How Bosch uses retail data analytics to boost sales across retail and ecommerce channels

Finding actionable insights in the chaos of retail and ecommerce data is a major challenge. This is even the case for a global giant like Bosch, a company with 400,000 employees.

As Director of the Power Tools division of Bosch Canada, Matthew Bergum needed to take an innovative approach to managing retailer partnerships using data in Alloy. In a recent webinar we sat down with Matthew to explore how he is meeting these data challenges and maximizing sales with a small, nimble team.


Running a big business with a small team, empowered with POS data

You’re a big believer in Bosch being data driven and having a culture of being data driven at Bosch. Why is that important to you and how have you thought about leading your team to adopt a more data driven mindset?

Matthew Bergum:
Without Alloy, without really digging into what POS data provides us historically, we’ve really only relied on shipment data, what we have shipped from our warehouse to our retailers and to our customers. And that only really tells a very small part of the story, and it doesn’t allow us to speak intelligently to our customers about their business, their metrics and their targets.

So once we were able to bring all of our data from each individual customer into Alloy, it allowed us and our sales people — when they’re having conversations with their customers, with their merchants, their buyers about programs or line reviews — now we can speak intelligently and talk about the same data that they have in front of them. Without something like Alloy, it was virtually impossible for us to do that.

I’ve noticed as well that you manage a huge business. And I think you may not have a massive team commensurate with the size of the business. So how do you tackle wrangling all of the retailer data, the e-commerce data to make the right business decisions for your division with such a small team?

I’m not sure there are too many companies that would ever argue that they have more people than they know what to do with, but yes, our team is relatively small and nimble, and we have to rely on tools like this to help.

And when you think about not only Canada, Canada has some specific complexities that might be different than some of our US counterparts, but regardless of the country, every customer will send their data in a different way, whether it’s a flat file or EDI or a different way. And they’re all in different formats, some include different information. It’s a mess.

We tried to do it on our own. We’ve got a handful of — I mean, we have 400,000 employees and — we tried to figure it out and how to consolidate it. It was virtually impossible and required a lot of people and resources.

And so Alloy has really helped us bring all that together and consolidate that so we can see it all in the same place, in the same format at the same time. And so that’s just been a huge point for us.

Instead of spending all of that time trying to put all the data in one place and format it and clean it up, now our team — the same number of people — can spend that time looking at the data and gaining actionable insights and things that we can actually do with it, versus just trying to understand what it means.

Retail and ecommerce sales data collection and analysis

How dynamic is the data update in collecting the data from different vendor portals?

Every customer updates their data in different timeframes. For example, Lowe’s is a customer of ours. We get data from Lowe’s daily in Canada and we see that daily, I think we’re usually a day behind. So if I were to log in today, I would be able to see yesterday’s business, but to me, that’s phenomenal.

It really depends on the cadence that the customer provides. Alloy is usually very quick to get it in as soon as they have access to the data. We have other customers that only give us data in weekly chunks. I believe Canadian Tire is a weekly data dump for us, but as soon as we have that data, the next day, it’s in the system. So the roadblock is much more on the customer side versus the Alloy side in terms of timing.

How do you make sure that the sales data collected from the retailer is real sales data and not manipulated for the supplier?

It’s an interesting question. So there’s a couple of things I would say here. At some level, we have to trust that the data that our customers are giving us is accurate and there’s only so much verifying that we can do there, however I would say one of the things that we do often is we give ourselves a gut check.

Many customers, many large customers, have their own portals. They have other ways to look at the data in their portals. And we’ll give ourselves a gut check to make sure that everything we’ve imported into Alloy matches up to what the customer is seeing.

Back to what I was saying at the beginning, if the goal is to be able to speak intelligently with our merchants and our buyers and speak the same language and the same data, if the data doesn’t match up, then we look like we don’t know what we’re talking about.

So we do gut check that with our customers’ portals and sometimes directly with the merchant, but I’ve never run into an issue where we caught something or something looked off where the data was being manipulated in any certain way.

