Miriam Carey

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Brands and agencies use anonymized location data to make better business decisions. From pulling data on a single point of interest (POI) to study and learn about customer behavior, to looking into POIs across an entire country to develop a better understanding of trends, location data derived from mobile phone usage can be a valuable tool. Here are some of the ways our clients have been using location data options.

Location Data for the Restaurant/Hospitality Industry

men in casinoGaming and Hotel Loyalty: One client recently looked at all the Las Vegas visitors who were members of their loyalty program to answer location-based questions such as, How far did visitors travel to get to Las Vegas? Where did they go while they were here? Which of my competitors’ locations did they visit? How long was their stay?

By learning more about their customers, they could better serve offers and deals at moments when those offers, and deals were likely to have the most impact. This kind of targeting lifted engagement and spend

Restaurant Locations – How far are people traveling to get to a restaurant, particularly restaurants that rely on repeat customers? Answering this question helped an agency make smarter ad buys on behalf of a restaurant chain, optimizing spend where digital, print, and broadcast ads would have the most potential to reach customers within the restaurant’s “drive zone” in each market.

Who is Walking Into Your Restaurants: We can provide data on the demographics of people entering a restaurant such as age, race, sex, income, and more, to help restaurants make smarter decisions about what kind of food or drinks to serve, specials to run, and audiences to reach out to.

Deterministic Location Data for Financial Services

Tracking Potential Disaster: When a fast food chain got hit with bad news, we were able to look at all the chain’s stores across the country to see if footfall was increasing or decreasing immediately after the scare. Our client, a hedge fund, was able to make a more informed decision – rather than following his gut.

Check on Footfall at Branch Locations: One bank conducted a study on footfall traffic at each of its branch locations to gain insights on how busy each branch location was and how patterns differed by time of day or day of week. With this data, they were able to make smarter decisions about staffing, operational hours, and even parking lot design.

Luxury Brands Leverage Confirmed Visits and Location Data

Check up on the Competition: One client, a luxury brand, wanted to know where their customers tended to go when they weren’t at their locations. Studying trends market-by-market helped the brand keep an eye on their competition to see where else shoppers were going. The result was not only a deeper understanding of the competition, but the brand was able to create richer affinity programs with neighborhood hotels, restaurants, and attractions to drive additional traffic to their locations.

Improve Marketing Automation with Location Data

Know your Customer: Make the most of your CRM. We help many of our clients make deterministic and/or probabilistic matches between email addresses and mobile device IDs. This helps marketers better leverage their own database to target specific customers on social media, or to get better results from CRM health and usefulness.

Trigger Location-Specific Promotions: There is no better time to remind a customer of a promotion than when they’re walking into – or near – your store. We work with agencies and brands to deliver location data that helps them target customers in this way.

Smarter Billboards: Studying information on traffic patterns for a specific stretch of road helps agencies who work with digital and print billboard advertising target locations for messaging.

Retail

When paired with foot traffic data, Google Floor Plan maps like this one provide valuable insight.

Optimizing Store Layout: Retailers who can provide us with floor maps of their store layout can request information about how visitors travel through aisles or sections of a store. They examine traffic patterns, look for cold spots, and conduct A/B testing on best layout options to optimize customer experience and sales.

Target the Right Demographic: See traffic patterns in key demographic areas and understand how a neighborhood location is most likely to have the signal density you’re looking for in a city.

Confirmed Visits: Location data such as confirmed visits can bring more clarity to a dataset. Know when a visitor not only walked by a location, and if they walked in or checked in.

Auto Dealers

Visualize Path-to-Purchase: When auto dealers gain insight into buyer intent, they can “drive” sales more effectively (sorry, we couldn’t resist.) With our location tools, they can gain insights on which lots customers are visiting in a regional area, and drill down into that data to see which area of the lot customers are spending time in to know which car brands are capturing the customer’s attention.

 

These are just a few of the ways our clients use data to gain insight, save money, drive sales, please customers, or broaden their business. Learn more about our location data and get creative – we never run out of ideas.

Find out more about our location data offering.

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For publishers, ad blocking represents the ongoing dance between revenue and user experience. According to IoT for All, that dance may move in a new direction: A.I. ad-blockers that identify ads according to their FTC-mandated signifiers.

Your personal experience of online ads depends heavily on the type and topics of media you consume. If you’ve never played a shoddy iPhone game or accidentally lost yourself in a clickbait farm, perhaps you’ve never seen those low-quality ads that are clumsy at best and deceptive at worst. What do I mean by low-quality? Here are a couple of the programmatic sins that drive millennials to pick up ad-blockers.

