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A VoC Interview with Massimo Paludet, Customer Care Director at De’Longhi

Wonderflow’s Account Executive, Adam Hosker, is joined today by De’Longhi Group. Specifically, we interviewed Massimo Paludet, Director of Customer Care.

·21 min read

Adam Hosker

De’Longhi is one of the top leading brands in the small domestic appliance industry, best known for its home coffee machines. Since its establishment in 1974, the company has distributed products related to coffee, cooking, air conditioning, and so forth in over 120 countries worldwide, including commercial sales in Europe, North America, the Middle East, Africa, and Asia.

Paludet has been in the industry, at various global firms, for over 15 years now, having observed the sector’s evolution and helping it transform into a more customer-centric arena. We are fortunate to bring in Paludet and his years of expertise in this unique interview that contains a 40-minute live recording and the video’s transcript. Click to watch the video interview below:

Or read on further to learn all the questions asked and Paludet’s transcribed answers.

Hosker (0:09):Massimo, Thank you very much for joining me today. Obviously, this is part of our VoC interview series on customer experience. In particular, leaders and their shared insights for other people in similar roles to understand and become inspired to work in similar roles.

So we just wanted to obviously have a conversation about your work and what you’ve been doing and how you’ve been finding some of the advances in technology over recent years and obviously into the future. Just as a quick introduction to people watching this, do you want to give us a quick intro on your role at De’Longhi?

Paludet: Yes, sure. So, first of all, thanks for this interview, Adam. I’m glad to present my experience with the Wonderboard tool.

I joined the De’Longhi Group in 2007. So it’s almost 15 years now after another long experience at another premium company, all of which are multinational companies. And it has been a journey since then when I joined.

It’s a really great group, a great company to work at, De’Longhi. Vert nice and useful products. I think it’s normal that you know, you have to love the company you work for when you stay there 15 years and not planning to leave in the short term!

So, when I joined the company, I think it’s interesting to see how the situation has evolved over the years. The De’Longhi organization was “service.” The name of the department was “TLS De’Longhi Service.”

With the TLS, we were supporting many other brands, all the brands of the De’Longhi Group. We have about 20 brand names, some of them are not even existing today, but some still are and are still very important like Ariete.

So, once upon a time, it was service. Then I brought in a bit of the evolution of our job, from Service to After-Sales or After-Sales Service (whatever you want to call it). But I also wanted to bring something broader, something that encompasses not only the technical part of the job but also consumer support. _Very_much consumer support.

Long story short, today we are “Customer Care.” To a broader scope, supporting consumers all across the journey: pre-sales, even during the sales phase, and after-sales. With additional services, added-value services, even repairs, accessories – whatever you need that is connected to the consumers in an engaging manner. I think this is very important.

I can also say, and although this may not be completely true, our products are very much alike. Our competitors, they also produce good products. They also provide good services. So, service can be, let’s say, the way of managing better consumer loyalty, managing better the relationships, gaining trust from consumers, and of course, from our customers’ business partners.

We need data. We need to be able to process data. We use data in our organization, and modern technologies enable the organization to exploit the data content in an easier manner into something that can be understood, even if you're not a data scientist. 

Massimo Paludet, Customer Care Director at De'Longhi

Hosker (4:15): So, just very quickly on the organization, Massimo - De’Longhi is still a family-owned business, isn't it?

Paludet: It is a public company. Of course, the family owns a good part of the shares, but it is a public company. The family influence is important, but we have a CEO who is not a member of the family, Mr. Massimo Garavaglia.

Massimo Garavaglia comes from Maracaibo, which is in the food industry business of chocolate. So, our organization is quite modern. Yes, the family influence is there. The family legacy still can be appreciated all across our organization’s processes, and the sense of belonging to the company - the sense of belonging to the bigger family that is the De’Longhi Group. So, it is very important, but we are a modern multinational company.

Hosker (5:16): Didn’t that combination of being a modern PLC business, but without that family influence, be one of the reasons why customer care is taken so seriously in the organization?

Paludet: Well, customer care is taken so seriously because it's an important competitive factor. It is a competitive advantage that you sum up with your product innovation, excellent distribution, and excellence in execution.

