Zoom levels
Almost each and every report in our report library can be configured by adjusting the zoom levels (or filters) during the report setup. Here's an overview of some of our most common zoom levels.
Please note that zoom level availability depends on your active sector and country.
🗓️ Time periods
| Time period | Description |
|---|---|
| Day | Specific day of choice, e.g. 25th of December |
| Week | Full week (Mon-Sun) |
| Week (with weekday) | Full week, including daily insights of the selected week |
| Commercial week | Full week in line with internal leaflet / promo calenders (e.g. Wed - Tue) |
| Month | Full month (Jan - Dec) |
| Periods | Examples: 4-4-4 / 4-4-5 / 4-5-4 weeks |
| Quarter | Full quarter (Q1-Q4) |
| Year | Full year |
| MAT (Moving Annual Total) | Monthly insights, taking both current and previous 12 months into account |
| MQT (Moving Quarterly Total) | Quarterly insights, taking both current and previous 3 quarters into account |
| YTD (Year-To-Date) | Monthly insights, including all months from the start of the year up until the selected month |
📍 Store groups
| Store group | Description |
|---|---|
| National (= default) | All customers in the entire country |
| Region-based | Regions: FL/WL/BXL (BE), North/East/South/West (NL), Bundesländer (DE), Régions (FR) Nielsen regions: I - VIII (depending on the country) Provinces |
| Assortment-based | Clustering of all stores that offer a specific assortiment or that (should) attract a specific segment |
| Competitor-based | Clustering of all stores that are located nearby a specific competitor or category |
| Location-based | Clustering of all stores based on specific geographical parameters, e.g. urban vs. rural |
| Market-based | Clustering of stores based on market trend (fusion, takeover or bankruptcy), e.g. track all stores that were taken over by retailer X Examples: Intermarché X Carrefour (BE), PLUS X Coop (NL), Casino Group X Auchan / Intermarché (FR) and Real X Edeka/Rewe/Kaufland (DE) |
| Period-based / like-for-like | Clustering of stores during a selected reference period. The same set of stores is then also used in the evaluation period to exclude newly opened / closed stores, takeovers, etc. |
| Custom | Combinations of abovementioned store groups or other relevant parameters are discussable Examples: franchise vs. non-franchise / large stores vs. small stores / areas around distribution centers / ... |
Competitors can be included based on: driving time / distance, bird's eye view, visit radius, etc.
👤 Customer segments / audiences
| Segment | Description |
|---|---|
| Social class | Division into 3 groups (low-mid-high) based on the customer's income (linked to your home location) |
| Age groups | Division into 4 groups: 18-25 / 25-45 / 45-65 / 65+ |
| Education | Low / middle / high education level |
| Gender | Male / Female (based on behaviour in past year) |
| Household composition | Basic: households with or without kids and singles Additional parameters: division into young/older households and age of the youngest child |
| Loyals | Occasionals and Secondary / Primary loyals (check glossary for exact definitions), i.e. frequency-based loyalty segements (e.g. 2 monthly visits to category X) |
| Retailer-based | All customers that visit a specific retailer or combine specific retailers (e.g. 'Lidl customer' or 'Lidl X ALDI customers') |
| Category-based | All customers that visit a specific category: fitness users, bakery/butcher visitors, pet shop visitors, supermarket visitor, garden lovers, ... |
| Custom | Combinations of abovementioned segments or completely new segments are discussable |