Measuring Channel Heavy-ups (Increased spend) & Resulting impact to CPA/ROAS (Diminishing returns)

Rockerbox can be leveraged during your sale periods and channel heavy-ups to understand how your marketing performance and user behavior varied during this time period.

Below we outline the following four analyses:

1. Impact to CPA/ROAS

2. Impact to Channel Mix

3. Impact to Top and Bottom funnel channels

4. Impact to Path to Conversion and Time to Convert


These analyses will be accomplished through a time frame comparison. For illustration purposes, we use an example from Black Friday/Cyber Monday.

Our example compares the three day BFCM time period (Fri-Mon) to the following:

  • A control period of the same three days (Fri-Mon) averaged across multiple weeks
  • A partial heavy-up period of the same three days (Fri-Mon) averaged across multiple weeks

Priority Questions to Answer


Marketing Performance

  • Impact to CPA- how did CPA change due to heavy discounting coupled with increased spend (and mitigating against diminishing returns)
  • Impact of discounting- if used different discounts across channels, did that change the improvement on CPA of each channel?

User Behavior

  • Changes to path to conversion- were users taking more vs less time to convert and interacting with different marketing touchpoints?
  • Impact to marketing mix- were users converting from different channels?
  • Did branding heavy up result in users entering the funnel from different channels (first touch) vs converting from different channels (last touch)?

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Choosing a control period

Before you begin any analysis you need to first choose your control period.

This is the time period you will compare performance during the sales/heavy-up period against.

When choosing your control period consider the following:

  • Choosing a time period without any significant changes to your marketing mix ( heavy-ups, new channel launched)
  • For sales with a longer ramp time (i.e. BFCM) - you may want to choose two control time periods (one pre-marketing heavy up and one during heavy up)

1. Impact to CPA/ROAS


Priority Questions to answer:

  • Impact to CPA/ROAS- how did CPA/ROAS change due to heavy discounting coupled with increased spend (and mitigating against diminishing returns)
  • Impact of discounting- if used different discounts across channels, did that change the improvement on CPA/ROAS of each channel?

Methodology:


Resulting Metrics:

  • % change in CPA/ROAS by channel
  • % change in CPA/ROAS relative to % change in spend

Example analysis from BFCMExample analysis from BFCM

Example analysis from BFCM

2. Impact to Channel Mix


Priority Questions to Answer

  • What was the impact to your marketing mix- were users converting from different channels?

Methodology:

  • Using buckets breakdown to look at % of overall normalized conversions
  • Identify any changes at the channel level

See Marketing Performance Report (Buckets Breakdown) for more details on this report type.


Resulting Metrics:

  • % of conversions by channel

Example of analysis from BFCMExample of analysis from BFCM

Example of analysis from BFCM


3. Impact to Top and Bottom funnel channels


Priority Questions to Answer

  • Did branding heavy up result in users entering the funnel from different channels (first touch) vs converting from different channels (last touch)?

Methodology:

  • Using paths view in UI to see conversions by first vs last touchpoint
  • Step-by-step guide at Path to Conversion to replicate analysis

Resulting Metrics:

  • % of conversions by channel for last touch vs first touch
  • % change in first-touch conversions relative to % change in spend

Example looking at change in first touch conversions from BFCMExample looking at change in first touch conversions from BFCM

Example looking at change in first touch conversions from BFCM


4. Impact to Path to Conversion and Time to Convert


Priority Questions to Answer

  • How did our users' path to conversion change- were users taking more vs less time to convert and interacting with different marketing touchpoints?

Methodology:

  • Use paths view in UI to see average time to conversion and look at any changes
  • Be sure to filter for new vs existing customers

Go to Path to Conversion (doc:paths) for more detail


Resulting Metrics:

  • Avg # of days to convert
  • Avg # of marketing touchpoints
  • (Both overall and by channel position)
Example impact to time to convert for BFCMExample impact to time to convert for BFCM

Example impact to time to convert for BFCM


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