Stabilize acquisition KPIs - scale your business
Scientific Testing Process Allows Your Market to Automatically Inform - Direct - and Shape Your Winning Ads & Campaigns ...
PLUS ...
Machine Learning Tools Uncover What Your Market Really Wants -Providing an Endless Stream of Ideas, Copy and Creatives for Testing...
Proven with over $500 million in profitable ad spend ...
Ideal for information publishers – course creators – and SaaS sellers ...
The "Fractional CMO – Paid Digital Channels" Process
Manage for Target KPIs – Scale - Efficiency
This short 3.5 min video (less than 2 min 2x speed), gives a quick overview of our Fractional CMO - Paid Digital Channels process. If you prefer to scroll - scan - and read - please do so...
Fractional CMO - Paid Digital Channels is a service that delivers:
1. Consistent and predictable results, at an acceptable client acquisition cost
2. Key business objective(s) at greater scale and/or greater efficiency
3. And manages long-term growth across all channels
The key intel & levers we focus on, include:
Budget - timeline - upside potential - roadblocks - risk tolerance - cash flows - AOV (average order value) - LTV (lifetime value).
Also, what's the conversion of first purchasers to repeat customers? What's the first sale margin compared to LTV delivered?
The testing process allows you to solve for business objectives:
How do I reduce my cost per acquisition?
What appeals work best for lead generation, that generate the highest long-term value clients?
What follow-up products would have the most appeal, and in what order?
The focus is on removing bad choices, simplification, monitoring the REAL results to the business. We use strategies to achieve stability, efficiency, and scale.
Facebook is the best place to test - then use your proven creatives with other channels.
The Facebook Machine Learning Process involves:
- Testing with Feedback Loop
- Targeting with Creative
- Manage by Business Objectives
- Automated Rules to Train the Machine
Facebook’s powerful machine learning platform can uncover intent at scale. It has coverage of every possible market segment, and deep insights into what drives them to action.
Facebook prioritizes attention, and sells that to businesses for profit.
If your content is something people like and engage with, you will pay less to reach them.
Success comes from giving the machine learning platform what it wants, and it will then in return deliver to you what you want.
Facebook targets your audience based on your ad creatives.
It reads your headline, copy, images, even videos - and decides who your ad will appeal to - based upon trillions of data points...
...billions of users tracked across millions of websites, 24/7.
The focus is on ACTIONABLE INSIGHTS, based on TRENDS, for BUSINESS OBJECTIVES - such as prospecting, creative testing, or maybe a new product launch.
Finally, Facebook and Google also, they only perform as well as you train their machine learning. Automated rules train them on what are considered acceptable results and costs.
Our testing process comes from 35+ years in direct response marketing ...
... plus working with super savvy people such as one of the top 100 Facebook advertisers, who has spent close to $500 million profitably.
Parts of the process also came from a VP at Guthy Renker who spent $100 million a year, a North American director of Omnicom, and the ad tech engineers at Facebook.
The process works for any company that does online lead generation and conversion to paying customers.
With a lead generation project - this process reduced the cost per lead from over $25 to $15.
With a book publisher – client acquisition cost was reduced from $40 to closer to $25.
And with a large company selling golf training programs, who already had many control ads - the process uncovered new angles that delivered a return on ad spend around 2.1x.
