At first glance, these metrics look contradictory: local ad impressions are up 35%, while local business sign-ups are down 8%. But they measure different parts of the system—one is advertiser acquisition, the other is ad delivery.
Assumptions:
Local ad impressions = impressions generated by local businesses.
The changes are quarter-on-quarter.
Sign-up means completing all steps required to become eligible to advertise.
1. Why are sign-ups down 8%?
Local Business Sign-ups
│
┌──────┼───────────┐
↓ ↓ ↓
Addressable Funnel Entry Sign-up Conversion
Businesses
I would assign a low probability to addressable businesses or funnel entry suddenly falling this much. That leaves sign-up conversion.
Visit Meta Ads
↓
Start Sign-up
↓
Business Details
↓
Verification
↓
Eligible to Advertise
My working hypothesis is that verification is where the funnel is breaking, especially given tighter advertiser verification.
2. Why are impressions up 35%?
Suppose total impression inventory grew only 4%, while local impressions grew 35%:
1.35 / 1.04 ≈ 1.30
So, all else equal, local businesses would have won roughly 30% more share of the available inventory.
That tells me normal traffic growth cannot be the primary explanation.
Local Ad Impressions
│
┌─────────────────┼─────────────────┐
↓ ↓ ↓
Total Ad Opportunities Fill Rate Render Rate
│
├─ Active Users
├─ Sessions/User
├─ Content/Session
└─ Ad Opportunities/Content
× Local Advertiser Share
So the stronger explanation is that local businesses either became eligible for more placements or started winning a larger share of inventory.
What I would do
For the -8% sign-ups, reduce unnecessary verification friction without weakening verification.
For the +35% impressions, check whether the increase is actually creating value. I would monitor advertiser ROI, CPA, CTR, and consumer guardrails like ad load and hide/report rate.
Conclusion
The two metrics are not contradictory.
The -8% looks like a verification funnel problem.
The +35% looks more like an inventory allocation problem.
So I would fix the friction on the sign-up side, while validating whether the additional local impressions are genuinely valuable rather than just more volume.
N
Naman Gautam
We can reframe this as: efficiency per impression has seen a drop.
Now we can find the root cause by analysing the following:
1. Validation of data and metrics (are the numbers correct, or is there a gap btw ad and sign-up data).
2. Has the sign-up definition changed?
3. How's the TOF? What was the quality at which this campaign was launched? (If at low-placement users, then clearly the TOF needs to be improved).
4. Funnel: Impression -> Click -> Landing Page -> Start -> Sign up
5. We will analyse the funnel to see if there's a leak or any new steps (extra KYC steps or verification) or latency being added.
6. We will also plot this by geo and device type, repeat vs. new users, channel, and campaign.
7. Any external factors, maybe a new competitor (we should validate, though it is indicating to be an internal problem).
Based on the possible root causes, solutions can be implemented.
r
rishendra vikram singh
Here is my answer before jumping into solution, we need first verify the causation.
- Did drop start dropping before or after the impression spike...??
A 35% jump could be measurement change; we will need to confirm that data point first. If it’s real, my hypothesis will say it’s traffic quality issue, not a funnel problem. A large impression without corresponding budget increase usually means the system expanded its operations to lower-intent audiences or placements; those who will see the ad’s but will never sign up.
To confirm this, I’ll segment impression by placement, geography and business category to where the growth came from. If spikes are concentrated in cheaper surfaces or lower intent market, that is a major issue to resolve.
- If traffic quality looks fine and CTR is holding, then I shift focus on sign up funnel.
Mainly looking for friction points like complexity, payment set-up or account verification that may have worsened recently.
In the end the fix follows diagnosis: (What we find)
A. If traffic quality issue, we stop scaling and tighten targeting first.
B. If it’s the funnel issue, we find where the people are dropping off and remove that friction.
Bottom line is don’t treat them in isolation, but find where we’re losing qualified intent, fix that, then scale up.
S
Sai Phaneendra
Here's my approach:
The customer journey typically is: impression -> click -> sign-up. So 2 hypothesis: either 1. CTR must have decreased or 2. conversion rate must have decreased.
Case 1: when CTR decreased:
a. Refresh the creatives (try newer creatives that are engaging and use proper visual hooks)
b. Use better call to action (optimize the copy)
c. Might be ad fatigue if targeting the right people.
Case 2: when conversion rate decreased:
1. check whether we are targeting the right audience
2. offer change. Change the offer you are giving to the people on the sign-up page (may not be appealing / relevant anymore)
3. Use CRO tactics like social proofing, etc. to revive conversion rate.
C
Curious Coder
There are a few possibilities here -
1. Older advertisers are spending more on Ads: The value of ads as a proposition starts coming in after a seller spends some time learning about how ads work on the platform. In this case it is likely that the sellers onboarded few years back have started spending too much on ads. One way to check this will be looking at the QoQ or YoY spend for these advertisers, if this is rising continuously, it proves the point. Also, for the latest year ad impressions, we can bucket those impressions by ad providers. If the incumbent share is high this point turns out to be true.
2) We should also study if the effect is applicable only to local ads or elsewhere as well. If the overall platform ad impressions are shooting by so much, there could be an instrumentation change or a new display surface unlock, which may be causing this
3) There could be something wrong with the sign up funnel. We should look at the funnel break-up right from the start of the sign up journey to sign up completion and compare the section of funnel YoY to see where the drop is coming and fixing the identified issues.
