Geopulse Audience converts time-stamped location data into demographic, behavioral, and geographic user profiles. It is designed for mobile publishers, mobile exchanges, and DSPs who wish to better personalize apps, and target content.
Geopulse Audience does not require an SDK or an on-device presence. The product is designed exclusively for Mobile and does not require beacons or cookies: Factual creates user-specific audience segments based on location data you provide over time, and additional first-party data where available.
Factual’s privacy practices are TRUSTe certified. Factual does not pool data across partners and does not position itself as a data broker. Instead, we act as a ‘force multiplier’ for first-party data: we create profiles based on the locations of your users over time, and share these only with you and your authorized partners. Profiles we return do not contain personally identifiable information (PII).
This document provides further detail on Geopulse Audience and the individual user profiles we return.
Time-stamped coordinates are submitted to Factual with a user ID — the more coordinates provided, the more detailed profile can be created for your users. We create and enrich profiles over time, keyed on the ID provided to us. We begin recording geographic attributes with just a few data points, and expand to demographic and behavioral attributes as we see more. There is no minimum number of observations required to build a profile, but as guidance we suggest 200 or more data points distributed over a two-week window as a convenient minimum. Geopulse Audience is however designed to accept tens of thousands of points over the course of many months to create very rich and refined profiles.
Because these coordinates can come from any source – on-device geolocation, W3C browser API, geotagged images, or business check-ins – the service is designed explicitly to create profiles from intermittent, occasional, and even dirty data. A greater number of coordinates over a longer period of time allows Factual to increase confidence scores and add new attributes to the profile.
Geopulse Audience is a server-side solution; it does not require SDK integration to implement; instead, data is passed to Factual from your servers, processed, and returned.
Geopulse Audience has been especially designed to accommodate apps and advertisers that collect intermittent location — location data points acquired infrequently and irregularly over the course of a day. While Geopulse Audience can accommodate GPS traces or ‘tracking data’, it is optimized for location data collected by apps once or twice per session, or location data pulled from an advertising bid stream. These are analyzed over an extended period to identify repeat activities and patterns of behavior.
In essence, the system identifies and classifies specific Areas of Activity (AsoA) – locations that users frequent on more than one occasion. We analyze AosA to determine patterns of behavior and preference, and turn these patterns into geographic, demographic, and behavioral profiles.
Repeat visits create an ‘Area of Activity’
The following image shows the irregular and intermittent activity of a single user normalized into Areas of Activity; the size of the circle in the example indicates the relative frequency of activity within that AoA over the sample period. Here we see a hypothetical user’s activity in and around Los Angeles:
Areas of Activity are locations of repeat behavior. The size of the circle reflects its significance.
We then study general patterns of movement between Areas of Activity (AsoA) and rank them by importance. This also allows us to determine information such as home zip code, typical commuting start and end times, as well as diurnal behavior patterns to inform our predictive model.
Identifying the ‘home’ Area of Activity, returned at postcode level
The image above shows a clear pattern of behavior to-and-from a primary AoA that we tag as ‘home’, and capture in the profile. In addition to the locations, rank, and business categories of these AsoA and their relative importance, we also return a ranked breakdown of all cities, regions, countries, metro areas, and DMAs in a user profile. This information allows content providers to use geo context effectively to customize content events when a geo signal is absent.
We look at the time and location of these coordinate pairs over a period of time to build a general picture of a user’s interaction with an application, and return the specific attributes about a user that you find valuable, including:
The segment data is specifically designed to enhance the connection between an individual, and a publisher or advertiser. It helps serve the publisher serve correct local news and more relevant information, can customize content by location, and ensures only the most contextually relevant information is served at the right time.
A complete menu of segments (attributes) is available in the Geopulse Audience Segments documentation.
Most location data is of varying quality due in-part to the huge variance in its source and accuracy – from IP-based geolocation (almost useless), to cell tower (better, but still suspect), wifi location (acceptable), and GPS coordinate pairs (preferred). Geopulse Audience incorporates a number of data verification techniques that cleans it on submission. We do not require the precision or source of the geodata. Give the geolocation data to Factual and we will identify and discard untrustworthy points: depending on the application our tests show that we commonly disregard 15-25% of inputs as irrelevant to profile building. Throw it all at us, and we’ll sort the wheat from the chaff.
Privacy concerns surround any product that consumes user location; we take our responsibilities here seriously.
We aim to ensure that the entire audience remains current: users without activity for the past 90 days are not returned, but will be marked as ‘inactive’ on Factual’s internal systems; if we see data from these users in the following nine months, we renew the profile with the addition of new information. However, if they are not seen within a year they are deleted.
Factual exposes the audiences for the data sources with whom we partner. The Geopulse Audience Designer dashboard provides the means to query the data source’s audience data with specific criteria, estimate impression capacity and unique devices.
The Audience Designer dashboard allows you to create your own audience selections. For example, to create sets for “golfers over fifty” and “california costco shoppers”, you would create an Audience Set for each, and name “golfers-over-50” and “ca-costco”. You can select whatever naming convention you like, and there is no pre-existing mapping of set-criteria onto set-name.
