Marketing Spend Use Case
A guide to implementing Auto Insights for a Marketing Spend use case, including data structure and sample questions.
Auto Insights can help Marketing Teams get faster, more meaningful insights to support portfolio strategy, performance coaching, and building deeper customer relationships.
This article will cover:
Example insights from this use case
Recommended data structure for this use case
What sort of insights can Auto Insights help me uncover?
The types of insights you can get from Auto Insights will depend on what datasets you want to use. We've outlined some typical example questions to provide an indication of some of the types of insights you can expect:
Automate marketing spend analysis analysis
Show me my marketing spend YTD by channel
What is the average revenue by channel for Facebook campaigns??
Drill into customer behavior and revenue
Top 30 campaigns with the highest revenue this month
Show me the Offline campaigns generating the highest revenue for the last 12 months
Which campaign channel generates the most revenue in New South Wales?
Drive higher team performance
Number of orders by Campaign Manager
Revenue by Campaign Manager
How do I structure my data?
Auto Insights requires structured, transactional data, with at least 1 measure (e.g. Spend) and 5 segments (e.g. channel type). In addition, we recommend at least 7 months of data (at monthly or daily granularity) so you can take full advantage of Auto Insights' Unexpected Changes feature.
Example data structure
Please note, the example below is just a simple illustration of data structure, the fields (measures and columns) will vary depending on your dataset. Please click on the picture or zoom in for larger copy of the image.
Please refer to this article for more information about data structure.
Here are some of the typical segments we find in revenue data. A segment is a qualitative value, like names or categories:
Channel attributes: Channel type, Channel Name
Campaign attributes: Campaign name, campaign description and campaign manager
A measure is a quantitative, numeric value. Some of the typical measures include:
If an attribution model has been defined to attach sales to marketing spend, metrics like Revenue and Number of Orders can also be included