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How Location Data Is Reshaping Mobile Advertising and Attribution

How Location Data Is Reshaping Mobile Advertising and Attribution

With increasing smartphone penetration worldwide, marketers have rightly adopted the mobile-first approach. However, in a world of ad-blocks, marketers need to be careful of delivering content that is irrelevant or annoying.

Fortunately, access to location data makes it possible to create highly relevant mobile targeting campaigns by ensuring users receive personalized and useful content at the best possible time.

The value of location intelligence

Location data comes in quite handy to target mobile devices effectively, enabling real-time message delivery based on a device’s location. Besides, real-time location intelligence can be used to build audience profiles that make it possible to create highly personal mobile campaigns by applying the offline behavior of users to the targeting process.

According to the LSA Market Landscape Report, location-targeted mobile advertising is expected to reach $32 billion by 2021. The report says that “marketers across the spectrum have awakened to the importance of location data as a powerful and versatile tool to identify audiences, gain competitive insights and observe offline consumer behavior.”

It further explains that brands are beginning to use location data for insights beyond marketing. Some growing applications of location intelligence (identified by the report) that can give a brand a competitive edge include:

  • Identify audience segments (from offline behavior)
  • Understand consumer purchase intent and preferences
  • Match digital (and traditional) ads to real-world activity and transactions
  • Understand customer activity from an operational perspective (what is our busiest time?) to improve the customer experience
  • Gain competitive insights (where does the customer go and how often?)
  • Benchmark store/location performance (internally or competitively)
  • Enable more contextually relevant or personalized customer experiences
  • Predict earnings, financial performance, and potential M&A activity
  • Security and fraud prevention

Did you know that consumers prefer location-based ads? According to a Google study, 4 in 5 consumers want ads customized to their city, zip code or immediate surroundings.

In fact, more than 60% of consumers who participated in the study reported having used location information in ads. They said it was important to have the store address and phone number in ads on computer/tablet, and directions and the call button in ads on a smartphone.

Maintaining an omnichannel presence

According to Google, “6 in 10 internet users start shopping on one device but continue or finish on a different one.” This raises a unique challenge for businesses to be present on various channels a consumer expects them to be.

Besides, keeping their location data up to date on every platform where a consumer would turn to find them can be cumbersome for most brands, translating into missed opportunities for the business and a poor experience for customers.

This is where data amplifiers come handy. Data amplifiers refer to data publishers such as Google, Apple, Bing, Yelp and Facebook, and data aggregators such as Neustar that share a brand’s data with publishers.

By sharing their location data with these amplifiers, brands can effectively maintain an omnichannel presence in line with the expectations of today’s very demanding consumers.

Reaching out on social media – Using location data for creating targeted ads

Today, social media is an important part of every location-based marketing strategy. And why not? People use social media to interact, shop, share photos and even find information, making it the perfect channel for marketers to connect with their target audience. But how to do that remains a challenging question to tackle.

Using location data could be an answer to making your social media marketing initiatives more effective. Targeted advertising is an important area where location-based data can come exceptionally handy. Why?

Because, today, most of us happily share our location data with the numerous apps we use on our smartphones regularly. This presents an opportunity for marketers to personalize their content to people based on their current location, in real time! Thus, advertisers can effectively send different messages to people depending on where they are at a particular point in time.

Take a small example of you sipping a martini at your favorite restaurant. You are browsing your phone and receive an ad offering 50 percent off at a large brand. However, there’s no store nearby that you can reach conveniently. So, you ignore the message and continue to enjoy the evening at the restaurant. But, what if the same message was delivered to you while you were walking down a street where one of the brand’s stores was located? Chances are you would have paid much more attention to the advertisement then.

While this is a very simplified example, it must be noted that knowing where your customers are, and where they like to spend their time, can help you optimize your mobile targeting strategy.

Mobile attribution – Using big data to get a holistic view of a buyer’s journey

Attribution modeling allows you to determine the most effective channels of marketing for your brand. Until recently, the last-click model was most frequently adopted by marketers to determine the effectiveness of their marketing channels. But now, it seems that the last-click model is going out of fashion. Let’s see why.

Marketers use several tools to reach out to their customers including email campaigns, digital ads, television commercials, etc. However, the credit for converting a user generally goes to the medium that ‘touched’ the consumer most recently before a purchase. This is known as last-click attribution, a reference to a user clicking on an advertisement online. However, the last-click model only reflects on the last part of a user’s journey, clouding the importance of other marketing channels along the way.

To help you get a more holistic view of the customers’ journey, a data-driven, machine learning-powered attribution model, called data-driven attribution model uses sophisticated predictive algorithms to find and analyze data from multiple sources, assigning the conversion credit to the four most influential touchpoints in a user’s conversion journey.

Image Source: Optimizesmart

If you meet the minimum conversion threshold and Google analytics 360 suite view, the data-driven model is the incrementally better model when compared to the other models. In this model, credits are assigned on the basis of most recent conversion data and not according to the order in which various touchpoints appear on a user’s journey.

Regardless of the touch point where it is first, middle or last, the touch point which assists the most will get the maximum credit for the conversion.

Besides, location data makes it possible for marketers to effectively target omnichannel customers, most of whom start research on a smartphone but end on a different device. However, the last-click attribution model leaves such users out of the conversion funnel.

In a nutshell, location data offers much more than highly targeted ad experiences for brands. With increasing access to real-time location intelligence that is quite accurate, you can use location intelligence to gain competitive insights, solve the issues of offline attribution and create more personalized ad campaigns for your brand, resulting in more conversions.

Guest author: I’m Mercy, Marketing Manager at Dot Com Infoway with over 10+ years of experience in Digital Marketing. Dot Com Infoway is a 360° Mobile & Web solutions company that turns your ideas into world-class products and helps you reach your target customers.

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