"Our sales people, when they're having conversations with their customers, now can speak intelligently and talk about the same data that they have in front of them. Without something like Alloy, it was virtually impossible for us to do that."
-Matthew Bergum, Director of Power Tools @ Bosch Canada

Finding insights in data analytics across multiple retail and ecommerce channels

What surprised you about any of the insights over the last couple of years that you’ve been able to see when you brought the data together?

The ability to see all of the different fulfillment methods, that’s what it’s called within Alloy, but in store, online, which type of online. The ability to see that in one place across multiple customers has been pretty phenomenal. And so that has been a huge win for us to see the data in that way, again, to answer all those questions and make decisions off of that. So that would be probably the one that we love the most.

When anybody asks me to demo Alloy or if I’m training somebody for the first time, I always jump to geographic heat maps. On one hand, it’s just really cool to see it that way. Again, something that we would never have had before, but it also gives us a lot of actionable insight. If you think about the pandemic, and especially in Canada where every province had a different strategy around lockdowns and capacity and retailers, it really helped us see where that was changing by province. Now as we see that shift back to digital, that heat map, again, it gives us a lot of actionable insight.

What about ecommerce data specifically?

If you consider our ecommerce data, one of the nice things about that is Alloy can actually see not only where it’s shipping from, for us, we have one warehouse in Ontario, so that doesn’t tell us much, but it’s much more about the zip code or postal code data. And so we can see where all of our e-comm drop ship business is shipping to. With the heat map, we can see which provinces, which regions are still growing, which ones are struggling, because of that shift back to brick and mortar.

So to be able to see by province in a really cool way is helpful. And then if you think about it from a — depending on the size of your team — if you have territory managers or in store demo associates or things like that where you really want to be able to break it down by geographic regions, whether that be by state in the US or by province here, again, it’s a great way to split the data up.

Overall, what advice do you have for companies who are looking to get a better handle on their retail and e-commerce data?

I think this is an important one and every company might have a different approach, but the first question I think is important to ask is what problem are you trying to solve? And really take a look at what are you doing today and what is the problem that you’re trying to solve?

For us in Canada specifically, it was an enormous complexity of data that we just could not manage and we really needed to see everything in one place. If we were ever going to get to a place where we were using the data that we have to make actionable decisions or insightful decisions, the only way to do that was to be able to find a way to put everything in one place, and it’s virtually impossible to do that yourself. And so that was the problem we were trying to solve.

It might be different for other organizations if you’re primarily with one retailer, for example, and you might have good data from that retailer. I haven’t really seen a retailer-specific portal that does what Alloy can do. And so, there’s a lot of other bells and whistles and features that come with putting your data into Alloy that I don’t think is possible in many other customer-specific portals.

And finally — generally speaking — what would you say are those critical success factors for undertaking a new data project?

For any company that’s looking at doing something like this, if you’re not with Alloy today or any new data project, or if you are with Alloy but you think that there’s a lot of room to improve, I think one of the things that’s been successful for us is — not only me, but the rest of our leadership team in Canada — being the real champions for driving our team to use and engage. And that compounds itself and we all continue to learn more and use more. It has to come from the top, and so that’s been successful for us.

I will say that a critical success factor or something you must be aware of is that anything like this is a lot of work. Our customers send data many different ways, and when you really start digging into it, you will find things that might be wrong on the customer side and require some cleanup.

But a lot of that work pays off exponentially quickly. However, it does take some work to get everything connected, get everything in, but once it’s done, it’s done for forever, and it’s just maintenance after that.

The other critical success factor I would say is Alloy was phenomenal with our team as we continued to improve that engagement. Abby spent hours and hours with our team training, helping build dashboards. What we would do initially was come to Abby with a problem or something we wanted to analyze and she would use that as an example to teach our team how to create a dashboard to solve that. And over time, now we don’t need Abby to do that for us anymore because our team knows how to manipulate all the data in any way they want. And so Abby and Alloy have been pretty phenomenal in helping train our team and it has to happen that way, otherwise we wouldn’t use it.


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