Welcome to AdQuick’s Analytics Series
Welcome to week 1 of our Analytics Series! This week we're covering our Attribution Dashboard, and how you're able to effectively measure your OOH campaign.
Week 1: Attribution Dashboard
We’ve heard all of the myths about out-of-home advertising. Over the next 5 weeks, we’re going to show you AdQuick’s tools to refute the negative setbacks of OOH that you might have heard.
“Out-of-Home Advertising is good for branding, but it can’t be measured.”
“OOH measurement is not really accurate, so there’s really no point.”
To be fair, OOH measurement B.A. (Before AdQuick 😉) produced high-level geographic lift which produced noisy & inconclusive results. We entered this space to expand the limits of out-of-home with data and insights.
With AdQuick, you’re able to isolate OOH measurement, directly attribute online & offline events, measure the true ROI, compare relative performance by unit, optimize campaigns to improve outcomes overtime, and use data to power multi-channel marketing.
Ok, that was a lot. In short, AdQuick makes your out-of-home campaign as data driven and measurable as any of your online campaigns.
Let’s get into it.
If you’re running an OOH campaign to drive web events, app events, or footfall, then we can provide an analytics dashboard that quantifies how many users that were exposed to your ads later took one of these actions. We call these attributed conversions. We use a three-step process to get to this data:
- Define Exposures
- Gather All Conversions
- Discover Attributed Conversions
I’m going to dig into each of these a bit more, but I also want to encourage you to schedule an analytics demo to get full exposure to our Analytics Dashboard.
First, we aggregate mobile location data from various vendors. Think device ID, lat/lon, and timestamp; this data streams into our database on a daily basis.
We define a geographic polygon, or viewshed that encompasses the area where a given device user is likely to have seen your ad. When a mobile device has a ping in the viewshed, we call that an exposure.
Lastly, for digital units and programmatically-purchased units we apply an additional filter:
… we can’t give out all of our secrets. Schedule a short call and we’ll give you all of the sweet, sweet details.
Let’s keep moving.
Gather All Conversions
The next step is to get all converted device IDs. What this means is all the conversions that exist before we match the data to exposures. Let’s look into some event types.
Web Events: Let us know the names of the events you’d like to track, and we’ll provide you with a pixel for each event. You’ll need to place the pixels on your site before the campaign starts.
The pixel takes web visit data and sends it to our Device Graph. For example, if a given user visits your website on their laptop, the Device Graph attempts to return to us the device ID for the user’s phone.
Footfall Events: For Footfall, provide us with a list of the locations you’d like to track. We’ll draw a radius or geo-boundary around the locations, then we look in our mobile location data to find device IDs that entered those bounds. We will also define a custom dwell time based on the type of location. For example, dwell time for an art gallery conversion may be 5 minutes, but dwell time for a restaurant may be 30 minutes.
Still with me? If you want to learn more about how we’re able to gather conversions, let’s chat!
For now, let’s learn to…
Discover Attributed Conversions
At this point, we have the devices that were exposed and devices that were converted. To get to attributed conversions we look for device IDs that exist in both datasets. You can see these attributed conversions in the dashboard as Directly Attributed Conversions.
So much information here, and so much more to share. If you have any questions, reach out and we would be happy to help.