How to choose a location data provider

More than 20 questions to ask location-intelligence companies.

This is the first installment of my new Search Engine Land column, “On Location.” It will focus on local SEO, location-based marketing, location intelligence, relevant consumer behavior trends and online-to-offline analytics. I’m also interested in hearing from you about what topics and issues you’d like to see covered.

Mobile location data has become a critical and versatile tool for marketers. It can act as a kind of real-world cookie substitute (device IDs), identify audience segments, provide competitive insights and measure the impact of digital and traditional media on store visits and sales.

There are more than 20 companies that offer “location intelligence” in one form or another in the U.S. market. But not all location-data providers offer identical data coverage or quality. Indeed, there’sevidence to suggest that a majority of programmatic bid stream location data, which some providers use as their primary source, is either fraudulent or of questionable quality.

Brands, retailers and agencies working on their behalf should take advantage of location-based insights and attribution capabilities. Those that aren’t doing so are missing a significant opportunity. But choosing the right provider matters. What are the attributes or capabilities to look for?

To answer these questions I invited several companies in the segment (PlaceIQ, NinthDecimal, Placed and Foursquare) to offer their insights and recommendations. Many of their responses overlapped (i.e., around data sourcing and accuracy) but there were also differences in emphasis and unique answers — below.

Understanding where data comes from

The overarching recommendation from everyone was to gain a clear understanding of data sources and the ratio of first-party to third-party data. What percentage of the dataset is comprised of bid-stream data? Most companies will use both first and third party data, but do they have a process for expunging inaccurate data?

It’s important to note that data accuracy requirements can vary based on the intended use. For example, ad-targeting accuracy may need less precision than attribution use cases (did the campaign send people into stores?).

Other recommendations include assessing the sophistication of the company’s methodology, understanding whether the provider’s data has been validated by independent parties and how rich and complete the company’s dataset is.

Here are the specific questions and recommendations:

Foursquare:

• Coverage: How many of the total venues/visits are represented? How detailed is the metadata about a given set of venues?
• Accuracy: A mix of signals and sensors (i.e., GPS and cell tower signals, SSIDs, Bluetooth or beacon signatures) can help when distinguishing between places in densely populated urban areas. Marketers should look for multi-sensor inputs.
• Recency: How often is the data updated? What is the methodology for ensuring that any fluctuations at business locations are logged and verified in a timely manner?
• Sources: Datasets can be classified into three groups: first-party sources, third-party data aggregations and a combination of the two. Foursquare throws out more than 80 percent of third-party data that doesn’t meet data quality standards. Sources are important because there may be larger privacy and regulatory implications in certain regions.
• Contextual metadata: Contextual metadata indicates how much additional information is provided for a given location beyond the most basic attributes of name and address. This can be useful in providing a more complete understanding of a place, why people go there, or what’s unique about it.

NinthDecimal:

• Understanding sources of location data: How do you source location data? What is the breakdown of first-party data and third-party data? What percentage is bid stream vs non-bid stream?
• Making sure you are using data with strong density: Do you have a broad reach of consumers combined with a high frequency of seeing those consumers?
• Choosing a provider whose data has been third-party verified: Has a credible, independent third-party verified your data? Does that verification cover location data accuracy, location solution methodologies, data hygiene and privacy solutions?
• Using a provider with a broad scope of applications: How do you apply location data across marketing solutions? Do you support a range of services across audience creation, market research, measurement or media solutions?
• Having maximum omnichannel flexibility: Can your offerings go across more than mobile to be effective for all marketing channels? Is your data ready-made and do you have integrations in place to plug into the existing marketing stack (i.e., DSPs, DMPs, social platforms, TV platforms)?
• Unlocking the power of your first party CRM data: Can you map location data with first-party CRM data to create a more powerful understanding of the customer?

Placed:

• Employees: What percentage of the company’s employees are engineers and data scientists?
• Data sourcing: Where does it source location data?  What is the opt-in process?  Can I receive a list of apps to try and download?
• Verification: How do you verify the accuracy of the location data you are obtaining?  What process do you have for filtering the data for accuracy?  How much data do you throw out due to inaccuracies?
• First vs. third-party data: What do you consider first-party versus third-party data?
• Validating visits: How do you validate the visits you are reporting?
• Market share: What is your market share across partners, media channels, and advertisers?
• Business model: Do you sell media or targeting or are you pure-play attribution and analytics?

PlaceIQ:

• Basemap: Does the provider have a foundational understanding of the physical world or have they simply licensed a POI database?
• Movement data: Does the provider have a scalable and nationally representative portfolio of users?
• Technology expertise: Does the data provider have proprietary learning, cleansing, clustering, etc. to smartly fuse movement data and mapping data?
• Transparency: Does the provider share detailed, event-level data with clients and partners directly? Do they provide confidence scores for their visitation detection?
• Validation: Does the provider have a third-party marketplace valuation for their visitation data? Are they capable and willing to design or participate in valuation against truth sets?

Together all these questions form the basis of a very strong RFP and should accelerate your vendor evaluation process.