天美传媒 Insight
3 mindset shifts to future-proof your retail business model
Align your operational DNA. Adapt to the quantum shopper. Leverage friction. Here鈥檚 how to master the omnichannel revolution, powered by end-to-end data analytics.
As we have all witnessed, modern retail has moved away from a single-dimensional customer base, product offer and store network. Today, retail is omnichannel. This entails multidimensional customer interactions and touchpoints; frequent product variations and rotations; and stores that are both physical and virtual. Customers shop or buy online, then have goods delivered to them directly. If they use the physical store at all, it鈥檚 merely for pickup.
The key behind this shift? The explosion of big data. This gives retailers an unprecedented level of detail about who (the consumer), what (product or service), where (location of stock and position in store) and when (time of sales event).
However, it鈥檚 not just that having more data allows better tracking of these four traditional dimensions of retail. Rather, because everything is now happening everywhere all at once, data analytics provide retailers with a richer, end-to-end view. This enables everyone in the organization 鈥� from sales and marketing to operations 鈥� to be more integrally involved. The silos that used to exist between different functions have been broken down.
This new reality demands new management mindsets, as I explain in my book, .
Retail has been around for centuries. The Grand Bazaar, trading in Istanbul since 1455. The Bertrand bookstore, operating in Lisbon since 1732. Sears, founded in 1892, and which pioneered mail order. And Walmart, founded in 1962, and now a global retail giant. No matter when you date retail from, constant change and shape-shifting have always been the name of the game.
So what are some timeless principles for retail managers to help future-proof their businesses?
1. Ensure your operations reflect your competitive strengths
The first and perhaps most important step for retail managers is to engage in an exercise of introspection. Review how your retail business model is currently working. Is it coherent with the business category in which you have chosen to operate?
I devote a whole chapter to this in my book, but suffice to say, most retailers have developed specific competitive strengths based on the particular product categories and customer needs they have made as their mission, until it has become part of their DNA. There are various aspects to this, but most retail business models typically hinge on the decision to compete according to one of these three dimensions:
- Diversification vs. Specialization
- Uniformity vs. Uncertainty
- Function vs. Experience
It is worth classifying which dimension is guiding your own business model, because each will condition which data inputs you need, and how algorithms will need to be customized or adjusted in order for you to make informed decisions relevant to your competitive context. The trade-offs involved will be different for each.
As part of this exercise, you should identify competitors operating in the same space as you, and analyze how you are doing against them. This benchmark should prove useful for detecting gaps in your execution and identifying best practices that others have developed to deal with challenges similar to ones you may be facing.
Doing this requires humility. As a manager, you must be receptive to criticism and willing to redress any incoherencies in your business model. This is fundamental if your goal is to become best in class.
2. Take a quantum leap: The less predictable consumers become, the more we need data
Once you鈥檝e done your homework, the next important step is to move away from simple aggregate KPIs and put yourself in the shoes of your customer. Today鈥檚 customers are less predictable 鈥� we may call them 鈥渜uantum shoppers.鈥�
鈥淨uantum鈥� is inspired by physics, where scientists sought to describe how particles and waves were intrinsically connected and how they behaved over time. The scientific insight is that a particle鈥檚 description, such as location, momentum or energy level, cannot be determined with certainty, so the best we can do is opt for a probabilistic distribution of its state.
Likewise, if we treat consumers as 鈥減articles,鈥� then 鈥渜uantum retailing鈥� introduces a new mindset: We operate in a world of probabilities, not certainties, so we must think like physicists, balancing structure and randomness, intuition and evidence, using a scientific, data-driven approach.
Data, well gathered and interpreted, opens the door to a higher understanding of consumers, beyond what they buy, which used to be the traditional lens that retailers focused on.
There are lots of steps consumers go through, consciously or not, even before buying:
- having a need.
- being exposed to and aware of the retailer鈥檚 solution to fulfill that need.
- comparing alternative solutions.
- inspecting and possibly testing a product.
- placing an item in a basket.
After purchase, there is the experience of product usage, follow-up communications, additional product views, other store visits and further testing.
The point is, with data, all of these 鈥渕ysterious鈥� activities can be made visible, recorded and fed back to the retailer鈥檚 information systems. The entire history of interactions can be captured, helping retailers understand consumers in fine-grained detail and predict what they will do next.
