The cost of misinformation: is low quality location data impacting your business?

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With the location intelligence and analytics market expected to exceed $16 billion by 2021, according to IndustryARC, marketers are clearly seeing the benefits of foot traffic data. Used to power audience targeting or measure media performance, location intelligence can be activated to support all stages of the marketing funnel. Unfortunately though, not all data is created equal, and too often marketers don’t consider the importance of both scale and accuracy. Poor data quality can have serious consequences that translate into ineffective advertising and lost opportunities, highlighting the true cost of misinformation on business success.

In this post, we’ll surface the risks of low quality data on marketers’ bottom line, and highlight the reasons why our media and measurement solutions are uniquely positioned to optimize marketing decision-making.

When Marketing Misses the Mark

With an impressive 71 percent of consumers preferring personalized ads, according to Marketing Dive, marketers and advertisers have taken note and are utilizing a range of data sets, including location, to power enriching geo-aware and behavior-based marketing efforts. No matter the use case, successful experiences rely on accurate data, as the impact of low quality data on campaign success can be significant. Here’s one example:

Imagine that an offer is sent during the wrong time along a customer’s path-to-purchase. If the customer deems the advertisement irrelevant to their experience, they will ignore the ad completely. For the advertiser, this means a missed opportunity to effectively engage their consumers, which translates to lower campaign engagement and lost dollars.

In addition to poorly-timed outreach hindering campaign effectiveness, inaccurate behavioral targeting will also undermine performance. Let’s walk through an example to illustrate.

A marketer groups consumers into a Health Nut segment based on historical visit data to high-end fitness stores and salad chains. However, if the fitness store is misidentified as a budget apparel chain, and the salad chain is deemed a burger joint, the customer profile is completely different. That’s exactly what often happens when businesses are tightly packed together like in cities, making it difficult to correctly match visits to the right venues. Getting these nuances wrong with incorrect segmentation will cause marketers to target the wrong people and subsequently see poor campaign performance.

The technology that powers our behavior-based advertising solution, Pinpoint, solves for this dilemma. Reaching 150 million unique audiences across desktop and mobile, Pinpoint provides both the scale and accuracy marketers demand. We ensure data quality by carefully validating third-party data that’s used for targeting against our first-party truth set—13 billion user-confirmed place visits—to ensure visit attribution precision, even in the densest of environments. Real-time targeting capabilities —powered by Pinpoint—also enables marketers to reach consumers at the right place and time. And by surfacing only the highest quality audiences, clients are more likely to experience a positive return on ad spend. In fact, 93 percent of campaigns powered by Pinpoint reach or exceed clients’ campaign goals.

So, before signing on with a location partner, first consider the impact that poor quality data would have on your audience targeting and engagement efforts.

How Customer Churn Costs

According to Hubspot, the marketing automation company, 74 percent of consumers get frustrated when online offers, ads, or promotions have nothing to do with their interests or preferences. Frustration as a result of inaccurate, irrelevant, or inappropriate ads and notifications not only derails a company’s brand perception, but also causes customers to churn altogether.

Creating proper personalization requires having trustworthy data, and MIT reports that bad data is all too common. Per their branded study featuring executives across a range of departments, less than 5 percent think that their data is within an acceptable level of error.

The quality of data used to measure online-to-offline campaign effectiveness is particularly scrutinized as location signals sourced from the bidstream are the hardest to dissect. These signals are limited to latitude and longitude coordinates and the timestamp around when an ad is served, which leads to questions around data quality for two reasons. For one, this third-party data is rarely validated for accuracy against any truth-set. In other words, there’s no additional vetting process to ensure that it’s not junk. What’s more, bidstream location signals are sporadic and can’t differentiate between a real visit to a location versus someone just passing by. In fact, up to 80 percent of a marketer’s ad spend can go to waste by targeting with unvalidated bidstream data.

Comparatively, first-party data that’s sourced from a proprietary SDK is more precise for offline measurement, as location providers have greater transparency into how and why companies are using it. Greater visibility also allows marketers to understand the audience breakdown of an app’s user base, and to correct for any biases that can contribute to the resulting panel data. Additionally, SDKs that monitor consumers’ movements while running in the background generate more robust, precise foot traffic data. This gives partners a persistent look into users’ movements, not just when an app is open.

That’s why Foursquare’s Attribution is the industry’s leading online-to-offline measurement solution. We rely on data from our first-party foot traffic panel to measure marketing effectiveness. Totalling 70 million unique devices—10 million of whom have background location sharing enabled— Attribution delivers scale and accuracy with the largest “always-on” panel in the industry. Compared to bidstream-sourced data, which is incomplete, data from our Pilgrim SDK is persistent, eliminating foot traffic blind spots. We carefully evaluate which partners utilize the SDK, as well as what app categories are represented in the panel to ensure that foot traffic insights reflect the real-world movements of today’s consumer, not just one segment. Venues are also mapped against proprietary, machine-learned sensor fingerprints, instead of manual outlines, which solve for GPS distortion in dense urban areas and multi-story buildings.

In other words, first-party data results in higher quality products. Only partner with companies that have access to this data-set so they can not only verify the quality of third-party data, but also strengthen the accuracy of their foot traffic panel.

Our Two Cents

Don’t compromise the quality of your marketing by ignoring the accuracy of your location intelligence. Remember that not just any data set will do—work with Foursquare and our suite of media and measurement solutions to reduce the cost of misinformation on your business.

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