To compete in an omnichannel world, retailers and CPGs need store clustering and assortment planning based on objective data intelligence and customer-centric analytics

04.26.2021 | By Mark Speyers

Trust is at the foundation of so many things we do every day.  Trust can help us build relationships and make decisions that improve our decisions and our outcomes.  A lack of trust can prevent us from making the changes we know we need, because we aren’t sure if those changes will deliver the outcomes we expect.  Luckily when it comes to category planning and assortment, technology solutions exist that have been built with trust in mind – from data quality and AI-powered analytics to process integration and change management to ensure the success of end-users.

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Intelligent and objective analytics complement experience and instincts

Gina: I think this perfectly plays into the things that we’ve talked about with retailer and ask them about assortment optimization and clustering and they say, “Yeah, I really need to be doing that better.” And that desire for improvement is because they hear people like us and others say, “This is what you need to be doing. And you’ll get X amount of sales increase.” And they go, “Yeah, I want to do that, but I don’t know how to do it.” Right?

Julian: Yeah. The other thing I would say is that I have conversations regularly where customers ask, “Do I plan my assortments at a cluster level? Should I go store level?  Should the approach vary by category? I just don’t know”. And I respond, “Let the AI and analytics guide you.”

For example, we’ve provided scenarios that help bring this to life by letting the analytics show them that they don’t need to go to store-specific assortments in categories where they traditionally thought store demographics might have indicated they should – such as in decorations and accessories.

But then we would also look at some bigger, more complicated categories like wine and beer that traditionally would have been too hard to execute store-specific assortments with legacy tools, even though the analytics indicate that there is significantly more opportunity for sales lift if they go to store-specific assortments – and now they can have access to the integrated technology platform that not only provides the analytics but can also seamlessly support the planogram execution and store communication.

Gina: Exactly. Or even being able to recommend starting at a cluster level, assessing that information, and maybe seeing that there are a couple of outliers in a cluster. And then you move that over into assortment. You start working that assortment at a cluster level, and then you start drilling into the store and you start seeing that there’s performance in a particular store that is declining, is below what the cluster average is. Well, go in there, play with that assortment, see if you can turn that around and make it a positive. And then maybe you have five clusters and one store-specific planogram. And that’s okay because the system can manage that for you.

So, this goes back to a retailer saying, “I want to do this better.” We don’t just say, “Yeah, we can do that better.” We show them how to develop the analytics, and we bring it to life by demonstrating that we both understand how they operate today and have built the solutions needed to support those operations – without making them feel anxious about having to add something complicated to their already overflowing to-do lists.

Data quality and integration is critical to trusting the analytics

Julian: So, one of the things we asked in the survey is, “What would help increase your confidence level when making category decisions?” And the top responses are integrating customer behavior insights and reliability of data. Which I think, Gina, goes to what you were saying earlier.

Gina: Yes, this circles back to the question, “Why don’t you do these things?” And the answer is, because the systems that they are using today do not support that level of integration. So, what happens is they’re faced with a lot of manual human intervention, which leads to errors and a lack of productivity and means they lose confidence in the depth and quality of the data.

Julian: And we’re seeing this move to cloud solutions increase steadily. So, it’s very clear that this is the way technology is advancing. We were forward-looking and this is why we decided to make the change to the cloud five years ago and create the integrated platform we have today.  When you think about the hundreds of thousands of hours that have gone into developing these solutions over the past five years, it’s really hard to imagine anyone being able to start from scratch today and not be left behind.

Gina: Exactly. It’s all about the integration, the efficiency and productivity, the data quality and reliability.

Future proofing category management requires a partnership for change management

Gina: When we consider all these areas of improvement and change, to really get customers to a level where all of this innovation and integration is truly benefiting then, we have also evolved to become a trusted partner for change management. You approach these implementations a little differently from the change management aspect by understanding the business processes and relating that to how they will work in the platform or guide them through a better approach. This method leads to successful implementations with happy and engaged customers who aren’t looking at the need for custom development or enhancement requests. And so, there’s a big push in the organization, especially here in the US, to partner either directly with customers using our domain experts or with other third-party providers that might already be engaged with a given customer.

Download the category planning and assortment optimization survey executive summary and infographic >>

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