Glossary of terms
| Metric | Definition |
| Share of visits | A visual representation of the relative power (Visits at your locations / Visits at selected retailers) of all selected brands showing the share of visits (see above) for you and all of your competitors. The graph stacks to 100% to illustrate the proportion of visits you and your competitors have. For regional insights, an index has been set up comparing each player’s regional visit share to its national. An index exceeding 100 implies that the player’s visit share is stronger in that region compared to on a national scale. |
| Share of avg visits/store | Similar to share of visits, but taking into account the active number of stores a brand has during the selected period. It is calculated by weighing each player’s share of visits based on the number of active stores which allows for a more fair comparison of the market. |
| Fraction of visitors (%) | The % of all visitors in the total market (your category = you and all competitors as listed in the selection area combined - excluding other categories such as bio shops or paint shops) that visited at least one of the brands' locations for the indicated period. |
| % of primary loyals | The % of visitors that dedicated 50% or more of their total visits to the designated brand (based on the selected period). |
| % of secondary loyals | The % of visitors that dedicated between 25-49% of their total visits to the designated brand (based on the selected period). |
| % of occasional loyals | The % of visitors that dedicated less than 25% of their total visits to the designated brand (based on the selected period). |
| Avg frequency | The average frequency of all your visitors for the indicated period expressed in # of visits. 2.5 equals an average of 2.5 visits per visitor during the indicated period. |
| Avg frequency in the market | The average frequency of all visits in your category for all competitors in your category. Competitors not included are not counted to calculate the average. |
| Visit transfer | The graph illustrates the % of visits that were won or lost between brands in the category from the point of view of the selected brand (by default: your brand) compared to the previous month. It is a subset of all total visits and excludes first time visitors (market penetration gains/losses) and category frequency drops (e.g. over summer the average frequency drops, no visits are won or lost between brands). The graph illustrates the % flow of visits from one brand to another → from whom have I won/lost visits? For example, if one person dedicated 3 visits to your brand in a certain month and, the next month, that same person only dedicated 2 visits to your brand and 1 to a competitor, then the visit transfer will visualize the flow of that ‘lost visit’ from your brand to the competitor. |
| Total net result | The net result represents the % of your total visits that you won/lost to or from competitors compared to the previous period. Example: a positive net result of 12% implies that 12% of your total visits for the selected period were won from competitors. |
| Customer journey | Visual representation of all (relevant) visitors’ last 3 visits in the past 90 days. The last visit is represented on the right of the graph, the visit before that in the middle and so on. Each brand’s visits can be divided into 3 groups: Retention: what % of visits returned to my store (= loyalty)? Acquisition: what % of visits did I steal from (selected) competitors? Market entry (None): what % of ‘new’ visits did I attract (= no prior visit to any selected brand in the past 90 days) |
| Loyalty types shift | An overview of how all the loyalty types from the selected retailer shifted in the evaluated period (compared to the reference period). 'No customer' represents the number of customers that did not dedicate a visit to the retailer in either the reference or evaluated period (depending on where they are positioned on the alluvial diagram). |
| Weekday visit transfer | A visual representation of how visits are flowing across different days of the week, i.e. what day is winning/losing visits from other days or what retailers are winning/losing visits from other days in the week? |
| Avg retailers combined | The average # of retailers all your shoppers, including your loyals, visit during the indicated period. Example: 2.5 avg. retailers combined equals you and 1.5 additional brands on average per customer. |
| Combiner rate distribution | With how many other retailers did the visitors of the selected retailer combine? Visitors in that only combined 1 retailer exclusively visited the selected retailer in the designated period. |
| % combined | The % of visitors that visited both your brand as well as your competitor’s brand in the designated period. |
| Avg. weekly traffic | The average number of weekly passers-by for the selected location. |
| Traffic distribution per day | How the average number of weekly passers-by are distributed per day (weekdays and weekends), expressed in %. |
| Traffic evolution | How has the traffic at the selected location evolved over time, expressed in monthly or quarterly number of passers-by. |
| Traffic heatmap | The spread of traffic around the selected location, highlighting high-traffic areas & hotspots. |
| Popular hours & days | Distribution of traffic around the selected location per hour and day, expressed in %. |
| Nearby neighbours | Overview of all the high-traffic stores in the viscinity of the selected location. |
| Visitor selectivity | How much more selective is your brand in attracting specific audiences compared to the overall market during the campaign period? |
| Exposed selectivity | How selective are the exposed individuals for a specific audience compared to the overall population? |
| Shopping Center Location | This map provides an overview of where the analyzed shopping center is located. |
| Traffic Heatmap | The heatmap highlights high-traffic areas (hotspots) within the shopping mall. |
| Theoretical Catchment Area | This indicates the zones based on specific driving times, showing potential visitor reach. |
| Catchment Filter | The catchment filter allows you to focus on key figures within a specific area. This is a multi-select filter: if multiple driving times are selected, the key metrics will be summed. Selecting a single time frame (e.g., 30-minute drive) provides key statistics for that specific range, so in this example for all people who live between 20 and 30 min. The metrics include population size in the selected zones, average income, total income, and the estimated number of households in the area. |
| Service Area | This map illustrates where the shopping mall visitors originated from, limited to a maximum 30-minute driving time. You can interpret the map as follows: X% of visitors to the shopping mall came from municipality Y. The data is based on the last 12 months. |
| Origin of Visitors | This bar chart shows the percentage of visitors based on their travel time. It helps identify how many visits originated from beyond a 30-minute drive. |
| Combiner Rate | This metric indicates the percentage of your visitors who also visited a competitor within the same month. The value represents the monthly average over the last 12 months. |
| Frequency | This metric shows how often customers visit the shopping mall. It is calculated as the monthly average visit frequency over the last 12 months. |
| Socio-demo distribution | Shows the socio-demographic profile of the population within the theoretical catchment area, compared to the broader distributions in Belgium, Brussels, Flanders, or Wallonia. |
| Origin of actual passers by | This visualization shows where passers-by are coming from, based on a 15-minute driving radius. To see how many people travel from beyond this zone, refer to the bar chart next to the map. |