Podcast | Category Management with dunnhumby

[ 0:00 ] Rhiannon: Hi, and welcome to our brand-new podcast series, Category Management with dunnhumby. I’m Rhiannon, dunnhumby CPG Category Management Insight Lead, and I’ve spent the majority of my career helping brands and retailers unlock the power of data to better serve their shoppers.

[ 0:19 ] Ruby: And hi, I’m Ruby, Customer Success Manager at Virtual Store Trials, or VST for short. We help CPG brands and retailers make smarter decisions about what products should go on the shelf and where they should go.

[ 0:30 ] Ruby: So we turn something as overlooked as planogram data into an innovation tool, reshaping how retailers and brands make decisions. For us, it’s really not just about managing categories better, it’s about making category growth the main focus.

[ 0:41 ] Rhiannon: Yeah, exactly. And that’s why we’re going to be launching this podcast series. So over the next couple of episodes, we’ll dive into how tools and new ways of thinking about data like planograms can completely transform the way category managers work and how they drive growth.

[ 0:54 ] Rhiannon: So let’s start by setting the stage. The grocery industry has seen huge changes over the last few years, hasn’t it? But category management practices have stayed largely the same as they were 20 years ago.

[ 1:04 ] Rhiannon: So back in the early 2000s, dunnhumby led the way by making transactional and customer data available to brands, giving a view into shoppers’ baskets to track trends and make better decisions for the first time. But what’s always been missing from that conversation is in-store data.

[ 1:19 ] Ruby: Yeah, so for years, category management relied on manual processes and limited visibility. However, now we have the in-store data alongside the transactional and customer data, you’ve got a much clearer picture of what’s actually going on.

[ 1:29 ] Ruby: Otherwise, you can never know whether sales have gone up because of a trend or because a brand doubled its shelf space. Like, if you’re managing over 3,000 stores, how could you know unless you visit every single one of them?

[ 1:38 ] Rhiannon: Yeah, it’s a completely unachievable task. So what would you say then is your biggest bugbear with how categories are managed now?

[ 1:47 ] Ruby: So one of our biggest frustrations is how much category management still relies on the spreadsheets. Now, everyone today is talking about AI, but AI is like a shiny new sports car, and here’s the critical point: clean, processed data is the fuel that makes AI powerful.

[ 2:00 ] Ruby: AI built on messy spreadsheets is like a sports car without fuel. It might look good, but it’s not going to get you anywhere. The data needs to be clean and in a consistent data model. And once you’ve nailed that, brands can really start to unlock exciting things with AI.

[ 2:13 ] Ruby: And I know it doesn’t sound really fun and glamorous, but it is what really matters to us.

[ 2:16 ] Rhiannon: Yeah, definitely. And historically, getting your hands on in-store data was not particularly sophisticated or robust. So brands would have to physically go into stores, hope they pick a store that had a representative range, take some photos, put those photos into PowerPoint slides, and then just try and digest it all.

[ 2:40 ] Rhiannon: But to make the process 10 times harder, 2020 hits. All of a sudden, we’re not able to visit stores as freely as before, right?

[ 2:49 ] Ruby: Exactly. So suddenly, we’re in the middle of a pandemic, and that’s when we realise there was a hidden treasure trove of data sitting right there in the form of planograms. And planograms, for those who might not know, are the blueprints for how products are laid out on shelves.

[ 3:04 ] Rhiannon: Yeah, and although planograms have been around for a while, they’re built for supply chain purposes, right? So they weren’t even designed to help category managers figure out how to grow their categories, and it just tended to involve a lot of white boxes on a page.

[ 3:15 ] Ruby: Exactly. And even where category captaincy exists, where a brand leads the planning for a category, planogram data wasn’t particularly freely shared. And that’s because it often contained sensitive data, like margin data, that retailers just wouldn’t want to risk sharing.

[ 3:28 ] Ruby: But now new technology is changing the game so that the data that’s shared can be much more selective and secure.

[ 3:35 ] Rhiannon: So, Ruby, can you take us through what is different now? So why can brands and retailers finally use this data for something that’s transformative?

[ 3:43 ] Ruby: So this wouldn’t have even been possible 10 years ago. We’ve now got cloud-based computing providers like Snowflake that can process massive data sets securely. And to give you an idea, just taking Tesco products, their store variations and planograms, it all adds up to over 7 billion rows of data, and that’s every single week.

[ 4:10 ] Ruby: And processing that kind of volume just wouldn’t have been possible even a few years ago, but now it is.

[ 4:15 ] Rhiannon: Yeah, it’s a really complicated data set. Um, that’s why we’ve been wrapping that up into something that’s actually useful and usable in the form of planogram publisher.

[ 4:25 ] Ruby: Yeah, so that’s where our web-based platform comes in. It’s designed specifically to make planogram data useful for CPG brands. So with planogram publisher, brands can finally see how their products appear in-store, and that’s across thousands of stores, just at the click of a button.

[ 4:37 ] Rhiannon: And I’ve seen first hand working with dunnhumby how that can be an absolute game changer for category teams. So what makes that different from the traditional approach?

[ 4:49 ] Ruby: Great question. So planogram publisher doesn’t just give you snapshots of the products in-store, it also lets you track changes over time. So gone are the days of searching on a shared internal drive for what the person who used to do your job created years ago.

[ 5:02 ] Ruby: We’ve got over two years of historical data, so brands can analyse trends, they can measure the impact of changes and get a really clear picture of what’s actually happening on the shelf.

[ 5:21 ] Rhiannon: And that’s where it all comes together, isn’t it? So when brands can combine planogram data with transactional and customer data, you can suddenly answer questions that you couldn’t have before.

[ 5:40 ] Ruby: Yeah, exactly that. So they’re no longer having to guess. They can see if their sales went up because of a promotion, a trend, or because they have more space on shelf. So planogram publisher is providing that missing piece of the puzzle, and it’s giving them the visibility that they really need.

[ 5:53 ] Rhiannon: ‘Cause growing a category is really hard. So every piece has got to play in harmony, you have to understand the strengths of each section, how they’re interacting with one another, and planogram data is really integral to that, giving brands the power to achieve exceptional growth.

[ 6:06 ] Rhiannon: So that’s the mission: smarter decisions, better collaboration, and bigger focus on category growth. So what can you expect to hear from the rest of the series? Well, in episode two, we’re going to be talking to Tesco and some of our friends from the CPG world about how planograms can improve collaboration between brands and retailers.

[ 6:28 ] Rhiannon: And then episode three, we’re going to be going all in on the practical side of things. So using a couple of real-world examples to show how data-driven approaches can revolutionize category management.

[ 6:48 ] Rhiannon: And then to round off in episode four, we’re going to be looking ahead to the future. So exploring how planograms could become a tool for innovation and shopper understanding.

[ 6:56 ] Rhiannon: So I hope you listen along to the rest of the episodes with us, and thanks for tuning into episode one.

[ 7:03 ] (Podcast ends)