---
title: "Zoom levels"
url: "https://support.accurat.ai/en/article/zoom-levels"
language: "en"
last_updated: "2026-06-26T15:32:35.715Z"
---
# 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 |
| Moving 4 weeks | Weekly insights, taking both current and the previous 3 weeks into account |
| Quarter | Full quarter (Q1-Q4) |
| Year | Full year |
| MAT (Moving Annual Total) | Monthly or periodic insights, taking a full year into account ending with the current month or period |
| MQT (Moving Quarterly Total) | Monthly or periodic insights, taking both current and previous 2 months or periods into account |
| YTD (Year-To-Date) | Monthly or periodic insights, considering this year, up to the current month or period
Attention: YTD month starts from Jan 1st, YTD period starts from the beginning of week 1 |
### **📍 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 |
| Household composition | Basic: households with or without kids and singles
Additional parameters: division into young/older households and age of the youngest child |
| 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 |