Betterclasses: Fundamental Digital Marketing Analysis Mistakes

Betterclasses is a series of articles focused on exploring  Performance Marketing and improving excluding the best practices and typical optimizations that are regularly done. Starting The Series with few fundamental analysis that's tricky to handle

Performance Marketing


1. The Incremental Scaling

Lets consider a scenario of an e-commerce store which starts Performance Marketing with Motive to attract more sales in long run while making sure they're not incurring major losses

Objective: To maintain minimum ROAS of 1 while scaling the number of orders

The Performance Marketing Manager Starts the Google Ads Campaign and the Performance of the campaign will be like below- Let's keep aside campaign optimization part for now


As the Objective is to maintain ROAS of 1 and the campaign is actually delivering ROAS of 2,2 even with Good scaling month on month, the Manager decides to further scale up the campaign till the overall ROAS hits 1.

Let's look at the incremental angle Month on Month


The Month 3-4 change you see the ROAS has hit negative meaning going forward the goal of campaign is not being achieved for the additional sales that are generated,

If the campaign is further scaled, the Objectives are not reached. Its recommended to keep the campaigns till this point keeping the business objectives in picture


Why does this happen

This has mostly to do with how the Performance Marketing channels algorithms are built- They're Primarily built to have more players/brands bidding for each category of keywords- Algorithm encourages new players to start Ads thereby delivers Mid Quality audience to new brands at discounted price, but once the brand starts scaling the Discount gets waived off, as scale increases competition for exclusive audience increases thereby making it costly to scale


The Action Item

Practically looking at the problem statement, solution is always to diverge whether it be starting campaign for parallel/secondary keywords, starting new kind of campaign or starting new channel itself, New Products, New Locations.

As the Principle more or less remains same in multiple areas, Its recommended to Maximize scale till the incremental ROAS hits 1.


2. The Root Cause Analysis- Metrics

Lets consider another e-commerce store example and let's look at their monthly report Data by Metrics


Typical Monthly Report would highlight difference in the Derivative Factors that goes like this

  • 5.4% decrease in searches
  • 1.5% increase in CTR
  • 16% increase in CPM and so on
giving the probable reasons for each of this would happen and maybe by more metrics like keywords, locations etc

What we tend to miss is to find out how much has each metric (or anything that's taken into consideration like keywords etc) has contributed to the end goal change

Going back to the example, there's 24% decrease in Overall ROAS and here's how each part of funnel contributes to the ROAS Dip if rest of downward funnel remains same



So the Data Reads as follows
CPM Change has impacted the ROAS by 13% while ASP has impacted ROAS by about 8%, This doesn't align with 13% and 10% difference respectively as shown in monthly report as the contribution depends on where metric is situated in the funnel.

This gives an idea of the priority of the optimizations to be done to improve the respective metrics

No comments:

Post a Comment

All comments will be moderated before they are displayed, so do not include hyperlinks in comments

Pages