So you need the right people, the right processes, the right product, or the right mix of everything. But in the very last mile of the very last meter, you need to interact with consumers in the proper manner. Also, in the operation of the phase.

Let's say marketing, for instance. The marketing community uses its creativity to attract consumers. So it develops dreams, concepts, or even any important things. But what I want to say is when it comes to the “Huh?,” “But,” “What if?” question, or a question that the consumer asks in relation to maybe a marketing message - we must provide to the consumers a factual answer.

You know that is more about the relation, and it's about trust. It's about building this relationship with consumers.

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Hosker (7:04): I think that takes me nicely to my first proper question, which is about the organization’s take on data and particularly about advanced technologies in the digital world. So those tools that exist to facilitate a lot of what you were talking about.

What is De’Longhi’s take on the use of advanced technologies like artificial intelligence? And I know it’s a big question, I understand. It's quite a broad question as well.

Paludet: Well, it’s not big. I will turn it the other way around that. I believe that only naive companies don't use data properly. Data is necessary. Data provides the right perspective, the right understanding, and the true knowledge of things.

So, if you say - “well, but I think that the market is going that direction or the other direction, and this is a gut feeling,” - then please consider that your gut feeling may be very wrong.

Whereas, when you start performing data analysis, a Consumer Insights Analysts say that consumers prefer, I don't know, silver coffee machines because you've got the feedback from 1.5 million consumers. That is almost the most factual definition, isn't it?

So, we need data. We need to be able to process data. We use data in our organization, and modern technologies enable the organization to exploit the data content in an easier manner into something that can be understood, even if you're not a data scientist.

We do need data. We do use data as we started our digital journey a long time ago. And for the digital journey, the terrific part of this digital journey is that you discover new and exciting things every day.

The boring part of this journey is that they say, “wow, but there is so much.” I mean, you need to sort out what you want to address first, and that is why you need some order, some discipline. Something simple.

Eventually, we are discussing the Wonderboard tool. So, one of the reasons why we chose Wonderflow is because it enables a job, an activity, and factor analysis in a simple manner. Very simple. Even the implementation was simple!

And when it comes to AI system implementations, they're not simple at all, to be honest, in this situation. So, to perform data mining - or data analytics, semantic analysis, everything - I mean, you need a lot of technical understanding about how to do those things. You also need an IoT infrastructure environment, a data lake, data organizer.

So, actually, it's not simple. And getting something simple is like a miracle to us. It's beautiful.

Hosker (10:33) It really is beautiful, isn’t it? And I think, for decades now, companies have used structured data and saw numbers essentially to do data analysis. I guess you are trailblazers for using unstructured data. So, the language of customers, particularly the voice of customers, and being able to do that kind of analysis.

What was the driver, or the event, that really made you want to dive into that information to really understand at a very granular level versus what your customers were saying?

Paludet: We started from a very simple concept: we wanted to improve our website service. It was a basic requirement to improve our website service and the knowledge-base. To improve the knowledge base, the best way is to review all interactions we have with consumers - all interactions that are registered in our CRM as well as ratings and reviews or Q&A.

So when consumers ask for something, let's see whether we can produce a knowledge-based article that replies to that very question. So we started from there.

We also experienced some other systems that were used to correlate the information to explain what are the relations among different factors. We are also partly using our own Business Intelligence to perform a certain kind of analysis. Just as I said before, though, it was time-consuming.

After one and a half years of experiments - basically using tools or trying to design a tool to perform consumer feedback analysis with text analytics and sentiment analysis - we discovered some benchmark systems in the market. But actually, there were not so many at the time, and then we discovered Wonderflow. That was like a big bag of chocolates: you pick one, then you pick two, then you keep on eating chocolates until you’re… (chuckles)

But anyway, it is really like that because the amount of information you can get from those systems is massive. The possibility to combine - to correlate factors with others and perform analysis from many different perspectives - it’s really impressive.

The other thing is that it fits the needs of different stakeholders in the organization. Because marketing has different needs from the one that R&D has or Quality or Customer Care. We can then maybe be more interested in what are the, you know, customer satisfaction, relation services, etc.

