![]() If you want more accuracy or higher confidence, even more reviews are needed (i.e. Maybe a large business can get reviews from 8.8% of their customers without doing anything, but a small business needs an active review strategy in order to get reviews from 49% of their customers. That’s only 8.8% of 1000 customers, compared to 49% of 100 customers. If we repeat the same calculation for a business with 1000 customers, you see that the business needs reviews from 88 customers for the same accuracy and confidence. Again, this calculation of 49 customers is a gross approximation at best – we’re simply trying to demonstrate the statistical disadvantage that small businesses have when it comes to getting an accurate review rating. ![]() That’s almost half of the business’ customers. You can see from the calculator that a business with 100 customers needs reviews from at least 49 customers to have a business review rating with some accuracy (+/-10%) and confidence (95%). See the Addendum at the end for more caveats regarding the sample size calculation. It’s really only meant to demonstrate how statistics favors large populations – in this case, larger businesses with more customers. The following calculations are not meant to calculate a precise number of reviews that you need. Let’s demonstrate this using a handy online statistics calculator. This really puts businesses with fewer customers at a statistical disadvantage. Now comes the non-intuitive part: a small business with fewer customers needs reviews from a LARGER PERCENTAGE of their customers than a large business with many customers. And the number of customers in the sample is referred to as the “sample size”. The group of customers that you want to measure (in this case, customers that write a review) would be referred to as the “sample”. In statistics, all the customers for a business would be referred to as the “population”. A class in statistics would be helpful to understand this, but we’ll try to demonstrate this without diving into the math and underlying assumptions.įirst, some definitions. The answer to this question is not intuitive because in statistics, the shapes of probability curves are anything but linear. You probably need more reviews than you think. Sample size: how many reviews do you need? number of recommended reviews) in Yelp is influenced (biased) by: So how does it come to be that so few customers wield so much power over a business’ success or failure? The answer lies in statistics and something called insufficient “sample size”. Many perfectly good businesses have been harmed by a few vociferous customers, and some have even been forced into closing their doors in spite of the fact that as much as 99% of their customers might be perfectly satisfied. Do reviews from less than 1% of your customers fairly represent your business? Of course not – it doesn’t take a degree in statistics to intuitively understand that. Typically, less than 1% of your customers will voluntarily write an unsolicited review of your business. Some of those advantages are the basis for this article.ĭo 1% of your customers control 100% of your online reputation?
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