their use of digital products and services. In general, people are staying at home significantly more than they used to before the pandemic. These new circumstances have seemingly leveled the playing field. Companies that previously had the upper hand are now left in the dark with their tools unable to handle the "data deficit", which means that their situation is virtually the same as that of their less data-mature competitors.
For firms that had fallen behind, this presents a golden opportunity to catch up. In some cases, though, as business owners are scrambling to jump on the omnichannel bandwagon, they decide to outsource their digitalization – hopefully allowing their products to reach more customers but also relinquishing the chance to take control of their data.
"Take marketplace shopping, for instance. Platforms such as Glovo, UberEats, and Wolt may be convenient for the customer, but they have no long-term future for the store. And that is not because of a lack of control over shipping, but rather because of a lack of control over data.
Those platforms do not disclose any information about the user except for transaction data. That means you will see a cart's value, its contents, and the time and date the order was placed. However, you will not know anything about the actual customer: was it their first purchase, or are they a regular who decided to stay at home? Likewise, it will be impossible to connect an online customer's data to information you already have about the same person as a member of your loyalty program.
Food delivery platforms are just one of such temporary solutions. Their implementation is lightning fast – in April, we all saw first-hand that it can be performed in a few weeks. In the long term, however, they will prove to be a burden rather than a benefit. Of course, those platforms do have some merit, and they fulfill their essential functions. Suppose you are thinking about launching an e-commerce platform, then those external solutions can allow you to test your logistic capabilities and gather some general information about the preferences and habits of your customers in a given city or area".
In the face of the COVID-19 crisis, some may wonder if going to great lengths to collect and process customer data makes business sense. After all, if unpredictable global events can easily undo all your efforts and cause your AI algorithms to go into a tailspin, an investment in analytics starts to look questionable. Regulations and consumer needs keep changing at a pace that makes it difficult for all sorts of data science tools to catch up. Some governments try to cooperate with businesses as they impose restrictions, yet others dish out new closures and reopenings arbitrarily and hastily, failing to notify industry representatives ahead of time.
Under such circumstances, coming up with long-term predictions may be impossible, however, companies that want to get to the end of 2021 unscathed still need to make informed decisions. Which stores to reopen first? Which parts of their offerings to prioritize to lure customers back in? Yet again, the answers lie in data. This time, though, as earlier behavior patterns have gone out of date, your datasets' recency and applicability take precedence over their size. What does this mean for your business? That the best time to start collecting information about your customers is now.
Coping with the challenges of the new normal is not the only way that data can prove useful. As Tomasz told us: "If you gather information on your own, you can decide where to test new ideas and gimmicks such as autonomous shops – an excellent example of an efficient solution that also serves as a justification for sending out a press release. You can only measure the performance of such a prototype after you launch it. Here, once again, collecting general data won't be the only thing you have to do. You will also need to learn all about the habits of each particular customer.
Shutting down a pilot store does not have to imply a failure, as some market observers may view it. On the contrary, such an experiment could allow you to verify that your customers are not interested in that format. Or maybe you could try it again after modifying the concept. Another good example is scan & go, also known as self-checkout, where a customer uses their smartphone to scan the barcodes on products and pay for them on their own. Some chains abstain from introducing such solutions on purpose because they realize that only, say, 1% of their orders would qualify for that payment method, so they would end up covering very high costs to implement a niche function."
Whether you feel ready to launch a full-fledged analytics initiative or not, one thing seems certain. If you decide to entrust an external partner with your digitalization, you will be failing to exploit a goldmine of information about your company's most valuable asset – its customers.