Interview with Lucio Lamberti, Professor of Omnichannel Marketing at the Polimi School of Management.
Rich in DATA but poor in INFORMATION: loyalty cards are a treasure of inestimable value, but Italian retailers are not yet ready to capitalise on them.
Lucio Lamberti is a Professor of Omnichannel Marketing at the School of Management of the Polytechnic University of Milan, who collaborates with Promomedia, a market leader in promotion and communication. He tells us how a data-driven approach can revolutionise the modern retail business.
“Let’s start with an assumption: competition in a market without significant growth rates is a complex process”, begins Lucio Lamberti. “Acquiring a new customer involves a tough battle in terms of communication and promotions and, subsequently, keeping the bar high, to avoid abandonment.
It’s an expensive process which, at a time of stagnation like the current one, is not sustainable. On the contrary, working on the relationship with your customers is certainly not free, but it is a process that adds value over time.
This process is customer relationship management, or CRM. The pioneers of CRM are the big players like Amazon and the social networks of the Meta group, who have begun to show their customers how, by taking advantage of the data gained from continuous interactions, it’s possible to offer more efficient shopping experiences and more fluid sales opportunities which, as a result, lead to the perception of a better service.
So we’re talking about Customer Centricity.
Yes, that’s right. Customer centricity is the goal to be pursued. Today’s manufacturers and distributors operate with a product-centric approach whose aim is to sell as many units as they can to as many customers as possible.
The customer-centric approach starts from a different premise: customers are not all the same but unique, so the goal is to know the customer, their habits and tastes and offer unique, personalised solutions.
Yet modern retail is a privileged interlocutor in terms of knowing its customer.
In principle, yes. Mass retail was the first to introduce loyalty cards, a tool with a very high potential that is used…to give away towels. Loyalty schemes are used to retain customers, but they’re often limited to collecting standardised, boring products, when instead they could offer much more profitable opportunities for the brand.
A change of culture involving all levels of the company would be necessary.
More than a change of culture, it’s about changing the perspective. Mass retail already has the data culture. A sales manager knows perfectly well how many litres of beer were sold on a given day, so they do read the numbers. What they don’t know, because they never think to find out, is how many customers bought beer and who these customers are. It’s the difference between having data, indeed an invaluable wealth of data, and having information.
We were talking before about promotions as the main competitive lever among retailers; do you think CRM can defuse this dangerous race to the bottom?
We’re in a period in which the promotional competition is increasing in order to retain customers; to put it bluntly we could say that retailers are paying for loyalty.
In fact, by reading a customer’s purchase data, you can understand a lot, and you can go back to offering value-added services for the customer.
Let me take an example: if I see from their purchase history that a consumer has never bought meat-based products, I can deduce that they’re part of a vegetarian or vegan family unit.
So does it make sense to send a newsletter with promotions for “pork week”? At best, this is only a waste of communication, at worst it acts as a disincentive for the consumer, who may feel annoyed at receiving unsolicited communications.
We often hear about predictive spending, what does it consist of?
The predictive spending model already successfully adopted by Amazon and some Italian retailers is based on analysis of the purchase history of a given customer: the algorithm can calculate the frequency of purchase of a product and suggest a pre-filled cart with products that the user is likely to buy again.
What message does this send to the user? I know you well so I save you time by preparing your shopping cart with the products you buy frequently.
With this type of service, the price variable tends to fade because for a customer, saving time can have a higher perceived value than saving money, as in the case of Amazon, it is convenient but not necessarily the least expensive option.
Does CRM allow you to arrive at this type of predictive analysis?
Yes, absolutely. CRM systems such as the one implemented by Promomedia offer different types of cart analysis and allow you to activate various functions depending on the environment in which the user is moving.
It’s clear that predictive shopping can only be used on e-commerce platforms, as it allows pre-filling of the electronic shopping cart, but there are other functions available for users who make purchases in physical stores.
We’re talking about basic functions such as promotions related to particular events, such as birthdays, or more complex functions such as promotions based on buying history, so in the example mentioned above, the user who buys only vegan products might be offered a promotion on a vegan or vegetarian product they don’t yet know.
An even more advanced and more interesting function could be purchase suggestions linked to the history of other users/customers with a similar profile.
Let me explain: if analysis of loyalty cards shows that two users have a similar customer profile and you notice that user A buys a product that user B doesn’t buy but that is consistent with their habits, you can send a newsletter containing the suggestion “other users have also bought…”
This practice, frequent in online stores, is the first case of an activity that’s also valid for offline users.
E-commerce is a much discussed issue for modern retail, for many it’s the future, but at face value it seems to be unsustainable. What’s your view?
E-commerce has enormous costs in terms of logistics, and that’s why there’s so much discussion. The question is: How do I create value? The answer is that it doesn’t create value in itself, but it creates value in terms of relationship with the customer.
Let me explain: if I get a customer online, it’s very unlikely that the numbers add up, if we include raw material costs, delivery costs, picking staff and everything else.
But what we’re observing with data analysis is that, on average, the online customer tends to be multi-channel, but customers who choose e-commerce are precisely the customers who are worth on average 3 times more than those who spend only in store. So they’re the best customers.
This means that in product-centric terms, e-commerce is not convenient, it’s a loss-maker. On the other hand, from the customer-centric angle, closing the e-commerce leaves your best customers unsatisfied.
E-commerce therefore makes sense when it becomes a channel of contact with your best customers.
What are the obstacles to adopting a data-driven approach?
The main obstacle is the organisation of the large-scale retail trade. Sales managers have an interest in selling a certain product category, because volumes are linked to rewards, it doesn’t matter whether or not the customer is registered or profiled. The interpretation of central customer data is a skill that the retail sector doesn’t yet have.
Of course, it’s an ongoing process and the most forward-looking managers are including data scientists in their teams, but it’s still early days and there’s no history on this issue. It’s a major revolution, which can bring enormous value to the entire organisation.
Does the data-driven approach come from CRM alone?
Absolutely not. Data analysis and artificial intelligence can also help in category management and in reordering, because it intervenes predictively to estimate the quantities of product to be purchased and therefore optimise stock inventories and reduce food waste. But that’s another very long chapter which merits a separate study.
One last question: do you think customers are reluctant to share their data?
Data processing is certainly a widely discussed topic, and there have undoubtedly been several cases of abuse against users.
The issue isn’t whether the user is more or less willing to hand over their data, but that the user determines their willingness to hand over their data on the basis of the benefit they derive from it.
If I say to you: just give me your data, I’ll obviously encounter resistance, but if I tell you: give me your data so that every month you’ll receive a free sample of a product in your area or a promo on a product that you regularly use, it’s a different matter.
As we mentioned before, loyalty cards are the classic example of how to gain customer trust, but they’re only the first step towards a change that retailers need to make.
