Activity: GeoPersona Segments - US

GeoPersona is an advanced analytics tool that identifies residential postal codes where people with high affinities for specific consumer activities (such as sports, dining, and entertainment) reside. It does so by analyzing people’s visitation patterns. For instance, it can reveal the postal codes in New York where sports enthusiasts reside by analyzing visitation patterns to sports-related locations like stadiums, playgrounds and sports retailers.<br/><br/>This particular data sample is for jewelry shoppers in New York, highlighting in which post codes you are most (and least) likely find audiences who frequent jewelry and accessory stores.<br/><br/>This analysis of complex visitation patterns and geospatial behaviors allows GeoPersona to transform raw mobility data into actionable insights. Businesses can use this sophisticated analysis to pinpoint where potential customers reside, significantly enhancing marketing strategies, optimizing site selection and improving customer experiences.

Why is GeoPersona Important?

- Strong Indicator of Intent: A physical visitation is stronger indicator of intent than simply browsing online. For example, a person who physically visits a movie theater is more likely to be interested in movies than a person who just browses for movie tickets online.
- Non-PII Data: With privacy guardrails becoming stronger with time, it will become more challenging to track online behavior at a device ID level, making aggregated insights the norm. GeoPersona does just this with postcode-level aggregation of affinities.

How does GeoPersona work?

Taking aggregated mobility data, we score each postal code against various interest segments with an Affinity Index, which is a measure of the level of interest for a given category in the specified postal code. The higher the index, the stronger the interest (or affinity) for the segment is.

The index is calculated using the following steps:

1. Use our strong Point of Interest (POI) database (68 million POI’s worldwide!!!) and segregate them by category
2. Assign each GeoPersona segment to related POI categories. For example, Sports Enthusiasts would be mapped to POI categories like ‘sports_stadium’, ‘sports_shop’, etc.
3. Compute the baseline for each region/country to determine the average number of visitors at a segment level
4. Calculate the average number of visits made by residents of a given postal code to the Category
5. Compare the averages of each postal code with the regional/national baseline for the segment to obtain the Index.

This data is non-PII and GDPR-compliant.

Dataset Attributes Include:

- Postal Code
- Postal Code Name
- Region Name
- Country Code
- GeoPersona Segment
- Affinity Index Regional
- Affinity Index National
- Quarter Range
- Population
- Number of Households
- Purchasing Power (Per Capita & Household)
- Demographic Data (Age, Age & Gender)

Country Coverage:<br/>Our data is accessible in the following countries: France, Italy, Spain, Germany, United States, Great Britain.

Additional Information:

- We provide data aggregation on a quarterly basis.
- Information about our dataset, including details on our country offerings and data schema, is available here:

1. GeoPersona Data Schema: https://docs.echo-analytics.com/geopersona/data-schema
2. GeoPersona Country Availability: https://docs.echo-analytics.com/geopersona/country-coverage
3. GeoPersona Methodology: https://docs.echo-analytics.com/geopersona/methodology
4. GeoPersona Segments Offered: https://docs.echo-analytics.com/geopersona/segments-taxonomy

Echo's commitment to customer service is evident in our exceptional data quality and dedicated team, providing 360° support throughout the location data journey. We handle the complex tasks to deliver analysis-ready datasets to you.