What is a Device Graph? The Details for TV Advertisers
![What is a Device Graph? The Details for TV Advertisers](https://images.ctfassets.net/8z6w7ujc4bh9/5Ii3MjHRasjATzQyGscRna/11da5b7b3185c3a7f9247b6a5495aaaa/Device_Graph.png)
The average American has eight different devices. Between smartphones, digital watches, laptops, tablets, gaming consoles, PCs, and smart TVs, weâre more connected than ever before.Â
And our data is more dispersed than ever before.
When a customer sees an advertisement on one device, does research on another, and makes a purchase with a third device, how do advertisers see the whole picture?
Thatâs where a device graph comes in handy.
What is a device graph?
Device graphs are data structures that anonymously link individuals to their personal devices.Â
Device graphs collect continuous inputs from many different data streams, and this data is categorized, organized, and validated to provide a more complete picture of each householdâand the multiple devices in it.
![home with lines showing two people and then lines showing that they each have a phone and laptop and share a TV](https://images.ctfassets.net/8z6w7ujc4bh9/2Zo0DoS9SalynXymnzxrf2/1c2c7f90880aee40356fe0ecb826bed9/device_graph_2.png)
How does a device graph work?
Imagine John and Lisa live together in a household. Combined, they own two cell phones, one Smart TV, one tablet, and one laptop. All their devices are registered to the same household, but John and Lisa donât use each device. John uses his phone, the tablet, and the TV, and Lisa uses her phone, her laptop, and the TV.Â
To decipher which devices belong to John and Lisa individually, a device graph aggregates feeds from many different data sources (browser activity, mobile GPS pings, and more), then identifies John and Lisa as unique users and links each device to its true user(s).
![layout of a house showing a phone in each bedroom, a laptop in a room and a TV in the living room](https://images.ctfassets.net/8z6w7ujc4bh9/5lgiKa4Eh0XXfVX1abDf9b/bcc070880fd278f6a7cd8f080cbc9b17/device_graph_1.png)
The data contained in a device graph thatâs used for device linking comes from many different sources. A few examples include:
Geo data: Geographic coordinates, timestamps, IP addresses, and device IDs
IP data: Connection type and approximate location
Real-time data: Content type, device type, timestamp, and IP address
Identifiers
Data, by itself, isnât that useful. Itâs a lot of numerical values that donât really mean anything unless you can identify what it is and why itâs important. Device graph identifiers provide the organization and context that make this data useful.Â
Identifiers are nodes of data that have a relationship. Common device graph identifiers include:
Device IDs
Timestamps
GPS locations
Connection types
Content types
IP addresses
Identity links
Individual nodes of data on different identifiers have limited usefulness. Knowing what devices were connected during an ad playâbut not where those devices were locatedâis like putting together a puzzle that is missing pieces.
A device graph fills in the gaps by using identity links to connect identifiers and show relationships.Â
Validation
Itâs easy to misinterpret data taken out of context. To ensure accuracy and reliability, each input is validated or double checked in a handful of ways.
For example, a validation sequence might check how often a specific device ID is associated with a certain geolocation tag or IP address. By doing this, outliers or guest devices are not mistaken as a part of the household.
Another example might be a validation to see if there is a pattern between device IDs and the networks they attach to throughout the day. This data can help identify differences between device use cases. A work device would likely be connected to a company broadband network or a public wifi access point during business hours, while a personal device would connect to a home wifi network in the evening.
Outputs
Once the data is collected, organized, linked, and has passed several thousand rounds of validationâit becomes usable. At this point, advertisers can pull the data they need by performing searches using an interfacing console.
How this works varies from one provider to another. Currently, Madhive is the only OTT-first device graph that links audiences to the devices they use in truly real-time.Â
How are device graphs used?
Device graphs are especially useful for targeting the right audiences with relevant messaging. Theyâre also integral to post-campaign attribution.
Targeting
Letâs say youâre a sports fan whoâs always researching the latest news and refreshing game scores on your phone. But when youâre sitting on the couch watching CTV content, you see a fashion ad.
Sounds like a mismatch, right?
With the help of a device graph, the fashion advertiser would know youâre the user for both your mobile device and your TV, so chances are youâre not an ideal customer. In your place, the advertiser would target a CTV viewer who has a clearer interest in fashion across their devices.Â
Attribution
Imagine youâre a retailer who wants to know your CTV campaignâs effectiveness at driving in-store traffic. The device graph makes it possible.
First, youâd create a geofence using the coordinates of your storefront. Then, when your campaign is live, youâd record the mobile device IDs of everyone who crosses that geofence.
Next, youâd use a device graph to cross-reference the mobile IDs with other devices belonging to the same users. If your device graph finds you served someone an ad on one of their devices and they subsequently visited your storefront, youâd know the ad was a success.
When it comes to full-funnel attribution, the industry has more work to do to turn TV advertising into a true performance channel. Device graphs are the first step. When you factor in the device data marketers now have access to, along with smart TV data â aka ACR data â and other measurement tools like panels, TV has the ability to become a true closed-loop performance vehicle.
The takeaway on device graphs
Device graphs might get a bad rep for being complex data analytics tools. But hereâs what you really need to know â theyâre just well-designed data warehouses designed to make audience information more useful.Â
Device graphs make it possible to target precise audiences with relevant ads, then accurately measure campaigns across devices.
You might also like: