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12 months of Google review research in EU automotive dealer groups

Captq5

Green Pea
Dec 31, 2025
4
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Awards
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First Name
Bob
Hi everyone,

First-time poster from Amsterdam, the Netherlands.

I’ve been spending the last year digging into the operational side of Google Reviews for several large dealer groups here in Europe (mostly Renault/Dacia/mixed portfolios). We started this just to look at response sentiment, but once we looked under the hood of groups handling 50+ reviews a day, the conversation quickly shifted from "marketing strategy" to pure survival.

I wanted to share what we saw happening on the ground. I’m curious if the US market is facing the same bottlenecks or if you have found a better way to handle the volume.

The Campaign Crash

The biggest pattern we found is that manual processes work fine on average weeks, but they break instantly during peaks.

Real example: We audited a well-respected dealer group that maintained a 4.5-star rating on the front end, but internally, they were sitting on a backlog of 2,000+ unanswered reviews.

They weren’t ignoring customers. They simply hit a wall during sales campaigns where daily volume spiked to 80+ reviews. The marketing team physically couldn't type fast enough to keep up, and the backlog eventually became too intimidating to touch.

The Multi-Brand Tax

The other complexity we see here is "Profile Inflation." Because brands like Renault and Dacia demand separate digital identities, we see dealers managing more Google Profiles than they have actual buildings.

We watched one marketing team managing 8 physical locations but 13 separate Google Business Profiles.

The time drain wasn't the typing; it was the context switching. Logging in and out, switching tone from "Budget Brand" to "Premium Brand" dozens of times a day killed their productivity. The replies became robotic just because the humans were exhausted.

Speed vs. Polish

What became clear in our data is that at this scale, speed beats perfection. Groups that used tools to filter/automate the standard 5-star feedback, and only used human time for the negative exceptions, performed significantly better in Local SEO than teams trying to hand-craft every single "Thank you" five days late.

We are seeing a massive shift here in the EU towards AI-assisted workflows just to keep the operational SLA stable without burning out the marketing team.

Soeme questions:

How are you structuring this in the US right now?

Are you seeing this same "Profile Inflation" with new brands entering the market? And do you centralize the handling, or force GMs to handle their own store's feedback?

Curious to hear how you deal with the volume.
 
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Quick follow-up with a concrete data point from the EU side.

In one group we audited (mixed Renault/Dacia portfolio), the tipping point came around ~45–50 reviews per day. Below that, manual handling was “painful but doable.” Above that, SLA consistency collapsed within 2–3 campaign weeks.

What surprised us most wasn’t response quality, but backlog psychology. Once unanswered reviews crossed ~300, teams stopped touching them entirely, not because they didn’t care, but because the queue became demotivating.

Another pattern we see repeatedly is profile inflation. One operator with 8 physical locations ended up managing 13 Google profiles due to brand separation. The operational overhead wasn’t typing replies, but constant context switching between brands.

In those cases, teams that automated standard 4–5 star replies and reserved human time for exceptions (1–3 stars) maintained both response speed and Local SEO performance during peaks.

Curious if US groups see a similar “psychological backlog threshold,” or if responsibility is pushed down to store level before it reaches that point.