The Category Overview manual

In the top half of the report, you will find the results in Out-of-pocket, volume and units for the entire period, on the left in total and on the right period by period. This way you can see at a glance whether changes can be linked to a specific period, or whether it is a structural change.

Below that you can find the 2 ‘trees’. Each one starts with the turnover and always goes into more detail via branches. Allowing you to explain why your turnover is increasing or decreasing. The multiplication of the branch is always the result above it.

• 'Breakdown receipts’: we go deeper into a receipt to better understand the purchasing behavior. 
  • the first split is based on the number of receipts. This gives insights into whether you were on more or fewer tickets, or whether customers bought more or less per trip. The first can be improved by, for example, extra visibility or can indicate a problem with your offer. The second can be stimulated by having customers take extra, either through larger packaging or through benefits with larger quantities. 
  • the next split on the left benchmarks the receipts with the total receipts (is the in/decrease due to due to a general in/decrease in the number of receipts. On the right, we focus on mixing products from the category, or do they 1 or multiple SKU's. If this figure is high, it may indicate that there are many complementary products, or many similar products, which can easily be switched between. If your performance on this is lower than the category, this could be a sign that there may still be potential for new products or that there is a lot of competition and little loyalty. 
  • Finally, we check whether changes in spending per product are linked to changes in the purchase volume or a price change. Strong price increases can also have an effect elsewhere in the tree. For example, a customer may keep his purchase per trip the same, but he may reduce his frequency or drop out, which has an impact on the number of receipts. 
• 'Breakdown Households’: 
  • This tree is only available for families who have used their Xtra. Here we focus on families and their spending over all trips.
  • A first split looks at the number of families who buy the products and how much they spend on them. So it gives insight into whether new customers are being attracted and whether existing customers are spending more or less. 
  • Just like with the cash register tickets, you can then benchmark the number of families with the total number of families who visit the store. In addition, you can split the family’s spending into the number of cash register tickets they have on an annual basis (frequency) and how much they then spend per cash receipt.
  • The rest of the steps are similar to the receipts breakdown.
• Via the button you can find 2 more trees. These are similar but have a focus on volume, which can be handy when there are strong price increases. However, be careful that all articles in the selection expressed in the same volume unit.

Just like in the category tab, you will find the total Out-of-pocket, Volume or Units at the top, with the breakdown by brand or product group next to it, depending on the choice you have made. If you have both Colruyt and Collect&Go data, you can also opt for the Shop-Collect&Go split.

Use the ‘my performance/total category’ filter, this can make the graphs more readable for the brands on the one hand, but on the other hand you can also compare the product groups between yourself and the total category.

Underneath that you will find the results per brand or product group, with the results on the most important KPIs, with the customer KPI only available for Xtra users. When you adjust the filter at the top to volume or units, the KPIs will also adjust. You can find more explanation about these KPIs in the previous chapter ‘Category’.

Through this table you can see at a glance which KPI's are in/decreasing. The relationship between price, number of customers, frequency of customers, number of cash register tickets and spending becomes visible and allows you to immediately detect where the opportunities or pain points are.

Although the focus is on products, you can also choose to view the details at other levels (Category, Product Group, Product Segment, and Brand). If you have both Colruyt and Collect&Go data, you can also opt for the Shop-Collect&Go split. Additionally, you can adjust the KPIs, switching between Out-of-pocket, Volume, or Units (also in shares).

Use the filter ‘My performance/Total category’. This can make the graphs more readable for the brands, but it also allows you to compare the product groups between your results and the total category.

More explanation about these KPIs can be found in the previous section, titled ‘Category’.

Through this and the following table, you can see at a glance where growth or decline is occurring across various KPIs simultaneously. You can see the relationship between price, number of customers, customer frequency, number of receipts, and expenditures. This way, you can immediately detect where the opportunities or pain points are.

Just like in the previous tab, you can view the details at Category, Product Group, Product Segment, Brand, and Product levels. If you have both Colruyt and Collect&Go data, you can also opt for the Shop-Collect&Go split.

Note that the customer KPI is only available for Xtra users. When you adjust the filter at the top to ‘Volume or Units’, the KPIs will also adjust. More explanation about these KPIs can be found in the previous section, titled ‘Category’.

Through this and the previous table, you can see at a glance where growth or decline is occurring across various KPIs simultaneously. You can see the relationship between price, number of customers, customer frequency, number of receipts, and expenditures. This way, you can immediately detect where the opportunities or pain points are.

