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:

• Use buckets breakdown report to calculate normalized CPA/ROAS by channel for both control time period and sale/heavy-up period. See Marketing Performance Report (Buckets Breakdown) for more details on this report type.

Resulting Metrics:

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

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

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

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)