How do I make ad copy more relevant and raise click-through rate?

What ad-copy relevance moves, and what it doesn’t

Quality Score isn’t an input to the auction. It’s the 1-to-10 summary Google shows you of three things Ad Rank does weigh in real time: expected CTR, ad relevance, and landing-page experience. Two of the three live inside the ad copy itself. Better copy can earn a higher position at the same bid, so it’s the cheapest quality fix in the account.

Whether that shows up as a lower CPC is a separate question, and my own accounts say don’t count on it. When I compared low-score and high-score keywords inside the same account, low Quality Score didn’t reliably mean a higher CPC, and few accounts had enough clicks in both bands to compare at all. Most of the Search campaigns I run bid on Maximize Conversions or Maximize Conversion Value. When Google sets the bid each auction, a quality gain can go into position and volume instead of a cheaper click.

The score is also missing on a lot of spend. In my Q3 2026 Google Ads benchmarks, a median 38% of keyword spend ran on keywords with no Quality Score reported, and a median 4% sat on keywords scored 7 to 10 (N = 31). So judge a copy rewrite on CTR first and cost per conversion second. CPC is the third read, and the least reliable one.

On Meta, check the ad set’s goal before blaming the copy for a low CTR. Across 18 Meta accounts I manage in Q3 2026, ad sets optimized for reach drew a 0.06% link CTR, against 2.84% on ad sets optimized for a conversion event (N = 5 and N = 9). A reach goal asks Meta for the cheapest people to show the ad to, with no weight on who clicks. No headline fixes that. The full table is in my Meta CPM benchmarks.

Copy fails in two ways, and they need different fixes. Copy nobody clicks is a relevance problem. Copy the wrong people click is an attraction problem, and it costs more because those clicks turn into low-value orders that read as wins inside the platform. Diagnose which one you have before rewriting a headline.

Signal 1: average order value drops on a specific ad

Click-through rate and conversion rate can both look healthy while the basket size collapses. A creative that sells the cheapest SKU in the catalog will print conversions and starve revenue. The leading indicator is AOV segmented by ad, not by campaign.

Pull the report from Shopify or GA4 with ad name as the dimension and average order value as the metric. Look for a creative running clearly below the account-wide AOV across at least fifty orders. Below that volume the number is noise. Above it, the copy is selling the entry-level product instead of the catalog.

The fix lives in the headline and the primary image. Lead with a mid-tier or premium SKU price point in the visual, name the upgrade benefit in the headline, and drop the “starting at” language that anchors buyers to the cheapest variant.

Signal 2: new-customer share shrinks on an ad set

A profitable ad set can lose its job over time as it stops finding new buyers and starts harvesting people who would have bought anyway. Meta and Google both report new-versus-returning splits at the campaign or ad-set level. Read the trend, not the absolute number.

Set a baseline by averaging new-customer share across the trailing thirty days at the account level. An ad set whose share sits well below that baseline for a full fourteen-day window is attracting the wrong audience. The copy is speaking to existing customers when the budget is supposed to find fresh ones.

Rewrite the hook to address a first-time buyer concern: sizing, fit, shipping speed, return policy, brand provenance. Cut the loyalty language (“welcome back,” “you’ll love this again”) and the in-group references that only an existing customer parses. Then watch the share rebuild over the next fourteen days.

Signal 3: ninety-day cohort LTV trails the account average

Some ads acquire customers who never come back. The damage hides for ninety days because it lives in the second-order purchase, not the first. The signal is cohort lifetime value pinned to the ad that originated each cohort.

Build the report with three columns: first-touch ad, ninety-day repeat-purchase rate, ninety-day cumulative revenue per customer. Read it only on ads with a hundred or more acquired customers, and look for the ones whose ninety-day LTV trails the account cohort average.

The copy fix is filtering at the top of the funnel. Discount-led creative (“50% off,” “lowest price ever”) attracts buyers who came for the discount, not the brand, and they exit after the first purchase. Replace the discount hook with a quality, durability, or use-case hook, then compare the next cohort’s full-price share and repeat rate against the one before.

