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Merchandizing Analytics Case Study

Mercator Slovenia

Mercator is the largest supermarket in Slovenia, with nearly 500 stores. A data rich company, Mercator found it difficult and slow to extract meaningful information from their vast and complex data systems. Here is how 11Ants helped them.


At Mercator, the Business Intelligence team have had to spend large amounts of time, developing reporting for the rest of the business.

“We got a lot of ad hoc demands from different branches of the company. We lost a lot of time producing those reports. We realized, the process is ineffective, and we were searching for a solution to reduce the workload”.

Watch the video to learn how 11Ants has greatly freed up the time of the Business Intelligence team at Mercator and enabled them to put data and insight into the hands of business teams.


My name's Mark Ennis, I'm the manager of the Category Strategy team here at Fonterra Farm Source. Farm Source is, a rural retailer, we've got stores situated right the way across the country. 


The data that Farm Source uses from 11Ants helps us to make good decisions. We can really understand the success of different products, different promotions, and from a commercial perspective we can make sure we're making good decisions each and every month. 

Prior to 11Ants' onboarding, we had large amounts of data, but it was split across multiple systems - and it could be hard to access, and it could be hard to truly understand. 11Ants has given us an opportunity to aggregate that data and turn it into meaningful insight. Previously, we had access to a lot of data, but it was predominantly drawn from our data warehouse and most of that data was reactive. So we could quite easily see what had happened, but not necessarily why. 


Farm Source had grown reasonably year on year prior to taking 11Ants on board; but we felt that our data wasn't really going to enable us to move much further. The team would be frustrated because we'd be under pressure from the regions to make changes in the business which were unqualified. We didn't really have any tools to test whether or not decision making was going to make an impact, or if we did make a decision, whether or not it worked to the full extent that we'd hoped it would. But with 11Ants it's a lot easier to qualify whether a decision is something we should do, and then to measure the success after we've done it. We'd use 11Ants to get better insight into our data, particularly when we were looking at promotional and campaign execution. In one instance, we saw one hundred and eighteen percent increase in units sold by understanding how we could use better companion and flank products to support our promotional products and by simply repositioning where we had something in store. 


We get deeper insight in terms of ranging, which helps us make sure we've got the right products available. For our customers, it's essential that they've got the right products on the shelf at the right time. But given we've got a range of thirteen thousand SKUs available to account for all the nuances nationwide, we're able to really drill into the data and make sure it's the right products, in the right store, at the right time. 


One of the problems we had with our old model was getting the data out in a timely manner and getting useful information out of that. 11Ants allows us to get it out quickly and in a meaningful form, that means we're a more customer centric business. When we had to do a complex analysis previously, it was quite time consuming to get all the data out. Once we had extracted it, had to go into another format and then we'd ask the questions of it. If there was any changes to the parameters that people were wanting, it meant rerunning the report. Now that we have 11Ants, all the data is there at our fingertips and we ask the questions we want if we want to know something else and we just ask another question. 

What we liked immediately about 11Ants was how easy it was to get the data uploaded and then within an hour or two we'd have access to all that data - so really simple to do. 

11Ants allows us to use some science behind our promotional activity rather than just take a best guess or go on our historical knowledge about how a promotion is going we can actually look at some metrics and determine whether a promotion has been successful. 11Ants allows us to look historically at how promotions have gone, but all this also allows us the ability to look forward and design promotions that are more effective for our customers. 


11Ants just provides the data to us so quickly. 11Ants allows us to get information from our data almost immediately. In the past, we've had a lot of time spent getting data information out, sorting it into some sort of order for people, whereas 11Ants, the data is there and we just go in and ask the questions we want to, it immediately provides us some results and if we want to ask a different question, it's very easy to change the parameters and get a new answer. 


Farm Source as a rural retailer has a very diverse customer base. We have dairy farmers with huge amounts of land that come in to shop with us right down to your lifestyle block, who might have one or two animals on their property. So 11Ants allows us to segment the customers and understand their different needs and make sure that we are providing them with what they need. 


Until Farm Source started to use to use 11Ants, I don't think we realised some of the challenges we had with our data until we saw the opportunity to do things differently. And from that respect, we've really integrated 11Ants into our planning cycle and it's become a big part of our business. 

tangible business benefits

With the introduction of 11Ants to the Mercator business, the Business Intelligence Team is now able to:

  • Save a lot of time.

  • Produce instant, useful reporting for the business.

  • Focus on more sophisticated, valuable analytics.

  • Democratize insights across the business.

  • Increase data usage across commercial teams.

See what 11Ants can do

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