Proving vague performance claims don’t drive adoption

Context

Many Ads Manager products used vague performance claims in product descriptions to get advertisers to adopt them: "improve campaign performance," "we predict will perform best," "when we think it may perform better." None of these value props had any data behind them. Teams kept using them because they assumed the claims drove adoption.

I designed and led a content experiment to test that assumption, then turned the result into a content standard for value props across Ads Manager.

Problems

For advertisers

Vague claims didn't help advertisers choose. Every product promised "better performance," so the phrase became noise advertisers learned to ignore. Without a specific benefit, advertisers couldn't tell which product fit their needs.

For the business

No shared content standard. There was no rule for when a performance claim was allowed. Every team wrote its own value props, so vague performance claims spread.
Real proof got diluted. When every product promised better performance, the products with real proof, like data-backed recommendations and Advantage+ products, stood out less.

Hypothesis

Vague performance claims don't drive advertiser decisions. Removing them won't hurt adoption or revenue.

Key decisions

1. Test the assumption before rewriting anything

Most product teams believed that removing the claims would reduce adoption. I thought the claims were weak, but my opinion alone would not change their minds, and a rewrite without data would have started a debate about opinions.
So I proposed a test framed on one question: do vague performance claims change what advertisers do? If adoption dropped without the claims, they were working. If it stayed the same, we could replace them with specific value props.

2. Design a test people can trust

I focused the test on 4 products where advertisers interact with the product, like checkboxes and toggles, so we'd get real usage data. I limited the test to sales and lead campaigns, where performance matters most.

For each product, I either removed the claim or replaced it with a specific benefit, depending on what made most sense for that product:

Product	Before	After
Partnership ads	"...to improve campaign performance"	"...to help you build connections with people who trust your partners"
Text	"...we'll show the one we predict will perform best"	"...we'll personalize variations to different audiences"
Image crop	"...cropped it to fill the placement when we think it may perform better"	"...cropped it to fill each placement better"
Advanced preview	"We'll show variations of your ad we predict will resonate with different people to improve performance"	"We'll show variations of your ad to different audiences to prevent creative fatigue."

Two versions of the Partnership ad toggle. Arm A, the current content, says the ads use signals from both accounts “to improve campaign performance.” Arm B replaces that with “to help you build connections with people who trust your partners.”

3. Turn the result into a content standard

The test showed that vague claims did not drive adoption. But a rule that only says what not to write doesn't tell content designers what to write instead. So I wrote a content standard with one rule: a value prop in Ads Manager can make a performance claim only when data supports it. It has two parts:

a) Five principles

Lead with the advertiser's outcome.
Be specific. If a value prop still makes sense on another product, it's too generic.
Save performance claims for products with proof.
Let a clear description of what the feature does be the value prop.

Match the message to the decision the advertiser is making:

Decision	What the advertiser needs to know	How to write it
Turning a feature on	Why should I turn this on?	Lead with the benefit
Choosing between options	Which one fits my goal?	Lead with the difference
Reviewing a preview	Is this what I expected?	Say what changed and why
A feature that's on by default	What is this doing to my ad?	Just explain what it does

b) A toolkit of value prop themes

It covers themes like personalization and creative variety, with guidance on when to use each. It helps content designers use the type of value prop that best matches their product's core value, and helps advertisers make optimal decisions.

Outcomes

Across hundreds of thousands of ad accounts, removing vague claims caused no measurable drop in adoption or revenue for any of the 4 products.
I co-run reviews with another content designer for teams applying the new standard.

Reflection

Test for lift, not just for harm: The test showed that vague claims could go without hurting adoption. It didn't show whether specific value props do better. Next, I would test specific value props against plain feature descriptions to learn which ones raise adoption.