KIND is supercharging its field team with elm data


The brand: KIND

KIND is on track to be the UK’s biggest healthy snacks brand. Originally founded in the US, where they’re now a $1.5bn business, KIND launched in the UK in 2015. In the last 6 years, they’ve already grown to an almost £20m business in multipacks and singles, and now have a team of 35. Two years ago, KIND was acquired by Mars and, 2020 aside, they are doubling year on year.

Stuart Ball, Head of Category and Customer Marketing, explains how elm is saving KIND time and money on data management and unlocking value from their field team.

The problem

“Most of our customers give us great data, but it’s disparate, scattered, and almost unusable. Making this data work for us was time-consuming and complicated before elm.”

‘Unusable’ data systems

“Most of our customers give us great data and, for our size, we’ve got a lot of it. But the formatting is horrific – it’s disparate, scattered, and almost unusable. Making this data work for us was time-consuming and complicated before elm. I didn’t actually have the resources, the time or the energy to know how to convert certain datasets into a pivot table, let alone a dashboard.”

No actionable insight

“Everyone from the General Manager to the Sales Director to National Account Managers (NAMs) and the field force need certain information. As the sole category data manager, I was unable to provide the level of insight that they needed. Reports were basic, scattered and I couldn’t drill down where I needed to.”

Time spend

“Extracting, consolidating and analysing the data across all our accounts used to take our Account Executive 1-2 full days every week. On top of that was the time I’d spend responding to data requests.”

The solution

Simplified data management

“One of my big remits this year was to simplify data. That’s exactly what elm is doing for us. I can log in and get visualisations which really quickly show me what I should be focusing on this week – for example, is Singles up? Has the Rate of Sale declined? elm’s simplicity means that everyone can use it, from people at Mars to our National Account Managers – our NAMs are now much less reliant on going to Category for support with retailer conversations.”

Actionable push reports

“Every Monday, elm sends us push reports with really actionable, practical information. They’ll flag any big fluctuations in sales or stock availability and say ‘these 14 stores had zero stock last week, but they should have’. I just hand that directly to the field team to put on their call list and they’ll go and they’ll fix it. Those sort of immediate, actionable things are really key.”

Promotional analysis

“Sometimes retailers will give their own promotional spend analysis but more often than not, you get nothing. elm lets you snapshot certain weeks when you’ve had a promotion and analyse the effectiveness of your spend. If you spend £10k on a promotion plus 50p per pack, you need to be asking, ‘did we get the uplift to justify this?’. And the tool just calculates that.”

The results

– £20-30k projected savings next year with elm
– 1-2 days Account Executive time saved per week
– 50% fewer internal requests for simple data retrievals

A data-powered field team

“Our field team has probably used elm more than anyone – they can log into elm whilst sitting outside a store in the car park, and easily check any issues ahead of meetings: ‘did sales grow last week, or decline? How does that compare to stores in this region?’ Mars has a large field team in the UK. With elm, they can check our availability at a glance – if we can identify an issue at 200 Tesco stores each week, it could be the difference between 10% growth and 10% decline for KIND.”

Money saved

“We were in the habit of spending £20-30k for the premium tier data package with some of our larger retailers, but the store-level data that this gave us is now extremely accessible in elm. elm’s functionality is as good as these costly retailer tools which can cost significantly more. It’s a perfect tool for a brand that’s between £1-40m that can’t afford retailer loyalty databases orNielsen – and even if you can afford those, you’re only getting a snapshot.”

“Retailers have an expectation of data, even if you’re a small brand”

Differentiation on data

“Retailers have an expectation of data, even if you’re a small brand. It helps you stand out from the rest if you have data to hand that’s useful and that you can make decisions from. One pillar for success at KIND is being a data driven business – these are the sorts of tools that make that a reality.”


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