Lots of people are having a hard time getting a good return on their Facebook ads. In this video, John Lincoln, CEO, will explain a few steps to scale your machine learning through your Facebook ads.
Start with a test campaign: set up your campaign, run it for about $800 a day, check the results, and if you see improvement, scale your program.
Creating Quality Audiences
Think about your target audiences. The real power is in your first-party data and retargeting audiences. You should have well-organized audience data that does not overlap.
Serving Ads
Encourage your click-through rate on ads to show the algorithm you have valuable content. Pay attention to your saturation point; don't serve too many ads to the same people at one time.
Refine Your Creative
Never underestimate the value of good upper-funnel storytelling. Try customer testimonials and use social proof in your short-form video.
Landing Page
Make sure your landing page specifically matches and aligns with your ad.
Tracking
Set up Facebook offline conversion tracking. You want the algorithm to run ads off a true conversion to your business.
Monitoring
Create a consistent weekly program to continue to monitor and enhance your ads as needed.
- Week 1: Complete overall reporting, strategy and budgets for the month
- Week 2: Review your creative, pause the worst ads, and create new variations
- Week 3: Review your competitors' ads, find new insight, and analyze your landing page for performance
- Week 4: Review your audience's key performance indicator and figure out what needs to be shifted
Other Campaign Performance Aspects to Pay Attention To:
1. Pacing: confirm pacing is on track and daily spending meets the target
2. Goals: monitor your current standing on lead and revenue goals for the month
3. Publisher Delivery Health: prospecting frequency and remarketing frequency should be 10 - 14 days
Try all of these things on your Facebook ads and let me know what changes you see. Leave a comment below.
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