Signal 4: the search-terms report leans informational

On Google Ads the search-terms report is a transcript of who the copy is reaching. Commercial intent reads like “buy walnut dining table” or “walnut dining table for sale.” Informational intent reads like “how to clean a walnut dining table,” “what is solid walnut,” “walnut dining table reviews.”

Tag the trailing thirty days of search terms by intent. If informational queries make up a visible share of an ad group built for commercial intent, the copy is broad enough to pull in research-stage traffic that won’t convert at full price.

Tighten match types, add the informational stems as negative keywords (“how,” “what is,” “vs,” “reviews,” “guide,” “tips”), and rewrite the description to gate the click. Lead with a price point, a stock status, or a buyer commitment cue. Researchers read past the gate and self-select out before the click costs money. For home and furniture brands, the copy patterns repeat with one extra gate: shipping lead time inside the description.

Signal 5: price-objection tickets cluster on one campaign

The support inbox is the last reliable lens on who the ads attracted. Tag every ticket with a price-objection field: “too expensive,” “do you have a cheaper version,” “can you match a competitor’s price.” Then map the tagged tickets back to the first-touch ad or campaign on the customer record.

Look for a campaign whose price-objection rate clearly runs above the account-wide rate, and only once there are a hundred or more tickets to read. Lower volumes don’t separate signal from random complaint. Above that, the creative mispromised the price band.

The copy fix is the on-creative price cue. Show a representative price in the image, the caption, or the headline. Replace aspirational lifestyle photography that suggests a lower price tier with product-on-white shots at the actual price range. The wrong-budget buyer self-selects out at the impression instead of at the support ticket.

Reading the five signals together

A single signal can mislead. AOV can drop because a seasonal SKU is cheap. New-customer share can fall because the budget moved to retention. LTV can lag because a cohort is young. Two or more signals firing on the same creative is the confirmation. AOV down plus LTV down on one ad is a discount-led hook acquiring transactional buyers. Informational search terms plus price-objection tickets on one campaign is copy that promised a research resource and a budget product at the same time. When four fire at once, that’s when to request the free ads audit. I write it myself and send it back within 24 hours of read-only access, no call.

The sequence is signal first, hypothesis second, copy rewrite third, measurement window fourth. Skip any step and the rewrite reverts to taste.

On a wellness brand I audited, ninety days of Meta spend ran at a sub-one-percent click-through rate, on enough impressions to read honestly. The audience looked right, so the copy was the suspect. The hooks were aspirational, and the buyer was looking for permission to spend. The rewrite path was price-anchored creative against the lifestyle set, tested on a controlled hold-out before any cross-campaign rollout.

Once the diagnosis is in, the rewrite runs on seven levers. Work them in order.

Lever 1: the keyword verbatim in headline 1

Headline 1 is the asset Google weighs most heavily for ad relevance. The keyword belongs there in the same form a searcher typed it. A query for “walnut dining table” matches an H1 reading “Walnut Dining Table” far more strongly than one reading “Handcrafted Dining Furniture.” The second headline reads better as marketing copy and scores worse on the relevance axis.

The implementation rule is one ad group per search theme with the theme keyword pinned to headline 1 position 1 inside the responsive search ad. Pinning is the only way to guarantee placement. Unpinned headlines rotate, and a strong relevance asset can land in position 3 where it carries less weight. Check every ad group for a headline 1 that doesn’t contain the top-spend keyword.

Lever 2: headline 2 as the differentiation hook

Headline 1 confirms the searcher found the right product. Headline 2 answers the next question, which is why they should click your ad over the five others on the page. The hook lives in headline 2: the price band, the free shipping threshold, the warranty length, the inventory status, the geographic coverage.

Generic differentiation kills CTR. “Quality Service” and “Best Selection” carry no information and read as filler. Specific differentiation earns the click. “Ships in 48 Hours” beats “Fast Shipping” because the timeframe is verifiable. Headline 2 is also where the price cue from Signal 5 belongs on search. Pin it to position 2 once a winner emerges from rotation testing.

