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[Case Study]

Coaching High Performing
Women Entrepreneurs

Imagine investing $1 and generating $4.67 every time you spent a dollar on Facebook. In this case study, we will breakdown how a client invested $28,967 in Facebook ads, generated $135,300 in revenue in a 60 day period for their launch and generated a 467% ROAS.

In this article, we will breakdown how we were able to generate $4.67 for every dollar invested…

 

Ad Spend ($)

Revenue ($)

%

Return on Ad Spend

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If you’re selling high ticket services, we created this breakdown is for you

In this case study breakdown, we will break down:

  • The overview of the campaign
  • The Ad Scorecard framework
  • KPIs that were tracked and optimized
  • How to move this from a launch model to evergreen
  • And a lot more!

Campaign overview

The client has a $6000 coaching program designed to help women get unstuck and scale their businesses to million dollars in revenue. There is also a scholarship offer (that a percentage of the applications were offered)

The dream client is a women entrepreneur with an existing business that generated at least $200,000/year or more, but has been stuck. They feel they are doing everything in their control to grow but feel they aren't able to breakthrough.

The coaching program is sold via an evergreen webinar.

But even though the webinar is evergreen, the program was offered in cohorts.

We ran the campaign over a 60 day period

Meet The Ad Scorecard

The Ad Scorecard is our methodology to analyze, optimize and scale paid advertising campaigns.

The 7 elements of the ad scorecard are:

  1. Offer
  2. Avatar
  3. Funnel
  4. Nurturing
  5. Ad
  6. Ad Optimization
  7. Tracking For Decision Making

While most media buyers focus on the ad and ad optimization, a holistic approach is the difference between having a profitable campaign vs. one that just gets by.

As a part of the Ad Scorecard, it is critical we determine what NOT to focus on when it comes to the optimization of the campaign.

Here is what we learned:

✅ There is a successful proven offer at the ad, funnel and over the phone
✅ The avatar is clear, with messaging that is attracting the dream client (and repelling the rest)
✅ The funnel has proven it is able to convert cold leads into clients
✅ There is a decent nurturing process that engages and converts leads into apps, and apps into clients
✅ There is one proven ad that won across the different ads that were tested

Now this may sound like: well, if everything is working, what's the actual problem here?!

The Challenge

Challenge #1: Double ad spend (profitably) from $15k to $30k
There is a small window to decide, optimize, scale and adjust

Challenge #2: There was very little audience segmentation and testing
2 ad sets = 79% of budget ($12,590.1 of $15,907.54)

Challenge #3: There were some initial benchmarks, but not enough to take action
Below, we will share the 3 metric types we track for every campaign we manage

As we started breaking the ad account down, we started seeing opportunities to optimize the account.

Here were a handful of opportunities we could implement right away:

  • Go deeper into audience segmentation with interest/lookalike targeting
  • Test new ads to beat control
  • Create / optimize retargeting funnel
  • Test minor funnel adjustments to see bumps in conversion and consumption metrics
  • Improve KPI tracking with our 3 metric types to make decision making simpler. This includes:
    • Deciding on metrics to track
    • Deciding on metric benchmarks
    • Setting up a KPI sheet to make decisions

Here is an example of a KPI sheet that we use:

Opportunities

As we started breaking the ad account down, we started seeing opportunities to optimize the account.

Here were a handful of opportunities we could implement right away:

  • Go deeper into audience segmentation with interest/lookalike targeting
  • Test new ads to beat control
  • Create / optimize retargeting funnel
  • Test minor funnel adjustments to see bumps in conversion and consumption metrics
  • Improve KPI tracking with our 3 metric types to make decision making simpler. This includes:
    • Deciding on metrics to track
    • Deciding on metric benchmarks
    • Setting up a KPI sheet to make decisions

Challenge: Double ad spend: $15k to $30k (Launch, not evergreen)
Solution: test faster to fail faster, to find winners faster

Challenge: Minimal audience segmentation 2 ad sets = 79% budget
Solution: test harder. Last media buyer ran 11 audience tests, we ran 42+ audience tests

Challenge: There were some initial benchmarks, but not enough to take action
Solution: be aware of decision making traps. Here are decision making traps media buyers fall into:

  • No target benchmarks for their campaign overall + steps of the campaign
  • Not tracking key metrics on a daily basis (it's "too much work")
  • Don’t collect real data (rely solely/mostly on Facebook pixel fires)
  • Don’t look at the truth: ignore the difference in numbers from FB to real life metrics
  • Siloed communication (no feedback loop from sales to media buying team)

In this case, the client knew their numbers and had a solid base. We took that base and went deeper!

So Here's What Happened!

Most Importantly, Here Was The Bottom Line:

Ad Spend ($)

Revenue ($)

%

Return on Ad Spend

If You're Looking An Agency, Meet Ad Pros!

AdPros is a direct response Facebook advertising agency.

That means we don't care about likes, comments and shares.

We care about money in and money out.

Here is what our dream client looks like:

  • Revenue of $1MM+ (min $500,000 annually)
  • Offer transformation information/coaching programs to large markets
  • Market size allows to scale past $1000+/day
  • Actively spending on Facebook/Instagram (breakeven or profitable campaign)
  • Understand core growth metrics in your business to scale
  • Committed to scaling front end growth, aggressively
  • Ready to invest in a traffic partner, not a first time media buyer

If this sounds like you, we want to speak to you!

Click the link below and book your consultation with our team to see if we are a fit.

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