#Post-7 - category analytics - Role of data in category management
Data analytics, excel, Tableau
Before you delve into the retail analytics, I would encourage you to look at previous post to get the context:
To know more about category management process, click here
To visualize what kind of data you would be looking at, read assortment planning.
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Viktor Mayer-Schönberger writes in one of his books - Big Data: A Revolution That Will Transform How We Live, Work, and Think:
“In God we trust—all others bring data,”
Data is powerful. It gives you a direction. As a category leader, you will be working with tons of data. Your category decisions would be driven by the insights that you draw from multitude of data. (customer data, transaction data, product data, store data etc.)
You would want to see category performance and driver of your category. You need to identify trends in your category.
What are the key questions that you need to understand for your category?
what are the top performing (no. depends on the size of your category) products in your category? Sales wise & profitability wise. And why?
what are the worst products in your category? Slow-movers?
What are the suppliers / manufacturers whose products are doing better compared to other suppliers?
Which is the most important Geographical Region for the category and why?
Looking at trends, which manufacturer will hold highest category share in next FY?
Ok, Let’s see how that works. You can download the data and lets start answering these questions :
Category Data - The file includes data of:
Profit, revenue, price, volume from different manufacturers / suppliers
Geographical distribution of food category across region
Once you analyze, these data you will be able to see which manufacturers are doing better in terms of profit as well as sales volume.
Also I said earlier,
Moreover, the demand at location level is hard to predict as well as it’s an expensive. (More data you add, leads to more complexity, and that means computational cost).
To put it into perspective,
Insight ∝ Complexity
Complexity ∝ Accuracy cost
Once you are done with the analysis, leave a message in comment box. I will post the solution there.
Now let me share how data centralization and visualization can help you to achieve your category goals.
When I was working in my previous organization, we were used to look at end numbers of sales report as a category analyst. All these report will give you bits and pieces of your category performance, inventory level and all that but it’s difficult to connect the dot. That led to a long-term project to set up a centralized database (fetching data from umpteen no. of segregated places) and a visualization dashboard within the merchandising department. If you look at all the parameters in graphical format, it becomes easier to generate insights from your data, and you can make your decisions faster and in real time.
If you are running an e-commerce site, you can get your data in real-time basis. In future post, we will get to that. We also see what different dashboards can aid ypu in your decision-making.
Till then, Happy analyzing the data!
Image source : https://www.hiclipart.com/