Recently did a study of 1 million reviews to see what the most mentioned attributes were across all industries.

Figured I'd share some of the findings that were interesting to me:

  • Staff friendliness is the most frequently mentioned attribute in online reviews across all industries, appearing in 13.1% of all small business reviews.
  • The strongest drivers of 5-star reviews are staff professionalism, product/service selection, and fair pricing.
  • Low-star reviews frequently stem from problems with the payment process and online information accuracy.
  • Customers are increasingly looking for a simple process. Customer reviews highlighting a simple process (e.g., easy in-and-out, clear next steps) increased by 162.4% over the last two years compared to the prior two years.
  • Taste and food quality comes up in 18.9% of all restaurant reviews.
  • In retail store reviews, 21.8% mention how helpful (or unhelpful) store employees were during their visit.
  • Cleanliness of the room is cited in 41.0% of hotel reviews, while 38.1% specifically reference housekeeping service.
  • 23.7% of salon reviews highlighted the quality of work.
  • Salesperson helpfulness is a focus in 32.7% of all car dealer reviews.
  • Food or drink quality is mentioned in 29.1% of coffee shop reviews.
  • Nearly half (49.6%) of dentist reviews mention staff friendliness.
  • Professionalism of technicians show up in 36.6% of HVAC customer reviews.
  • 26.2% of grocery store reviews reference the service quality at the store’s deli.
  • Cost is mentioned in 27.8% of barber reviews.

Source: More details on findings/methodology

Posted by Late_Positive7246

8 comments

  1. Source: Google reviews for 6,000 small businesses

    Methodology for analysis: Used Python-based natural language processing to identify and quantify over 150 customer experience attributes. Review dates range from 2006-2025, with a heavy emphasis on the last 5 years.

  2. I normally disregard staff friendliness. 1) it usually doesn’t affect food or service quality. 2) I have frequently seen this used against businesses run by immigrants

  3. I was curious whether this was all over the world or just the US, because it seems very American. What I found was even narrower:

    “Review data was collected from Google Business Listings for small businesses located exclusively in Lancaster County, PA.”

    Seems like an important detail.

  4. You have a lot of redundancy in the categories. You could simplify the graph if you collapsed them. For instance: Pricing, Fair Pricing, Price Transparency. At the very least, fair and transparent are the same effective meaning in this context. I mean, what is an unfair price that is transparent, but doesn’t affects plain ol’ “pricing”?

    Similar suggestion for reviews that mention staffing. I get it, there are different aspects to a job performance. But take professionalism and friendly, aren’t they the same in this context? I guess some employees can be too “friendly” in a non-professional way, but that is what unprofessional means.

    I was recently in an organization, and everyone was asked to rate their home living conditions. The person who compiled the survey had a chart with so many categories for the question of “Do you have a pet?”:
    1. No
    2. Yes, Dog
    3. Yes, Cat
    4. Yes, Dog and Cat
    5. Yes, Cat and Dog
    It went on and on like that, and the graph had all these low% slivers of info. It all could have been collapsed into: No, Dog, Cat.

    $0.02

  5. Did you use sentiment analysis to figure out if the thing mentioned was important?

    > Staff friendliness isn’t a big deal to me, and I’m not bothered by the ease of purchasing, but I really like their unique offerings! 5 stars!

  6. This is gold for anyone in customer experience! The 162.4% increase in mentions of “simple process” over two years really reflects how customer expectations have evolved post-pandemic.

    What strikes me is how industry-specific the pain points are – 41% of hotel reviews mentioning room cleanliness vs. 32.7% of car dealer reviews focusing on salesperson helpfulness. This suggests businesses should benchmark against their own industry rather than general customer service metrics.

    The payment process being a major driver of low ratings is particularly actionable – that’s often the last touchpoint and heavily influences overall experience. Did you notice any correlation between review length and star rating across industries?

  8. They may try but AI will never replace human friendliness. Those robots always hallucinate and their purpose is simply just to get a real human staff real quick

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