Community Answers (5)
At first glance, these metrics look contradictory: local ad impressions are up 35%, while local business sign-ups are down 8%. But they measure different parts of the system—one is advertiser acquisition, the other is ad delivery. Assumptions: Local ad impressions = impressions generated by local businesses. The changes are quarter-on-quarter. Sign-up means completing all steps required to become eligible to advertise. 1. Why are sign-ups down 8%? Local Business Sign-ups │ ┌──────┼───────────┐ ↓ ↓ ↓ Addressable Funnel Entry Sign-up Conversion Businesses I would assign a low probability to addressable businesses or funnel entry suddenly falling this much. That leaves sign-up conversion. Visit Meta Ads ↓ Start Sign-up ↓ Business Details ↓ Verification ↓ Eligible to Advertise My working hypothesis is that verification is where the funnel is breaking, especially given tighter advertiser verification. 2. Why are impressions up 35%? Suppose total impression inventory grew only 4%, while local impressions grew 35%: 1.35 / 1.04 ≈ 1.30 So, all else equal, local businesses would have won roughly 30% more share of the available inventory. That tells me normal traffic growth cannot be the primary explanation. Local Ad Impressions │ ┌─────────────────┼─────────────────┐ ↓ ↓ ↓ Total Ad Opportunities Fill Rate Render Rate │ ├─ Active Users ├─ Sessions/User ├─ Content/Session └─ Ad Opportunities/Content × Local Advertiser Share So the stronger explanation is that local businesses either became eligible for more placements or started winning a larger share of inventory. What I would do For the -8% sign-ups, reduce unnecessary verification friction without weakening verification. For the +35% impressions, check whether the increase is actually creating value. I would monitor advertiser ROI, CPA, CTR, and consumer guardrails like ad load and hide/report rate. Conclusion The two metrics are not contradictory. The -8% looks like a verification funnel problem. The +35% looks more like an inventory allocation problem. So I would fix the friction on the sign-up side, while validating whether the additional local impressions are genuinely valuable rather than just more volume.
We can reframe this as: efficiency per impression has seen a drop. Now we can find the root cause by analysing the following: 1. Validation of data and metrics (are the numbers correct, or is there a gap btw ad and sign-up data). 2. Has the sign-up definition changed? 3. How's the TOF? What was the quality at which this campaign was launched? (If at low-placement users, then clearly the TOF needs to be improved). 4. Funnel: Impression -> Click -> Landing Page -> Start -> Sign up 5. We will analyse the funnel to see if there's a leak or any new steps (extra KYC steps or verification) or latency being added. 6. We will also plot this by geo and device type, repeat vs. new users, channel, and campaign. 7. Any external factors, maybe a new competitor (we should validate, though it is indicating to be an internal problem). Based on the possible root causes, solutions can be implemented.
Here is my answer before jumping into solution, we need first verify the causation. - Did drop start dropping before or after the impression spike...?? A 35% jump could be measurement change; we will need to confirm that data point first. If it’s real, my hypothesis will say it’s traffic quality issue, not a funnel problem. A large impression without corresponding budget increase usually means the system expanded its operations to lower-intent audiences or placements; those who will see the ad’s but will never sign up. To confirm this, I’ll segment impression by placement, geography and business category to where the growth came from. If spikes are concentrated in cheaper surfaces or lower intent market, that is a major issue to resolve. - If traffic quality looks fine and CTR is holding, then I shift focus on sign up funnel. Mainly looking for friction points like complexity, payment set-up or account verification that may have worsened recently. In the end the fix follows diagnosis: (What we find) A. If traffic quality issue, we stop scaling and tighten targeting first. B. If it’s the funnel issue, we find where the people are dropping off and remove that friction. Bottom line is don’t treat them in isolation, but find where we’re losing qualified intent, fix that, then scale up.
Here's my approach: The customer journey typically is: impression -> click -> sign-up. So 2 hypothesis: either 1. CTR must have decreased or 2. conversion rate must have decreased. Case 1: when CTR decreased: a. Refresh the creatives (try newer creatives that are engaging and use proper visual hooks) b. Use better call to action (optimize the copy) c. Might be ad fatigue if targeting the right people. Case 2: when conversion rate decreased: 1. check whether we are targeting the right audience 2. offer change. Change the offer you are giving to the people on the sign-up page (may not be appealing / relevant anymore) 3. Use CRO tactics like social proofing, etc. to revive conversion rate.
There are a few possibilities here - 1. Older advertisers are spending more on Ads: The value of ads as a proposition starts coming in after a seller spends some time learning about how ads work on the platform. In this case it is likely that the sellers onboarded few years back have started spending too much on ads. One way to check this will be looking at the QoQ or YoY spend for these advertisers, if this is rising continuously, it proves the point. Also, for the latest year ad impressions, we can bucket those impressions by ad providers. If the incumbent share is high this point turns out to be true. 2) We should also study if the effect is applicable only to local ads or elsewhere as well. If the overall platform ad impressions are shooting by so much, there could be an instrumentation change or a new display surface unlock, which may be causing this 3) There could be something wrong with the sign up funnel. We should look at the funnel break-up right from the start of the sign up journey to sign up completion and compare the section of funnel YoY to see where the drop is coming and fixing the identified issues.