In this article, we will show you how to use the filters available in the "Compare my performance with the competition" module to refine your analyses.

Using the filters: step by step

Step 1: Select the type of period you want to analyze

• 4-week period: Calculates performance over 4 complete weeks, following Nielsen period start and end dates. Unlike a calendar month, a 4-week period starts on Monday and ends on Sunday. Check the 4-week period calendar here.

• Year-to-Date (YTD): Calculates cumulative performance from the start of the first 4-week period of the current year up to the end of the selected 4-week period. Example: YTD P6 2024 runs from the start of P1 2024 (01/01/24) to the end of P6 2024 (16/06/24).

• Moving Annual Total (MAT): Calculates performance over the last 12 consecutive 4-week periods. Example: MAT P6 2024 runs from the start of P7 2023 (19/06/23) to the end of P6 2024 (16/06/24).

• Month: Calculates performance over a full calendar month.

• Week : Calculates performance over a specific week within the month.

Next, select the desired analysis period . For example, P13 2024 (01/01/2024 - 29/12/2024)

Note : You have access to 3 rolling years of data history.

Step 2: Select the Hierarchy to use

If you want to use a custom hierarchy, it must first be created via the "Create" module in the left-hand menu. Once created, it will appear in the module filters.

By default:

• Intermarché France: Nielsen Local (FR) hierarchy
• Intermarché Belgium: Aware Group hierarchy
• Intermarché Portugal: Nielsen Local (PT) hierarchy

For more information, see our article on creating a custom hierarchy.

Step 3: Select the Level Type and hierarchical levels to analyze.

There are three types of level available: Family, Subfamily and Segment .
You can then select one or more items to analyze (12 maximum).

For example, I want to perform an analysis at the segment level. I then select "Segment" in the filters. Next, the "Hierarchical Level" filter allows me to select up to 12 different segments from different families and subfamilies.

Step 4: Select stores

Select the store format (s), region (s), and specific store (s) to analyze.

Store format nomenclature by country and by brand:

Here is the breakdown of the construction for each country:

🇫🇷 ITM France

The value is a combination of the short code for the format and the area.

• Construction rule: {format code} + {average area}
• Format codes:
• • CO : Contact
  • EX : Express
  • SA : Superfood
  • SG : Super Generalist
  • HY : Hyper
    

Example: SG2000 designates a Super Generalist format store with an average area of 2,000 m².

🇵🇹 ITM Portugal

The value combines the full name of the format followed by the surface, separated by a space.

• Construction rule: {format name} + {average area}

Example : CONTACT 600 designates a Contact format store with an average area of 600 m².

🇧🇪 ITM Belgium

The value is defined by a unique letter code. Each letter corresponds to an average store area bracket (in m²).

• Construction rule: {area letter}
• Correspondence grid:
• • S : Less than 699 m²
  • P: from 700 to 999 m²
  • M: from 1,000 to 1,299 m²
  • G: from 1,300 to 1,899 m²
  • H: over 1,899 m²

2 methods of analysis:

• The "funnel" method:

The filters are interconnected. This means that by selecting the format(s) to analyze, Aware Analytics will automatically exclude the region(s) and store(s) that are not linked to that category.

• The direct approach:

Select the store(s) to analyze directly.

Note : All checkboxes are deselected by default. To further refine your results, you will need to manually select the relevant checkboxes based on your criteria.

Step 5: Select the transaction type

You can choose to display your analysis results according to the type of transaction:

• All (default) : the aggregated total of all physical store and e-commerce transactions,
• E-commerce : Drive-through and Home Delivery transactions
• Physical stores : In-store transactions

Once the filters have been applied, click the "Run" button to start your analysis.

Save time by saving your custom filters

For example, if you regularly analyze a group of stores, you can save this setting as a selection so you can easily reuse it, without having to manually recreate your filters each time.

Save a Selection :

1. In the "Settings" side menu, choose and apply the desired filters.
2. A new “My selections” button then appears below the choice of the analysis period: click on the “Save” icon to create a selection with the selected filters.
3. Name your selection, then save it.

Note :

• The personalized selections are specific to each dashboard.
• You can create up to 6 Selections per dashboard.