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3 comments
There are so many businesses that are operating without a website and without reviews.
The bottom line is if you are selling electrical equipment to Amazon, do you really need a web presence or reviews? Your internal advocates will make sure Amazon buys from you, since they know the equipment you deliver will be UL Listed, direct from the OEM, etc.
This same line of reasoning goes for so many other lines of business. Reviews only kinda matter for retail and restaurant businesses, and the second you leave certain specific regions you are literally better off going to a 3.6 star business with 600 reviews than a 4.5 star business with 600 reviews despite both purporting to offer the same thing.
FYI I tried the prepopulated options for King County, Oregon and San Diego on your site and consistently get "No leads found in San Diego" or similar for https://rangelead.com/leads?county.slug=us-ca-san-diego
Not sure whats broken, but I wish you luck fixing it!
The bottom line is if you are selling electrical equipment to Amazon, do you really need a web presence or reviews? Your internal advocates will make sure Amazon buys from you, since they know the equipment you deliver will be UL Listed, direct from the OEM, etc.
This same line of reasoning goes for so many other lines of business. Reviews only kinda matter for retail and restaurant businesses, and the second you leave certain specific regions you are literally better off going to a 3.6 star business with 600 reviews than a 4.5 star business with 600 reviews despite both purporting to offer the same thing.
FYI I tried the prepopulated options for King County, Oregon and San Diego on your site and consistently get "No leads found in San Diego" or similar for https://rangelead.com/leads?county.slug=us-ca-san-diego
Not sure whats broken, but I wish you luck fixing it!
What surprised me wasn’t the volume, but the patterns.
A significant number of active businesses still don’t have a website. Entire industries lag far behind in basic online presence. Some niches are saturated with outreach, while others appear almost untouched.
The hardest part wasn’t collecting the data. It was cleaning it, normalizing categories, deduplicating entries, and deciding what actually matters to someone who wants to use the data.
This post summarizes what stood out once the dataset grew large enough for patterns to become obvious.
Happy to answer questions or clarify methodology in the comments.