In this tab, you get more insights into who buys your products. We segment in 3 ways:

• Region: based on where the Xtra user lives 
• Age bin: based on the user’s date of birth, which they provide when they sign up for Xtra. In a few rare cases, we do not have the date of birth, then we indicate this via ‘NA’. When there are several Xtra users in a family, we use the age of the Xtra code that is most used. 
• Household type: in addition to age, we also determine whether there are children in the family. We determine this based on a model, via their Xtra purchases and is updated every month. Customers who do not often use their Xtra, cannot be categorized (called ‘NA’). When there are several Xtra users in a family, we use the age of the Xtra code that is most used. 

For each group, we measure 3 KPIs:

• % shr Out-of-Pocket: How important are the Product Group, Brands or products (choose top right) within each group in turnover. This gives the preference of certain groups for certain products.
• OOP / HH: the amount that a family in the segment spends.
• % HH bought the product: The % of households that buy the selected products.

Based on these KPIs, you can easily determine within which groups you have potential. Do you see a group that spends a lot, but still has a low penetration, then there is still potential here. Are your products popular with families with high spending?

Through the filters at the top, you can go up to your own products. If you make your own group of products with articles from competitors, then the rules apply, as usual (see chapter, how do I adjust the report).

In the previous tab ‘Customer Profile’ you can see per segment what the performances were, but you can’t see how important each group is. You can determine the importance of each group here, for the 3 segmentations we offer at different levels (Category, Product Group, Product Segment, Brand, and Product).

If you have both Colruyt and Collect&Go data, you can also opt for the Shop-Collect&Go split.

Through the menu on the right, you can choose which segmentation you want to see the details for (region, age, or household).

The graph shows the sales at the top per period at Brand and article level, for the sales (Out-of-pocket, volume and units), % HH bought and volume per trip.

If you had a product switch, a product launch or a temporary out-of-stock,  you can easily check this graph what the impact is on sales, and what the impact is on the number of households that buy the product or how much they buy from it. What to do ...

• for product changes or out-of-stock: do customers still buy my products as much and what is the impact of a packaging change on the amount a customer buys, before and after. 
• for a product launch, you can check how the new product is doing compared to your other products on number of customers and volume per customer. Keep in mind that the distribution of the articles is about the same, otherwise you certainly cannot compare the penetration. Similar articles from competitors can be chosen as a benchmark, but at least products from 2 different manufacturers must be chosen. If these factors are not met, you can always opt for a Launch pack.

Sometimes it is useful to download all data to be able to use in internal reporting or to have a compact overview of all available KPIs.

You can select the level of detail yourself, ranging from total category to article level. You have 2 levels that you can set. You can use this to group products (put all products of a brand together), but you can also use it to determine the level of the ‘others’, combine your product segment with brand, instead of category with brand, then you will have more detail for the other brands.

There are 2 tables that you can download:

• All KPIs for the chosen period (MAT, YTD, …) for both this year and last year. 
• All KPIs per period (Quarter, month, promo period,…) for the current year. If you also want the previous year, you can adapt the reference, and then you can also download the previous year.

Through a number of funnels, we provide insights into where there is still potential:

• Chain: the result on total Colruyt LP, OKay or Spar 
• Category: the total performance of the category 
• Product group: a level lower than the category 
• Supplier: your total performance within the product group 
• Product: finally the result of the chosen product 

Based on the chosen product (top right), the product group, the supplier and the product adjust.

The different funnels are built on the basis of a different KPI:

• Store visits: number of cash register tickets 
• Households: number of customers 
• OOP/trip 
• Frequency 

Based on these factors, you can see where there is potential:

• Do we notice that in the number of receipts that the difference between supplier and product group is limited, but that there is a large drop-out between category and product group, then it will be especially important to further develop the product group and to focus on extra visibility and demand. 
• Do we see that the Out-of-pocket for a product is rather limited, compared to the product group. Then you can focus on trying to increase the volumes per customer. Keep in mind that there are multiple products in the first levels. When you see in the ‘Category’ tab in the trees that many different SKUs are being bought, it is logical that the Out-of-pocket per trip is higher in the category. 
• In the frequency, you can see how many times a customer visits a store on average, how many times they buy something from the category, product group, brand or product group. When you see that the category is only bought once a year, then it doesn’t make much sense to work on frequency with your offer.

Here you can find an overview of the stores, along with a number of KPIs: what is the average receipt value, how many products does one buy and how much % of the turnover is represented by Xtra customers.

This overview is especially important when you do an analysis on SPAR, because it gives an overview of all the stores that are included in the data, along with which type they belong to: SPAR CG, SPAR Compact CG or SPAR Other.