Torn seams

The average consumer has no idea how many moving parts a video ad entails. They just see a 30-second spot about deodorant. Poor media software or other structural errors can result in improper formatting, slow loading, and other tears in the seams. Viewers expect a smooth transition; having to sit through an ad longer because the ad is broken is a great way to sour user experience.

Déjà vu

Programmatic advertising is a godsend when working with high-volume inventory. However, when marketers aren’t careful in their delivery parameters, strange and annoying things can happen, like repeating the same video for the same customer over and over. Or repeating the same video for the same customer over and over. Or repeating the same video for…

Where’s the eXit?

This one’s especially egregious because it exploits users that don’t know any better. Since certain ad formats include a “skip” or “close” button, some of the more unscrupulous creatives will feature misleading visuals–like a pronounced “X” in a company logo–that fool inattentive consumers into a time-consuming click.

Thanks to infractions like these, the battle of the blockers is going to last us awhile. That’s why publishers need to consider alternate revenue sources, like monetizing their data. The Complementics Data Exchange helps publishers do just that: by installing a bit of code on site, publishers can sell anonymous behavioral data. Best of all, companies use this data to actually improve users’ experiences, instead of perpetuating a race to the bottom.

How Content Classification Adds Value to Mobile Data

If you spend some time on our new site, you’ll probably see a few mentions of our sister company, eContext. Why are we so proud of this partnership? It’s because Complementics takes already valuable Mobile Audience Data and enriches it via eContext to add an extra layer of understanding.

That probably sounds buzzwordy, so let me explain: eContext is a classification system that labels content according to 500,000 (very specific) topics. Those topics are organized into and taxonomy of 25 verticals and 20 tiers of depth. What does that mean? eContext’s structured labelling helps us group and interpret ambiguous content.

For example, suppose you have access to Audiences’ app usage. eContext can go beyond app store categories to get a granular understanding of users’ interests. Then, when you combine that structured, specific intelligence on app use with other dimensions of Complementics data, you end up with a hostile customer profile that reveals spending power, interests, and even brand loyalty.

Complementics Mobile Audiences marries empirical audience data–clear-cut items like location and demographics–with the kind of personal-preference information that’s notoriously tough to pin down. It’s that second half that relies on eContext, adding a deep understanding of content to a huge network of behavioral data.

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If you publish a website, extension, or app that sees a lot of traffic every month, are you optimizing that traffic as much as you possibly can? It’s hard work generating that much traffic – you should get the most out of it.

We can help.

Complementics Data Exchange

Our data exchange allows publishers to monetize their traffic by anonymizing and sharing behavioral data. All you must do is add a bit of JavaScript to your site, or implement our SDK to your app.

We developed our SDK in response to exchange members who were getting tired of downloading and sending reports and all the management time required. With the SDK, data is sent in real time without the need for reports and hassles. The Complementics SDK works with ADFA for Apple and ADID for Android.

What we collect

We collect a wide range of data and we make it possible for you to specify wat you want us to collect. From the basics such as partner and device ID, IP address, and SDK version, as well as location information and user interest data.

The data we collect is enriched and offered for sale via the exchange.

Publishers who participate in our program are paid monthly, or can work with us on a data share program. Our data is enriched through the eContext API (our sister company) and as the largest semantic text classification system in the world, it does a fantastic job of organizing data. You get a dataset that’s classified to 20 tiers, which can help you learn more about your audience and build more followers.

Want to learn more about our SDK? Download this PDF or visit our SDK page. Or just give us a shout – we’re happy to show you how it works – schedule an appointment here.

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We’re proud of our Location Analytics offering. Why? Well, we’ve got a LOT of data. In fact, we just reached the 500 million mark for mobile devices from which we collect data globally. We are also smart about the way we collect mobile data, and our offering shows that. In addition to all this mobile data, we’ve got offline data on more than 110 million American households.

Here’s how we put it all together to bring a wide range of data options to partners we work with.

Mobile data

We have mobile data from the Tier 1 carriers globally but we also track Tier 2 carriers like Telefonica and Virgin Mobile – on more than 500M devices.

We use cellular triangulation so to track up to 25 events per day with foreground and background tracking.  We can track up to 10 events per day with background tracking.

Where in the world…

To ensure accurate data, we use solid location tracking methodologies. We pull from GPS, Wi-Fi, and cellular triangulation sources to get our information. The result is accurate geolocation resolution, latitude and longitude information, time stamp and UTC codes, as well as country ID.

Footfall and much more.

Think of what you could do with this kind of location information. You could gain insights on what your competition is doing, or study how weather impacts sales in your seasonal locations. Test out ideas on increasing the curb appeal of your retail locations, or A/B test targeted mobile programs. There are a million ways to benefit from location analytics.

Want to learn more about it? We’d love to chat with you wherever you are in the world.