Meta’s Value Optimization Is Changing the Game for Brand and Performance Marketing

Earlier this year, Meta rolled out a beta framework for value optimization solutions. Previously, advertisers could only optimize for purchase value with current order revenue. Now, brands can customize their value definition (i.e. gross margin, predicted lifetime value, etc.). Furthermore, you can now run value optimization for non-purchase events, including upper and mid-funnel events, like Page Viewed, Product Added to Cart, or Lead. 

What is top and middle-of-funnel value optimization?

The ability to optimize campaigns for non-purchase events is important to top-of-funnel campaigns that are looking to raise brand awareness or nurture prospects.

Meta’s new value optimization framework allows advertisers to optimize for upper- and mid-funnel events like:

• Leads
• Product Viewed
• Add to Cart

This broadens the aperture for value optimization significantly and allows advertisers to track return on ad spend (ROAS) in ways they have not been able to with Meta.

How does this work with Angler AI?

Angler brings in the traffic quality into the equation through ‘value optimization’ of upper or mid funnel events. Since Angler AI predicts every site visitor’s likelihood to convert within the next 7 days (on a 0–1000 scale), we can pass that prediction as the “value” for each upper- or mid-funnel event.

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So instead of just optimizing for quantity (i.e. number of product views), you’re optimizing for high-quality product views that are more likely to convert in the next 7-14 days. 

Here’s why this matters:

Traditionally, Meta’s (and other walled gardens) machine learning system is excellent at hitting the goal you give it. If you optimize for product views, Meta will get you tons of cheap traffic that views a product but rarely converts to purchase.

This new framework allows us to bring predicted conversion quality into top and mid-funnel optimization. The results?

• Higher quality awareness/consideration traffic
• Improved efficiency of downstream conversion campaigns
• Account-level CPM drop as ad engagement improves

Real-World Example – A Beauty Brand 

A beauty brand spending multiple 7-figures per month in Meta, and 95% of that budget went to purchase optimization, wanted to explore this upper and mid funnel value optimization. They wanted to attract the ‘moveable middle’ for their brand, so we ran a matched-market test across designated market areas (DMA). 

• Test campaigns (103 DMAs covering ~50% of new customer signups in the recent months): Optimized for “add to cart” and “product viewed” using Angler’s predicted value
• Test and control markets: Business-as-usual purchase optimization

We saw:

• Meaningful increase in new customer volume (test vs. control, pre period vs. post period), as you see below.

• CPM drop (low teens %) across the ad account
• Re-engagement and conversion uplift from users who initially came through those ATC/product-view campaigns (verified through UTM).

Furthermore, when they rolled it out account-wide, the lift normalized, further validating the test lift. During the test period they reported statistically significant improvements in all 4 KPIs, measured at the store-front level:

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What’s next?

We’re excited to kick off similar testing for other Angler customers to test the impact of these top and mid-funnel tests. If you’re planning to test Meta’s new value optimization, make sure your data infrastructure can support these real-time value signals. Without them, these features won’t be fully effective.

Schedule a call with us today to learn more about how you can start leveraging these insights.

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