Whereas, Quality can be interested in what are the weak points of our products. Whereas, Marketing can be interested in understanding whether the marketing message is well-perceived, whether product features are evaluated positively or not. So, each stakeholder gets the proper reply to the question, and that, I found really impressive.

Today we are “Customer Care.” To a broader scope, supporting consumers all across the journey: pre-sales, even during the sales phase, and after-sales.

Massimon Paludet, Customer Care Director at De'Longhi

Hosker (14:48) Yeah, I think what you've mentioned there is the drive that we've seen from our end with De’Longhi. You're becoming more and more customer-centric.

And I think what you’ve mentioned there about multiple departments - obviously, you're running one department in a huge business. But this particular product itself (and obviously the journey that you've been on) is very much about bringing the whole organization together and everybody dipping into those different pieces of information. So was it a challenge when you decided to make the company more customer-centric? What were those challenges that you had?

Paludet: The challenge is not about being more customer-centric. And actually, I find the definition of "customer-centric" to be a bit obsolete. We are more for customer engagement. So working beside our consumers, we are not looking at consumers, per se, like they are observing ‘the Gods.’ That’s not the case.

They (customers) are our peers. We are sitting together. We’re doing business together. We are understanding their needs in their actual essence. It's not like trying to figure out what they think.

The challenge is to disrupt all the well-established processes that are present in the companies and reshape the way of work; reshape the organization in order to be actually engaging with consumers, engaging with the customer (or consumer-centric if you like, whatever) - in a real manner, not just in theory. Because if you keep your organization the same, if you keep the same processes, it won't work.

I think everybody understands how important it is to engage with consumers, to engage properly or what it means to a consumer-centric organization. It works only if you implement a new organization, new processes. Your way of work has to change.

You cannot maintain the same - for instance - MPD process, new product development process, if you are not sure that you consider your customers’ input at the very beginning of these processes. You cannot initiate a new marketing program if you don't consider actually and properly and with the right level of details. What was the consumer feedback of your previous campaign or what are the consumer trends nowadays?

And I'm not speaking for the De’Longhi Group now. There are many companies, many good companies out there with plenty of professionals that, we can say, know how to do the work. But we need to learn a new way of doing the work. And this is a transformation. It takes time. It requires a change of mindset.

Hosker (18:29) How would you say your working styles changed over the years?

Paludet: I love to change all the time, consistently. This is also one thing that I ask everybody I interview when offering a job.

When you do something, when you are trained or in the experience of doing something for a long period of time, don’t think it is the best way to do it. There’s always the best way to do things, every day. There is innovation. There are smart people thinking about smart solutions, innovative solutions that are a breakthrough in the way of work or in the industry or in the products. So, it's really important, to some extent, to be humble.

I'm a professional, but out there? There is someone more professional than me. They can teach me something, and my objective is to listen and learn and implement. And this is a consistent growing path.

Hosker (19:40) There's a saying in the UK that if you stand still, you're actually moving backward. I think that very much sums up what your thoughts are.

Paludet: Well, the problem in the De’Longhi Group is that often we move too fast, and then we will need a new pair of breaks. But moving fast and breaking things is the funny part of the job.

Hosker (20:08) I think it's probably not that easy for some individuals or businesses to move as fast as De’Longhi sometimes does. So what would you say the barriers are for companies that are trying to catch up and improve what they're doing as a business? And the decisions they're making through the insights you're getting from consumers?

Paludet: Consumer insights are consistently a source of inspiration. What I love about those kinds of tools is that you can spot weak signals, especially weak signals because you can identify the big trends rather easily and from many different sources.

But when it comes to weak signals, those weak signals can be the innovation that you're looking for or it can be the point that you didn't consider when you develop a new product and when you develop a new process.

I believe it really changes the perspective of looking at the way you do business, from the organization that didn't know how to do something to the organization that knows that there is something. But first, listen to the market - to consumers - and say, “Hey guys, let's do something together, something new, beautiful, exciting. Let’s get together.”

Hosker (22:14) I guess you guys have had a few Eureka moments over the years, haven't you when you've been listening to the customers? I think there was something the last time we met that you mentioned about one of the coffee machines you make and ‘noise’ and the importance of that.

