{"id":28766,"date":"2026-04-20T16:38:57","date_gmt":"2026-04-20T21:38:57","guid":{"rendered":"https:\/\/www.jasminedirectory.com\/blog\/?p=28766"},"modified":"2026-04-20T16:41:08","modified_gmt":"2026-04-20T21:41:08","slug":"a-data-analysis-of-500-business-directories-what-separates-authority-sites-from-the-rest","status":"publish","type":"post","link":"https:\/\/www.jasminedirectory.com\/blog\/a-data-analysis-of-500-business-directories-what-separates-authority-sites-from-the-rest\/","title":{"rendered":"A Data Analysis of 500 Business Directories: What Separates Authority Sites from the Rest"},"content":{"rendered":"

The dataset started as a side project. A client asked which directories<\/a> were worth submitting to, and I gave the answer every consultant gives: “depends on your industry, check the DA, look at the traffic.” They pushed back \u2014 reasonably \u2014 asking what that actually meant in practice. Six months later, I had pulled metrics on 500 business directories across eighteen categories, tracked referral outcomes for 47 test submissions, and watched roughly half my priors collapse.<\/p>\n

What follows isn’t a ranking. It’s a framework \u2014 I’ve called it TRUST \u2014 that emerged from the data once I stopped trusting the obvious signals. The short version: domain authority predicts directory<\/a> value surprisingly poorly past the top tier, and the signals that do<\/em> predict value are mostly ignored because they’re harder to pull.<\/p>\n

Why Domain Authority Scores Mislead Directory Decisions<\/h2>\n

Domain Authority is a blunt instrument. Moz designed it as a comparative SERP-ranking predictor, not a directory<\/a> quality score, and yet it’s the first (often only) metric people check before deciding where to submit. That’s fine when you’re comparing a DA 92 site to a DA 12 site. The problem starts in the murky middle.<\/p>\n

The correlation that falls apart past rank 50<\/h3>\n

When I ordered the 500 directories by DA and plotted referral traffic quality<\/a> (measured as sessions with >30s engagement divided by total sessions), the correlation was strong for the top 50 \u2014 then flattened into noise. From DA 45 to DA 70, the r\u00b2 was 0.08. Essentially random.<\/p>\n

This makes sense once you think about it. DA is heavily influenced by total backlink volume, and directories<\/a> themselves accumulate backlinks precisely because they’re directories. A mediocre directory with 2,000 spammy businesses<\/a> submitting and cross-linking can post a DA in the 50s while sending you nothing but bots and the occasional confused human.<\/p>\n

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Did you know?<\/strong> The average business directory contains over 50 different data points per listing, compared to just 5-7 in traditional print directories from the 1990s (Business Directory<\/a>). More data points mean more vectors on which to assess quality \u2014 or to fake it.<\/p>\n<\/div>\n

What DA misses about referral traffic quality<\/h3>\n

DA tells you nothing about whether the people landing on a directory page actually click through to listings. In my sample, the median click-through rate from a category page to an individual listing was 3.1%. The range was 0.2% to 19%. That’s two orders of magnitude of variation invisible to DA.<\/p>\n

It also misses intent. A directory ranking for “accountants near<\/a> me” sends visitors in buying mode. A directory ranking for “business<\/a> information Yorkshire” sends researchers, journalists, and data scrapers. Same DA, entirely different commercial value.<\/p>\n

Cases where DA 80 sites underperformed DA 40 sites<\/h3>\n

Three examples from the dataset \u2014 anonymised because the owners would, understandably, prefer I didn’t name them:<\/p>\n