The secrets behind selling a product? A word from Claudio Agazzi of RetailTune

We met with Claudio Agazzi, CEO and Founder of RetailTune, a company specializing in connecting a potential customer in dialogue with a local point of sale of a given brand.

Fashiontimes.it

How difficult is it to get people to understand the added value of your work?

Today, in 2020, with RetailTune I'm starting to see a more attentive response from companies. I see companies committing to understand these aspects better; in the past there was little inclination to understand them, whereas today I find much more of that. Some companies set up working groups specifically to discuss certain performance-related topics, but this only happens when there's real willingness on the company's part to tackle the subject.

How did the idea of creating these services come about?

It all started for a simple reason: as a digital advisor I was working for a fashion company with over 200 directly-operated stores, and there, while also doing some temporary management, I realized that the whole concept labeled "omnichannel" actually meant very different things to different people. I realized how little companies were working to bring this huge mass of people approaching the web from digital into the physical point of sale. After the first phase of the corporate website, e-commerce took over, and companies saw these online stores grow in terms of revenue and got a bit carried away, often confusing the role of digital director with that of e-commerce manager. It's also true that everything that isn't online sales tends to get pushed a bit into the background, but it's also worth noting that there are still many people who go to the website, get information online, and then buy in the physical store.

What is the step that leads a person from gathering information online to then buying offline?

Along the way we've coined several new ways of framing things, and one of these is mobile or fluid CRM: companies focus a lot on CRM understood as a database, and in the fashion world they send the public an average of about a hundred newsletters every 2 years. The data tells us that over 2 years, the fashion customer buys only once in 70% of cases, so hammering someone with information to get a customer who buys just once — while forgetting about all the people who, on their own initiative, seek out the company by going directly to the website because they're interested in the brand and the product — is counterproductive. In 70% of cases, the customer who chooses to browse a website also shares their location, giving companies very useful information. At that point, it's up to us to be good at connecting the nearest physical store to the customer who searched for the brand. This applies not only to the retail or franchise world, but also to wholesale, which in many cases accounts for a large share of revenue. You need to combine the strength of the brand with information about the nearest physical point of sale, perhaps adding the extra detail about the actual presence of a specific product in one store rather than another.

What do you think of the project Alibaba is launching to create an e-commerce driven solely by data extracted from big data?

Big data has also been talked about for a long time. I think data needs to be used solidly; we have big data in abundance, and sometimes we don't even need all of it. We work with various data points, for example the consideration performance rate: thanks to data passed to us by the web, and by other technology systems that supply us with additional data, we measure what we might call local brand awareness — that is, how well known the brand is store by store, whether single-brand, franchise, or multi-brand. This lets us tell you the brand awareness penetration rate store by store, and knowing this, the company can work on corrective actions. Another example of big data lies in the fact that we know what the local audience loves most about that brand, which is the product distribution rate — a very telling metric that tells us whether the company did good buying and, as a result, achieved good distribution across the various local stores, because the same product may sell well in one city rather than another, and having this kind of knowledge helps a great deal.

What do you think, and how, in your view, can communication and a social media project be combined with what you've explained so far?

Data provided in a disaggregated way doesn't help whoever has to analyze it. We're used to working with very clear data. The topic of big data and usable (i.e., actionable) data analysis to drive positive performance has a very simple key when it comes to presenting it: simplicity and conciseness. When I talked about the consideration performance rate, I was talking about the end point of a 3-year journey, during which we asked ourselves how to measure data store by store, always at the local level, because today we've all forgotten that we almost always sell at the local level (obviously e-commerce is excluded from this discussion), and this data lets us understand and analyze current situations. If there's some solidity in how the data is managed, then the data works! We prefer to have simpler data — cruder, if you like — but solid, capable of giving useful indications.

If companies have these tools, why do they spend hundreds of thousands of euros on influencers, which are temporary activities?

Why should companies bother with things that are "hard" to understand and maybe less well known, when everyone by now talks about influencer marketing? I'm not saying influencer marketing is bad, but we're talking about two completely different things. In my opinion, a lot of it comes down to habit. We also produce performance data and results that are sometimes astonishing, and often when this data is presented it doesn't have the effect it should, probably because people struggle to grasp the concept or the real scale of it. Companies still find it very hard to make the numbers coming from this data feel tangible; it's a matter of culture and of being willing to stop for a moment and understand what's really needed.

Let's talk about the future. Imagine a future where today I search for a product on Google, and tomorrow I ask Alexa or Google Home. How does the strategy change? How are you preparing for a market where people will no longer type on a keyboard but will switch to voice commands?

Let's say whether by voice or keyboard, we're always talking about a search engine. The mechanism is the same, but the concept of a product finder is very interesting — that is, where do I find a specific product? To answer that question, someone needs to have told Google which stores currently have the product I'm looking for. If companies don't provide that information, Google won't know it and will never be able to tell the customer. We've been studying Google and we've found that by providing quality data, we manage to rank our brands in top positions, and this is possible because we've supplied all the useful data. Our current project will result in having a product finder.

What's the mistake your clients make most often?

Carefully analyzing data is the biggest mistake companies make. They almost never have an analyst on staff, partly because it's a role that's genuinely hard to find. The second mistake is not having structured a quick response to new developments and opportunities. Companies need to be able to rely on lean structures that can react immediately. It also often happens that companies lack the tools to respond in the best way. In short, companies need to be ready! In the digital world, we should consolidate the knowledge we already have.

There's a lot of talk about blockchain technology. How can it help companies add value to and certify this data?

Honestly, I find it a bit hard to make sense of this. Not every industry has the same characteristics, and the same model doesn't work for everyone, but we need to have a very clear mind in understanding how to use this data. There's nothing in today's technology that wasn't already there in the 1800s. We need to be good at using data and connecting it together, starting from the assumption that on the other side there's a user we want to treat with care. The medium has changed, but all of us need to try to be solid in what we do.

So what's the secret to selling more, both online and offline?

Taking care of information. When a website is slow, when it doesn't work, it's like slamming the door in the customer's face. What could be done that isn't being done? Let me give you an example: through a call-tracking system, we measured the answer rate of phone calls to stores, and the result is that on average 30% of in-store phone calls go unanswered; this means companies spend a lot to build a brand, to produce a catalog to showcase a product, managing to communicate the store's presence at a given geographic location, and yet 30% of customer calls go unanswered: 15% of these people who don't get an answer end up calling another brand.