As customer personalization becomes more granular, one-size-fits-most assumptions are becoming archaic. Acquisition of customer data is important, but the real value lies in properly interpreting and utilizing the data to understand and serve customers.
Pinpointing the preferences of the digital consumer is proving to be extraordinarily nuanced. This is particularly true of millennials and Gen Z consumers whose buyer journeys involve touch points across multiple channels, making traditional tactics less impactful.
The wealth of data captured on customers from a wide variety of automated, algorithmic sources, might confound rather than clarify retailers. The tremendous influx of available customer data begs a key question: what to do with it, and how best to use what you have?
The recent shifts in consumer behavior and accelerated digital shopping trends brought on by the COVID-19 pandemic have not made these questions any easier to answer. Additionally, the adoption of emerging retail technologies (such as VR, Web3 and software that places individual data at the center of the web experiences) has surpassed projections by nearly a decade, in some cases.
These shifts in consumer preferences in ways are more predictable for digital marketplaces, where nonlinear and significantly better-informed purchasing decisions have become normalized for demographic groups beyond the digitally native.
The digital world serves consumer niches effortlessly. This results in increasingly fractured demographic groups with unique preferences that may deviate hugely from conventional consumer wisdom. Consumers also expect to be provided with experiences that are customized to them and where they are in their journey. For example, younger demographic groups obtain most of their product information from social media, and are less influenced by traditional advertising tactics like outbound marketing and television commercials.
“The customer is the only channel,” agrees Rasmus Hyltegard, AI & IoT retail lead at Avanade, and Amperity Solutions Consultant Megan Lunde in a discussion for RETHINK Retail with Carl Boutet, a retail strategist and board advisor of StudioRx, on the subject of digital transformation, modern customer relationship building, and relevant developing retail trends.
It is a simple observation that reinforces an intuitive, tried-and-true retail approach: that to reach consumers, you need to understand what they want, when they want it, and where they are looking for it. Retailers must follow consumers through a more fluid, channel agnostic experience, rather than leaning on a singular channel approach.
Customers know retail has become increasingly data-centric, and they’ve increased expectations. Today’s consumer wants brand experiences and targeted suggestions to “show me that you know me,” to make use of that targeted data, to know that the debate around privacy is at least resulting in better consumer experiences.
However, the emphasis on that conventional wisdom is tweaked here in a critical way: viewing the customer as the “only channel” in a era of modern and emerging technologies implies a move away from reliance on aggregate consumer data trends toward sharp data insights that allow retailers to shape consumer journeys to each and every individual’s preferences.
“It is pivotal to understand your customers, their level of engagement, and predict what they will respond to. Customers want to know that the data retailers have collected is being used to understand who they are,” argues Hyltegard.
If that sounds overwhelming, the good news is the data, tools, and technology already exists to do just that.
When Personalization Still Isn’t Personalized
Whether relying on web and digital marketing services, purchasing other third-party data, or cultivating your own data analysis, retailers should work towards using data to put customers at the center of their brand experience. Consumers want to be spoken to as individuals, and feel that all the talk of ‘personalization’ is actually personal.
Lunde argues that traditional retail methods – like showing customers the products the retailer believes they are most inclined to purchase according to aggregate-level data – don’t necessarily deliver what modern consumers consider a ‘personalized experience.’
Understanding customer intentionality – why they are purchasing what they are purchasing and what matters to them when making that decision is an insight that can be leveraged to ‘speak to’ customers in a way that inspires loyalty-generating interactions.
When consumers believe their data is being provided to enhance their experience, they will be more willing to share that information with retailers.
“‘Personalization is a differentiator. You need to invest here,’ [is what you would have heard 10 or so years ago]. And I think not so much anymore. Every customer expects [basic personalization] with every brand that they interact with…the expectation is now there for retailers to show me that you know me and create curated, seamless experiences,” argues Lunde.
At times, retailers may find themselves with such a wealth of data that it becomes overwhelming. To which they should ask: How do you identify your best data? How do you implement it at the point of greatest opportunity?
To do so, you have to know how not to think about customer data by becoming much more careful about your assumptions.
Avoiding Misinterpretations of Your Data Analysis: An Example
Building trust is an important component of maintaining brand loyalty, but it isn’t what it was decades ago. Consumers have endless opportunities to explore alternative products, which has led to fragility in brand loyalty.
Younger purchasers, in particular, can go find a YouTube influencer who will go into excruciating detail about why the competitors are better. There is just too much information, too many off-brand opportunists, too much of seemingly everything, and as cognitive research has shown, the perception of greater choices leads to reductions in reported satisfaction with whatever one ultimately chooses.
That means less satisfaction overall, particularly if your product has problems. With so many options in the palm of their hand, dissatisfaction leads to consumers going somewhere else at the drop of a hat. This can be described as a reduction in inherent customer loyalty.
“Who is my high-loyalty customer today?” To know who your loyalty customers are, you need to identify them first, then thoroughly understand what makes them tick. One pitfall in this process is to conflate data trends that do not necessarily have a causal relationship with loyalty with the perception of actual ‘loyalty.’
Lunde provides an example: your high value customers – whether top percentage buyers, lifetime value customers, or high-spending customers – aren’t necessarily your loyal customers.
“There’s this correlation that happens in your mind that high value equals loyal. So if you see that your average customer is spending a hundred dollars a year, and here’s someone who’s spending $500, she’s super valuable. I agree with that. Is she super loyal? I don’t think so. You don’t really know. You don’t have all of the information to know that maybe she’s spending $700 a year at your competitor down the street,” argues Lunde, emphasizing that need to check assumptions.
“You can’t get complacent about high value customers and just think, they’re loyal. I can count on them…because otherwise your competitors will court them, and they will erode away from your brand.”
New Technologies, New Consumer Expectations: Be Smart, Adapt, Change
All of this makes for a hyper-competitive retail market. It’s daunting. It’s new. It came to the industry “faster than expected.” However, it is ultimately no different in principle than the demands of any new technology, manufacturing process, or innovative marketing campaign.
Conditions change, and with them are always opportunities; when suburbanization took off in America, a famous example in the print world of innovative adaptation is the National Enquirer’s pioneering of the supermarket magazine racks in check-out lanes, an innovation that arguably allowed Reader’s Digest to become what it did in the post-war world quite single handedly.
Businesses can succeed in this changing world if they freshen their thinking. Aspects of the ‘old ways’ may be crumbling, but if your business feels like it’s in free fall into data clouds you don’t know how to use, at least don’t cling on to any boulders falling with you.
Invest in data analytics and gain a competitive advantage over those who refuse. Build a 360-degree customer view and integrate critical data insights into your strategic planning to customize consumer experiences and drive loyalty.
For more, you can listen to RETHINK’s Debunking Data Myths for Digital Transformation.