By Geoff Michener, CEO and Co-Founder, dataPlor
Today, many advertisers have turned to mobile and location-based marketing to deliver accessible offers at scale. With it, campaigns can serve targeted ads to customers based on their location and increase impressions and sales in the process. It’s no surprise, then, that more than half of all marketing budgets favor location-based solutions.
But while a geospatial approach allows advertisers to craft personalized user experiences and increase client ROI, mobile ad rollouts regularly misfire—by some estimates, as much as two thirds of location-based marketing dollars are wasted because of low-quality data and mistargeting.
To protect their budgets, marketers need to work with accurate location and mobility data. Let’s review what geospatial data adds to advertising, why it often comes up short, and how agencies can find and vet geospatial data to foster successful campaigns.
What geospatial data adds to campaigns
Most mobile advertising campaigns rely on insights derived from location and mobility data. These datasets provide different perspectives on consumer habits and market trends. Point of interest (POI) data, a form of location data, provides the type of place, exact address, latitude/longitude, hours of operation, phone number, website, and even opening date for a popular neighborhood eatery. It might also shed light on complementary sites, such as retail centers or tourist attractions. Mobility data can complete the picture by showing footfall in the restaurant, how long patrons spend there, where they’ve traveled from, and where they go after their visit.
Armed with this information, a competing quick-service restaurant (QSR) can build a data-driven marketing strategy centered on mobile and geotargeting or geofencing. They might choose, for example, to chart a fence around specific sites in the region’s shopping hub—or even the competitor’s location itself—to serve customers with tailored deals. In addition to creating relevant impressions and increasing sales, this type of geospatial strategy can provide indicators capable of fueling decision making about future campaigns and even site selection.
Where mobile advertising comes up short
Though potentially powerful, geospatial advertising strategies also come with pitfalls. If the QSR mentioned above makes the mistake of working with inaccurate data, for instance, they might deliver their creative to the wrong mobile devices, at an inconvenient time, or to an incorrect location. The consequences of this go beyond just missed sales and market share, as a poorly executed campaign can annoy potential customers and erode brand equity.
At their core, these consequences are the result of messy datasets. On a granular level, a specific POI datapoint might not be the actual place that it claims to be, or it could be missing important address, website, phone, or hours-of-operation information. Flawed mobility data could cause other problems by leading to incorrect insights about peak foot traffic or average dwell times. This could lay the groundwork for a mobile campaign that concentrates offer delivery at moments where customers are scarce.
How to find and vet high-quality geospatial data
To avoid the common problems associated with mobile marketing, agencies need to make sure that their geospatial data is of the highest quality.
This is easier said than done: sources for location and mobility data are numerous, and it can be difficult to know where to start. It’s possible, for example, to find free location data online; however, these datasets come with their own problems. In particular, this data tends to be outdated or poorly collected, which can lead to higher spend in the long run.
For marketers, a common solution to these issues is to find a third-party data provider. Yet this route can also be difficult to navigate. While some providers sell raw data that needs to be analyzed and enhanced, others go so far as to offer platforms that make geospatial insights seemingly easier to grasp. But remember: while deriving insights from raw data can be costly and time-consuming, third-party geospatial data—particularly international datasets—can also contain errors.
If agencies are willing to add another line item to the ledger, it’s possible for them to enhance this data. If they’re not, there are concrete steps that they can take to choose the right data provider and vet their purchase upfront to avoid data quality issues.
To protect their budgets with a high-quality data buy, brands and agencies should first confirm that a potential vendor specializes in the kind of data that they’re looking for, as some providers tend to sacrifice quality for quantity. It’s also important to only purchase data that has been collated from a variety of confirmed sources. To confirm this, make sure that your vendor provides metadata and other indicators for every record. Examples of this might include confidence scores, open or closed status, or a particular POI’s opening date. From there, choose a provider whose data covers all the regions you require; if they only provide datasets for a single region, for instance, you can’t assume the quality of their data extends overseas. For example, providers who maintain comprehensive and up-to-date POI data in the US, where most businesses post publicly available online information, do not necessarily have the same insight into developing markets. Finally, be sure to pick a vendor that’s not under public media pressure or scrutiny for their practices—when it comes to data, not all press is good press.
By following these steps, marketers can ensure that any money spent on geospatial data will translate to smooth campaign rollout, more impressions and engagement, and satisfied clients. Doing due diligence upfront is essential to preventing wasted spend and headaches down the road.
