PiinPoint's Geosocial Segments feature adds colour to your trade area analysis by using location-based social media data to discover the unique behaviours, interests, and beliefs that characterize any area. Developed by Spatial.ai using billions of geotagged social media posts, this rich and constantly evolving dataset aggregates the personality of a neighbourhood.

In our most recent product release, PiinPoint allows users to explore Geosocial segments in bulk, by adding segment concentrations and rankings to our Comparison Reports.

Image 1. Geosocial Segmentation from Spatial.ai is now included in PiinPoint's Comparison Reports feature.


One of the greatest ways to strengthen your decision-making via location analytics is by using a myriad of data sources. When you add Geosocial segmentation to your analysis via Comparison Reports, you can quickly identify behavioural and social trends that are occurring across a set of locations:

What's New

Geosocial segmentation data was previously only used when looking at individual Trade Area reports. Now, segments are also displayed within Comparison Reports (along with your POI data, Competition, and Demographics), through two new components:

    For those who have a clear understanding of which segments they want to optimize for, this new feature release will allow you to quickly rank a set of locations based on the concentration of your ideal Geosocial Segments.

    Image 2. Ranking 6 potential new trade areas for Waves Coffee by the ideal Geosocial Segments for this coffee shop, such as Coffee Connoisseur and Ingredient Attentive.

    You can use the Rank By feature to sort the sites based on a specific segment.

    If you don't already know which geosocial segments are most important for your concept, this feature update allows you to quickly discover what segments are most highly concentrated across all of your locations (or any set of x,y coordinates!).

    Geosocial data in Comparisons reports offers a powerful tool to reverse engineer your market research and identify new supporting characteristics and criteria that you can use in site selection. There are a few different use cases where this could be applied:

    1. What's going on across my store locations?
      Discover personalities and behaviour at your existing locations. Prioritize a high concentration of these segments then when searching for sites in new markets.

      💡 You could even build separate reports for a specific set of locations that are high performing, which you'd like to optimize around.

    2. What's happening at my competitors locations?
      How do the personalities of visitors to your competitor's location differ from your own?

    3. What's common at an anchor tenants' locations?
      How strong is the synergy between you and your co-tenants? Do you actually share similar customer types or are there other concepts which have a higher concentration of your ideal segment profile?

      Image 3. Most Common Geosocial Segments addition

    If you didn't select the right segments before building the report, you can add or remove the selection of segments that are included with a new Edit menu.

    This Edit menu also gives you the ability to edit Demographics, POIs, or the Comparison trade areas all in one easy menu.

    Image 4. The new Edit menu in Comparison Reports. Simply hover over the "+" sign to reveal the datasets to adjust.

    Still got a question about Geosocial data in Comparison Reports? Don't hesitate to contact your Customer Success Manager in the app or email support@piinpoint.com.

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