Updating old content is all the rage in content marketing. But do you track and measure your content update ROI?
I know a lot of SaaS businesses are not measuring the ROI from their content updates because it’s too tedious to dig the data up for each post.
But there’s an easier way to do it. And it’s completely free.
I’ve created some pivot tables with GA and GSC in Google Data Studio.
Ever since my mentor John Leo Weber showed me the cool things one can do in Google Data Studio, I’ve been obsessed with it. 😅
But first, let’s see what content ROI metrics you should measure at all.
Content update ROI metrics
What should you measure when it comes to content updates?
I like to keep it simple and look at two metics:
- the number of conversions
- and average position in SERPs.
Sessions is a vanity metric and is out of your control, as it can change depending on the search volume in a given month (the slow summer months when everyone’s on holiday and not searching for B2B software will skew your results anyway).
In order to measure these two metrics, you will need two data sources:
(1) your Google Analytics,
and (2) your Search Console accounts.
How to measure content update ROI?
Here’s a simple recipe for measuring your content update ROI::
- choose the content to update (topic for a different post…)
- update your content (as above)
- track conversions over time – before and after, monthly. Now let’s see how to set up your content update ROI tracker in Google Data Studio!
Building Google Data Studio dashboard for measuring content update ROI
As you can see from the image above (I had to blur the actual URLs and numbers out for privacy reasons as it’s a real tracker I’m using in Userpilot) – my content update ROI tracker consists of three pivot tables. I’m explaining how to set them up in Google Data Studio step by step:
Content update ROI tracker – Pivot table 1 – conversions per month
This table tracks the number of direct conversion events from each updated post in each calendar month.
Data source: Google Analytics
Row dimension: Landing Page
Column: Month of Year
Metric: your conversion event;
Filter: include LPs, RegEx contains: slugs of the updated posts (the last part of the URL after / ; each slug needs to be separated by | ; correct filter example: (slug-1|slug-2|slug-3) )
Pivot table 2 – Primary Keyword Average Position per month
This table tracks the average position of the primary keywords you’ve optimised your content for:
Data source: Search Console
Row dimension: Query
Column: Date* (Default Date Range: custom; this year)
Metric: Average Position;
filter: include: query, RegEx match: a list of your keywords/ key phrases separated by “|” again.
Pivot table 3 – All related keywords Average Position per month
Optional: this pivot table will allow you to track ancillary keywords, not just exact matches.
Table 3: same as table 2, but with a slightly different filter: RegEx “contains” instead of “match”.
Hope
