Posted by Ashley Osgood
The adtech ecosystem is in the middle of a fundamental shift in the way it conducts user targeting. With the amount of user intelligence and precision location technology capabilities available today, combined with an audience that is increasingly more receptive to relevant messaging, advertisers need to have a plan. What’s the most plausible way to successfully transition from the “okay” strategy of today to the advanced targeting of tomorrow?
Join us as we take a deeper dive into understanding the complete view of location and how you can use context to take your audience targeting to the next level.
The webinar will cover the following topics:
Location-based ad targeting means more relevant content for consumers, higher ROI for brands, and more revenue for publishers. In order for location data to be actionable, it must be both accurate and precise.
When you deliver the most relevant content to your audience, they are much more likely to engage because it no longer feels like advertising. Increase clicks and conversions in your campaigns by allowing brands to target their audiences more precisely.
There are a few ways, depending on the startup.
Location-based context will allow publishers to categorize the places that users are accessing their app (the user’s location services must be turned on) so that they can aggregate information by things that make more sense than looking at usage by each individual coffee shop, retail store, airport and so on.
Once publishers have this location data, they can then roll up places by Brand (Dunkin Donuts, Starbucks, CVS, Walmart, etc.) or Category (retail, pharmacy, coffee shop etc.) instead of trying to make sense of each address or location point.
Publishers can then compare their Vital Ratio (which is defined as your app functionality usage / total visits) across these locations to see if users are getting the value expected or if they are finding the functionality they need in the place that they are. Understanding this will help publishers prioritize how to design for place.
Enriching data with accurate and contextual location information can help make sense of ad requests. Linking ad requests to Personas and tagging device IDs with demographic information can give DSPs insight into what kinds of people will see the ad and will enable the DSP to facilitate better targeting when they work with ad servers.
Skyhook’s Personas can make sense of the generic data that the DSP receives when viewing an ad request and can inform the DSP of which ad requests are performing the best and delivering the greatest ROI. By layering the ad request with demographic data (age, gender, income, marital status, education level, etc.), psychographic data (likes and interests), and behavioral data, the DSP can then make a contextually informed decision on which personas it wants to target and which ad inventory it wants to buy.
Frankly, because the current state of what’s acceptable location data is just “okay”. Advertisers are delivering personalized and relevant experiences because they can use location to know exactly where their consumers are, right? Not as often as you might think. To understand why they may not be able to pay off “the right message to the right person in the right place at the right time” you need to know a little about location. In a nutshell, the best location is both precise and accurate and everything else is fuzzy.
Marketers dream about knowing precisely where their audience is and when because they want to win new customers, save their own customers before they fall into the hands of a competitor and they want their messages to flow directly into their lives so they find them useful. But their ability is often limited by the location provided by publishers to the adtech platform. The degree of relevance of the message is directly related to the precision and accuracy, but the location they are using has a larger margin of error than they realize. This means that the specificity is gone and the user’s movement is nebulous.
Remember, we’re trying to get the right message to the right person in the right place at the right time. If place is fuzzy, it’s the digital equivalent of dropping leaflets from a plane into that area. On-device location enables advertisers to know the accurate and precise location of the user’s device. This means you can have finer level detail of the place such as venue category, name and address. Think of hitting the bullseye with a dart instead of blowing it up with a shotgun. Now place is clear.
Once you have accurate and precise location you can focus on delivering the best experience to your audience. Adtech and publishers want to be able to focus on the end goal of making their audiences lives easier with relevant content and experiences that are vital to their daily lives. The experience is the new channel for connecting to your users.
With precise and accurate location, the next logical step is layering intelligence on top of that location to understand context. Mobile apps and mobile advertisers are becoming much more sophisticated, and mobile users are shifting more of their life to their mobile device. If you want to engage audiences with the richest possible experience, mobile is the place to do it. And the way to do it is by understanding and adapting to their real world context.
The aggregation of location data from mobile devices enables publishers to know the interests, activities, shopping patterns and mobile behavior of their audiences at a given time and place so that they can anticipate the right content to share at the convenient time. But it is not just about the content they are sharing, it is about how they are getting it in front of their audiences and what kinds of experiences they are creating.
Marketers have the ability to intelligently build contextual personas of their audience based on their real-world activities. Skyhook’s solution builds these consumer segments by combining census demographic data--like income level, education, gender, age and ethnicity--with behavioral patterns based on where users go and when.
These personas provide powerful insights into affinities and intents, enabling marketers and advertisers to enrich their inventories with contextual data on audience lifestyles. For example, a user who visits beauty supply shops and high end clothing stores and has an income of over 200K is classified as a Luxury Shopper. The publisher who builds that profile can command increased CPMs for ad impressions to that highly desirable segment, and advertisers can target those users with relevant messages to achieve increased conversion rates.