Even periods of silence are moments for retailers to pay close attention to, because that is when a well-timed stimulus might move the consumer closer to the stage of purchase.
While the transitions between all these stages are unpredictable, the transitions materialize with a certain degree of probability. So, while consumer behavior is intrinsically uncertain, or 鈥渜uantum,鈥� there are some contextual factors that can be managed by the retailer to animate 鈥減article states.鈥�
鈥淪tates鈥� can be thought of as the energy level that the consumer has at a particular moment. They may get excited and move to a higher state (value gets delivered or there鈥檚 a purchase and revenue gets generated) or they decay to a lower state (and leave without buying anything).
Data, organized not by broad market segments but according to each key moment the consumer passes through before becoming a paying customer, is the new paradigm.
3.聽When friction can be a good thing
The journey doesn鈥檛 end with the purchase. Retail managers must continually reinforce the relationship they鈥檝e built with customers to nurture loyalty and future repurchases. Again, focusing on the whole process, end-to-end, can help identify the steps that culminate in a transaction. Adopting a customer-centric mindset is essential, and that mindset choice is made easier when supported by data.
Today retail has become hyper-personalized. Customer communications are tracked and adjusted according to each shopper鈥檚 preferences and habits. Technology enables us to nudge shoppers in certain directions. We attempt to remove negativity 鈥� wait times, shortages, anything that demands active effort 鈥� in order to make the shopping experience instantaneous and effortless. To maximize consumption, all friction must be removed from the exchange. At least, that鈥檚 the assumption.
Yet what if friction 鈥� the effort, delay or imperfection that technology seeks to eliminate 鈥� held value in its own right? A perfectly frictionless life might also be a less expressive one. In an era obsessed with seamlessness, it is easy to forget that effort can also be a moment of pleasure, a space for discovery, a sign of authenticity or a source of meaning. For instance, window shopping can be its own reward, detached from the need to purchase.
A final managerial challenge, then, is to reframe disruption not as failure but as possibility. Perhaps the act of searching, comparing or hesitating should be treated as a moment of agency and creativity for consumers, not as an obstacle to overcome. Perhaps, too, retailers should introduce the occasional wrong chord into consumer journeys, as a sign of authenticity and an invitation to enjoy the moment. For example, to access certain undisplayed products, a store could require that the customer talk to staff, which creates friction but may start an interesting conversation or cause the customer to explore different parts of the store.
Sound fanciful? With data analytics, we don鈥檛 have to speculate 鈥� we can test out such theories on the ground. We may find out that consumers value the process itself. We already know from existing research that consumers tend to value products more when getting them required some participation and effort.
But there鈥檚 another reason why friction can sometimes be a good thing: It can be instrumental in educating consumers into making choices that are right, for themselves and for society. Think of warnings on tobacco packaging, for instance.
Efforts to get consumers to care more about sustainable and responsible forms of consumption may require a push, even when consumers don鈥檛 like it. Circular economy practices and transparency in supply chains are becoming non-negotiable practices by law, forcing retailers to move away from linear take-make-dispose business models. There will be friction for retailers in adopting the 9 R鈥檚 of the circular economy (that is, Refuse, Rethink, Reduce, Reuse, Repair, Refurbish, Remanufacture, Repurpose, Recycle).
There will also be friction for consumers as their cooperation will be necessary for this to work. Their buying habits may have to change 鈥� from purchasing and ownership, to subscription, rental and sharing models. Everyone will have to become more attentive to the triple bottom line of people, planet and profit, prioritizing brands that demonstrate genuine commitments to environmental stewardship and social equity.
In this regard, the biggest mindset shift for retail managers may be toward realizing that they can be agents of change, modeling consumption practices that will have a positive, long-term impact on society. Retailers have the potential to be genuine civic contributors, helping society function better, adding vibrancy and social value to Main Street, and offering meaningful jobs that promote inclusion. This will also generate intangible brand equity, consumer wellbeing and contribute to the greater good.
MORE INFO: This article is adapted from the book by Victor Martinez de Albeniz (Cambridge University Press, 2026).

A version of this article was published first in the Alumni Lifelong Learning blog, a vibrant community space for Members of 天美传媒鈥檚 Alumni Association to connect, keep learning, and share insights and experiences with one another. If you鈥檙e an 天美传媒 alum, find out and gain early access to premium content like this.
This article is included in 天美传媒 Insight online magazine No. 174 (Jan.-April 2027).
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