Lever 3: a description that mirrors search intent

The first line of description 1 is the second-most-read piece of copy after headline 1. It should restate the searcher’s intent in the language of the search itself, then offer the resolution. A query for “outdoor pendant lights waterproof” reads a description that opens with “Waterproof outdoor pendant lights rated for wet locations” and stops reading one that opens with “Illuminate your outdoor space with our latest lighting collection.”

The rule is mechanical. Take the top three queries by impression for the ad group, find the noun phrase common to all three, and use that phrase inside the first eight words of description 1.

Lever 4: dynamic keyword insertion with guardrails

Dynamic keyword insertion drops the searcher’s query into the ad headline at serve time. On a tightly themed ad group, the feature tends to help CTR and saves the work of writing a separate ad per long-tail variant. On a loosely themed ad group, it inserts ungrammatical or irrelevant queries and damages both CTR and brand perception.

The guardrail is theme tightness. Use DKI only when every keyword in the ad group describes the same product, the same intent, and the same buyer stage. An ad group that mixes “buy walnut dining table” with “what is solid walnut” shouldn’t run DKI, because the buying query and the research query don’t share a sensible headline. That’s Signal 4 showing up as a structural problem rather than a writing one. Set a default value that reads cleanly when the insertion fails, and check the search-terms report monthly for inserted phrases that misfire.

Lever 5: responsive search ad asset diversity

A responsive search ad accepts up to fifteen headlines and four descriptions. The platform mixes them at auction time and learns which combinations earn clicks. An ad that ships with three or four headlines forces the algorithm to combine the same assets repeatedly and starves the system of learning data.

The implementation rule is fifteen headlines per RSA covering five categories: keyword headlines (three or four), benefit headlines (three), proof headlines (two or three) such as review counts or warranty length, urgency headlines (two) such as inventory or shipping cutoff, and brand headlines (one or two). Three or four descriptions follow the same logic.

Lever 6: sitelinks and callouts kept on theme

Sitelinks and callouts extend the ad’s real estate, and they help CTR only when the assets match the ad-group theme. Account-level sitelinks pointing at “About Us” and “Shipping Policy” pad the ad with low-relevance links.

Build sitelinks at the ad-group level for the top-spend ad groups. Each one should describe a sub-category of the ad-group theme. An ad group for “leather sofa” runs sitelinks for “Brown Leather Sofas,” “Sectional Leather Sofas,” “Top-Grain Leather Care,” and “Sofa Delivery Timeline.” Callouts add non-clickable proof points: “Free White-Glove Delivery,” “30-Year Frame Warranty,” “Showroom Open Saturdays.” Both asset types feed the relevance signal.

Lever 7: auditing RSA asset ratings weekly

Google rates each RSA asset as Best, Good, Low, Learning, or Pending. The ratings update as the algorithm collects impressions. Low assets underperform the alternatives and should be replaced.

Open the ad view, select an RSA, and click Asset Details. Sort by rating. Any headline or description marked Low after a thousand impressions is a candidate for removal. Replace it with a new variation in the same category and re-check in two weeks. Three Low ratings on a single ad means the whole ad needs a rewrite against the lever stack above rather than incremental swaps.

Asset ratings are the closest thing Google gives to a per-asset quality read. They tell you which copy is earning its clicks. The five signals above tell you whether the click is worth having, and cost per conversion tells you whether the rewrite paid. The wasted-ad-spend library covers the bidding, targeting, and landing-page layers that compound on top of copy that finally addresses the right buyer.

When to bring me in

Bring me in when cost per lead keeps rising and the fixes above haven’t moved it, when you can’t tell which campaigns produce booked work, or when the search terms report shows money going to searches you’d never pick.

I'm Conner Crowe, and I write every audit myself. Send the free audit request and add me as a read-only user, and within 24 hours of access you'll have a written read on where the spend leaks and what to fix first. No call needed, and nothing in your account or store changes.

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