Win in marketing with data granularity: An MAU recap
It’s been a month since MAU Vegas and we are still excited about all the great content that was there! MAU is consistently the biggest opportunity of the year for marketers to learn new strategies and understand how to fuel your marketing stack for bigger and better things. Just in case you missed it, here’s an overview of the presentation by our VP of Customer Strategy, Victor Savath, on winning in marketing with granularity. It’s also available for viewing here!
**If you’re looking to cash in on some more valuable insights from MAU, our list of must-see sessions is a good place to begin!**
By definition, granularity means the quality of being granular, or the scale or level of detail present in a set of data. For the purposes of mobile marketing, we look to another definition:
Granularity means the depth of marketing campaign data available for teams to optimize at, such as sub-campaign, creative, keyword, user, etc.
There are two subsets of marketing data granularity in mobile marketing:
- Granular marketing data: data you collect from your different ad networks
- Granular attribution data: data you collect from your attribution partner that provides you with actionable insights on revenue, i.e., installs, in-app events, etc.
The combination of these two types of granular data provides you with granular return on advertising spend (ROAS) and gives you a true understanding of the performance of your marketing campaigns.
Why is granularity so important?
The head of most marketing strategies focuses largely on SANs – self attributing networks like Facebook, Twitter, Snapchat, etc. Though optimizing on SANs can be effective, marketers inevitably experience diminishing returns and need to look to other channels to expand.
Consequently, the mid and end tail of a marketing strategy are comprised of a multitude of ad networks that marketers test out. This strategy requires marketers to gauge the success of individual ad campaigns across each ad network to pinpoint the ones that deliver the best ROAS. This method does allow you to get scale, but your quality suffers.
How this happens today
When a mobile marketer is about to run an ad campaign, they have a lot of factors under their control. A marketer determines which audiences to target, what the creative assets look like, what the bidding caps are, and how to format the tracking URL that they then deliver to ad network partners. After all this has been determined, they start running their campaigns with the goal of stitching together ad network and attribution data and getting granular.
Let’s imagine a marketer who is getting ready to test out a new ad network by running campaigns in several countries at once. Prior to starting, they have:
- Carefully considered audiences to target
- Built tracking URLs to reflect a focus on campaign ID and country
However, a few days into the live campaign, the marketer looks at their attribution data and discovers that they’re getting some installs and revenue coming from countries they did not target. To solve this problem they then need to:
- Work with their account managers
- Work with their BI analysts
- Locate the source of the problem and fix it
This whole process causes delays and the marketer doesn’t get what they really wanted: valuable insights about performance metrics in these countries.
This results in the marketer not focusing on the performance of their ad campaigns, but instead only making sure they have good visibility on both sides of the equation. When companies are spending their time trying to piece together disparate data sets in pursuit of data granularity, they miss out on opportunities to expand and improve their marketing strategy. Doing this campaign by campaign is tedious, time consuming, and limits the ability to grow.
The bottom line: Marketers need granularity in order to scale.
Why is this all so difficult?
Achieving marketing data granularity is difficult no matter the size of a company or how many networks you’re running. The data sets that marketers work with are misaligned by nature between aggregate and user-level data:
- Ad network marketing data is often non-standardized. There is no universal schema for naming conventions
- Attribution data, which is more controlled by the marketer, requires a lot of manual input and will be organized depending on how you build your tracking links. This requires a lot of manual changes when adjustments need to be made, and is very time consuming
The big challenge: maintaining order of these two data sets at scale. Without a well-built internal system, this is almost impossible.
How can you achieve granularity?
- What data you will need
- Where/how to get the data
- When you need the data
- Where will the data go
By not assuming:
- Networks are created equally. Ad networks evolve, reporting dashboard/tracking link conventions change, macros supported, teams, relationships, and level of granularity vary
- Attribution granularity equates to available campaign metadata
By utilizing intelligent tracking templates:
Marketers need to be diligent, work as a team, and make informed decisions based on an understanding of how campaign metadata will come out, allowing them to ensure the pairing of intent and outcome.
By understanding your options to automate:
A big focus of what Singular does today is automatically standardizing attribution tracking URLs and marketing data, which essentially eliminates the need for marketers to manually track URLs. Singular meshes these two data sets together to provide marketers with a clear picture of performance, and ultimately allows our customers to get down to the most granular data possible: user level.
Data granularity is a necessity for marketers to scale, and we at Singular have seen how a lack of granularity presents problems for our customers on a daily basis. To learn more about how Singular will get your data granular, request a demo today!