You could use that example or another one, but would you say there’s a particularly big Eureka moment in the last couple of years that, perhaps, wouldn't have been noticed without listening to consumer feedback?

Paludet:Well, this relates to what I said before. We discovered things. We perceived that there was something to be addressed, but the "Eureka" was really explicitly vivid, like, “Hey, this is the point we have to address.” It was so clear, but I didn't have the evidence. Now, I have crystal clear evidence.

And as I said with weak signals: weak signals were Eureka moments like, “oh, I found you look! This is important. This is relevant.” It wasn’t relevant for me, but it had top relevance for the consumers.

Also, re-leveling our priorities? That was really a “wow” effect. We thought that value for money was a big issue, for instance, or a big target. Whereas consumers are more interested in usability aspects, for instance.

Also, among some of the new machines we have, we have some that are so technologically advanced. Then you need a bit of skill and understanding to exploit their maximum potential. I mean, you can use them but be even slightly disappointed because they say - “Ah, I thought it was rocket science,” or whereas I'm just getting a coffee.

Well, actually, that is rocket science. You can get a super-barista coffee, but you need a little bit of training. Because it's like when you drive a Ferrari, you need to learn how to drive a sports machine. That is not a family Sedan. It’s a Ferrari. Even gear-shifting is something new to learn.

And that is the learning curve and improvement process: when you say, “Ok, I understand that. I need to explain these things better. How do I do that?” Implement something and measure. Use the feedback.

One point I didn't mention is the speed of the feedback. Because, normally, performing customer interviews (or customer surveys or qualitative reading feedback) takes a long while. If you imagine the industry in the past, one of the parameters (that is still used by the way but most considered for quality improvement) was the service rate. Or the so-called ‘failure rate’ (meaning the percentage of products that were failing within the warranty period).

Today, the perspective is very different. It’s not that it is irrelevant. Only a few reviews (but very accurate ones) that are collected from one of the sources can be the trigger for quality improvement.

So it's not more statistical base but rather based on the probability of it happening. This is really important because this allows companies to react much faster than in the past. But to be able to do so and address your effort precisely, you need to act on this kind of data and this level of accuracy.

Hosker (26:26) Massimo, when you bring out a new product (and if we looked at like the old world before doing this kind of data analysis), how long would it have taken you to collect that kind of feedback? Sending out review forms to questionnaires to customers, all comparative to what you can do today?

Paludet:In our NPD process (and now we have a new one, thanks to the better management of the voice of the customer), we will redefine the complete checkpoint, which is now the gate system of our new product development process. But in the past, we had the standard checkpoint. Normally, from CP 6, that was a go-to-market tool. For product review, the CP 7 and one year more or less.

So, lately, we performed what we called (in company jargon) a “CP 6.5” because we performed bad! We were not waiting one year when we launched new products.

I remember recently, a kitchen machine (a coffee machine that is a connected product and an important product), we started to review the data daaays after the launch. We consolidated the first data weeks after the launch. Had the first product review one month, two months, after the launch. It's a huge difference.

As I said, what is important is that when you don't start to approach from a statistical viewpoint and say “okay, let me wait to have, I don't know, 600 or 6000 feedback before doing anything.” No! I get three or four feedback that says, ‘hey, this feature doesn’t work.’ Then, they say, ‘ok, let's perform an analysis for what is the likelihood of this event in our product?’ And you say it’s non-existent or misuse, etc. It can happen, and you can react immediately.

Imagine, also, the cost-benefit. Because if you have an issue with your product, you can rectify it and save months, if not a year!

Hosker (29:04) And that must be worth huge sums of money in research and development. But, most importantly, sales. If you've got a minor issue, perhaps even a training issue like people can't find a feature on the machine, then you can identify that straight away and contact those customers. You're going to have huge impacts, aren't you?

Paludet: Absolutely. And also, consider that the feedback is unprompted because the consumers voluntarily leave their reviews on the website. The other thing is that you need to understand how to read the reviews. It's not transparent.

Whenever you perform, like in the customers’ way, that's normally biased. It depends on the agency and the type of consumer selected. So the result is normally reliable but biased. Whereas, the others are unbiased feedback, unprompted feedback, and fast feedback. So, I think that there is great value in those.

Hosker (30:26) It's amazing. And this is another fairly big question, but what’s your vision of the future? Of yourself and other companies using consumer feedback. What do you think? Like the sort of ideal things that would happen going forward?

Paludet:There’s a bit of discomfort in my reply because we are not graduated now. We are really almost toddlers of the digital world. And a lot of people speak about AI, but only very few have an understanding of the complexity that is behind it.

One example: companies do a lot of saying about artificial intelligence and chatbots. Then I can list, among my friends, a large group of them who have had miserable experiences with chatbots. That means that the chatbot system is maybe backed up by a very poor AI feature.

We are learning how to develop those. We are implementing as a business community the infrastructure because you need a certain level of databases - the IT infrastructure, the data orchestrator, and data lakes.

So those kinds of things, I mean, a lot of people take AI for granted. They do exist in many areas; maybe in the financial area, they are more present than in the business we are in, like small domestic appliances. But the infrastructure is complex.

Also, if you consider the transition where recently the retailer scenario has changed, it's not only about going more online but everything that goes along with that. So the direct change, the direct contact with consumers, or a different way of dealing with consumers that have a relation with the retailer.

So you need to redesign, despite all these connected lines and that the dynamics have changed. Therefore, analyzing feedback is very important because whenever something is so complex, you need a powerful tool to simplify everything to get the few actionable feedback to address. And then implement actions accordingly. Otherwise, you can get lost in digesting information, trying to process it, and speculating over ideas. And those are not leading to maybe the right choice.

The question you asked me before about the approach to big data and everything: Well, if you don't have a strategy, if you are not already in big data processing, you better hurry up.

Hosker (33:54) I think there's probably a lot of companies out there that are a little bit behind with that. And like you said, we are very much at the early stages of artificial intelligence, and I think we're doing the basics. A lot of us are doing the basics well, but as you said, understanding that information is really key to this and being able to train models and that kind of thing. So, you're absolutely right.

I think there's still a lot more to be done, and when you can make sense of all this, it doesdrivedecisions to another level. But yeah, there are probably a lot of companies that still have some catching up to do. Fortunately, for De’Longhi, you guys are kind of at the head of the curve currently.

Paludet: Well, I hope so. I don't know if the first, but we were among the first to certainly have the tool to combine rating and reviews and also with the CRM information.

Hosker (34:57) Learning those data sets together has been incredibly powerful for you guys, hasn't it?

So bringing together that siloed information from marketing, customer reviews, customer contact centers and looking at that holistically across the whole business. Then getting feedback from, perhaps, product reviews that go into other parts of the business and then pulling information from your customer service center that even goes into marketing - it’s all quite new in itself, isn't it?

Paludet:I'm amazed by the amount of information, by the quality of the information, by the ability to perform also the comparisons of our products and our competitors’ products. It’s actually like we do the same thing as consumers do when they want to buy something. You know, they start comparing and etc. But then, when you imagine that we have a product portfolio with maybe 4,500 live SKUs, you need a bit of help to do that. Definitely.

Hosker (36:07) And there's a huge team of people. So, it's either an AI system or about 8,000 people in the call center.

Paludet (chuckles): Sorry, I want to say (because you just said a very important thing about the people), you can use fewer resources. You will use fewer resources, but you need some dedicated resources. Maybe also with a different education than the standard one.

People use this kind of thing; they need to understand data, they need to understand statistics, and they need to understand semantics and natural language processing. So, it’s all still relatively new, or in our industry at least.

Hosker (36:59) Massimo, thank you so much as ever. You've been incredibly insightful. I'm sure people watching this will have found that incredibly interesting. You are absolutely a trailblazer in this area of artificial intelligence and from a practical application point of view. I think we're lucky to have you as a customer as well. Thank you very, very much for your time today.

Paludet: You're very welcome. And I look forward to a long-lasting and mutual cooperation with Wonderflow. Thank you!

For more information about De'Longhi Group, visit their websitehere. Stay tuned for more of our client success stories in the future!

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