Factual returns a range of geographic, demographic, and behavioral segments for each device, in addition to a few special kinds of segments:
Tailored Location Segments provide you with the means to create your idea of the perfect location-based audience, based on where people go: essentially campaign planners and marketers can select and audience based on a specific retail brand, categories of places, landmarks, or any set of places in Factual’s Global Places data. Tailored Location Segments can be combined with any other segments to construct the best audience for your campaign. Tailored Location Segments are returned as Audience Sets and must be used in conjunction with Geopulse On-Prem.
Factual indexes attendance for select brands across your audience, and records it on a weekly and monthly basis. This approach allows an immediate overview of who has visited select brands, whether they are frequent or casual visitors, and understand a more holistic view of audience engagement with a specific retail brand.
Brand Affinities are similar to Tailored Location Segments in that they analyze audience attendance at specific brands over time. Unlike Tailored Location Segments, Brand Affinities are pre-indexed (meaning that these are ready out-of-the-box) and they reflect high-precision, in-venue attendance, having been created with detailed store polygons.
We support over 150 brands and their in-store visits. See the Brand Affinities Documentation for a complete list.
It is important first to note that Factual does not have its own audience. Instead, we are a force-multiplier for first-party location data. We create audiences for publishers and return the data to them directly for app personalization, or we write their data to Google DFP or Google DMP on their behalf. We work in a similar fashion with exchanges: here we create audiences on their RTB data, and then share these audiences with DSPs for enhanced targeting, again, with permission.
The second critical aspect of our position in the data stack is that we do not provide a ‘hosted’ service: because 9 out of 10 use cases demand extremely low-latency responses, we provide on-prem software imaginatively called Geopulse On-Prem that acts as a transport mechanism and low-latency query store. We do however offer an Amazon AMI version of Geopulse On-Prem for those who need a quick-and-easy service to call.
Factual processes third-party location data, enriches it, and indexes it on our servers. The enriched data is then selectively ‘pushed’ your local Geopulse On-Prem instance.
This data can take one of two forms: an Audience Set, or an Audience Profile. An Audience Set is a collection of identifiers that subscribe to specific criteria, for example “Business Travelers in California”. An Audience Profile is a JSON representation of every user within the dataset, represented as an identifier with assocated key/value pairs. Audience Sets are lightweight and easy because they contain a subset of devices that subscribe to a select criteria, and only the identifiers thereof. In contrast, Profiles contain every known attribute for every user, and therefore are more cumbersome and bulky. Audience Sets have data requirements of about 100MB per 100MM users, while Audience Profiles require ~10-50GB per 100MM users.
Generally, DSPs and others working in ad-tech will opt for Audience Sets, while publishers and orgs with their own CMS may choose Profiles. The decision is made during the contractual process.
Factual has arrangements with MoPub and several other exchanges to create audiences on their data. With the permission of the exchange we make these audiences available to select Demand Side Platforms (DSPs) to enhance targeting relevance. Using a visual interface, DSPs query exchange audiences on Factual for specific campaign criteria, such as “Business Travellers in LA”. This query produces an Audience Set, a highly optimized, binary hash of the exchange identifiers for all devices satisfying the query criteria. Audience Sets are transferred to the DSP for local execution on Factual software at runtime.
The workflow looks something like this:
In the diagram above, the steps can be articulated as:
Geopulse Audience Sets are designed for real-time, low-latency, high-volume queries: the steps in orange in the above diagram are real-time, and usually take about a millisecond; the steps in yellow are asynchronous, but usually complete within a few hours.
Factual builds audiences for each Mobile Publisher on their data, and returns those audiences only to that Mobile Publisher. Timestamped location data from the Publisher’s servers is pushed to Factual, through a local HTTP server we provide. These inputs are associated with whatever User ID you prefer, including proprietary or hashed IDs. The inputs can be provided in a single dump or trickled in over time, but typically it will be a combination of both. The more coordinates that are provided, the more detailed profile can be created for your users (the service is asynchronous, so you can pass us coordinates when convenient). Factual can render the profiles as Audience Sets, or we can return the profiles to the Geopulse On-Prem server where they can be queried by ID.
Geopulse Audience profiles are collections of demographic, geographic, and behavioral attributes keyed to a specific Device or Proprietary ID. Factual builds these attributes directly from Publisher data: ID, timestamp, longitude/latitude, and any other available information.
Unlike Audience Sets, Audience Profiles are a very ‘data heavy’ exercise, and should only be used in circumstances where the profiles are being added to a CMS, or where targeting parameters cannot accommodate Boolean member sets.
In the diagram above, the steps can be articulated as:
Geopulse Audience Profiles can be queried in Geopulse On-Prem in under a millisecond, or extracted and integrated within an extant CMS or User Data Store. The steps in orange in the above diagram are real-time and usually take about a millisecond, while the steps in yellow are asynchronous — we materialize new profiles and augment current profiles on a regular cadence of a few days to few weeks, but, as this process is computationally very expensive, the specific timing is largely an artifact of the business arrangement.
We provide a detailed implementation document that outlines in detail how the data and services connect to your own infrastructure.