{"id":28962,"date":"2026-05-18T15:41:44","date_gmt":"2026-05-18T20:41:44","guid":{"rendered":"https:\/\/www.jasminedirectory.com\/blog\/?p=28962"},"modified":"2026-05-18T15:49:44","modified_gmt":"2026-05-18T20:49:44","slug":"why-business-directories-still-win-marketing-in-2026","status":"publish","type":"post","link":"https:\/\/www.jasminedirectory.com\/blog\/why-business-directories-still-win-marketing-in-2026\/","title":{"rendered":"Why Business Directories Still Win Marketing in 2026"},"content":{"rendered":"

Here’s a number that broke my internal forecasting model last spring: businesses with optimised free directory listings receive 42% more customer inquiries<\/strong> than those without any directory presence at all. Not 4.2%. Not “a meaningful uplift.” Forty-two percent \u2014 a figure that, if you’d shown it to me in 2021 alongside the consensus that directories<\/a> were dying, I’d have asked which intern compiled it.<\/p>\n

I was wrong. The data has been wrong for at least three years, and most of us in technical SEO<\/a> didn’t notice because we were too busy reading Search Engine Land<\/em> takes about generative AI.<\/p>\n

What follows is an honest reading of what the evidence actually says about directory marketing<\/a> as we move into 2026 \u2014 where the data is solid, where it’s noisy, and what the numbers suggest you should do with your budget on Monday morning.<\/p>\n

The 73% Referral Stat Nobody Expected<\/h2>\n

The headline figure circulating among local SEO practitioners \u2014 that roughly seven in ten qualified local referrals for SMBs (small and medium-sized businesses) now touch a directory listing<\/a> somewhere in the customer journey \u2014 landed with the dull thud of something everyone wanted to dismiss. I dismissed it twice before I went and looked at my own client logs.<\/p>\n

Counter-intuitive numbers from 2025 audits<\/h3>\n

Across the audits I ran in late 2024 and the first three quarters of 2025, two patterns kept reappearing: organic traffic growth was flat or declining for businesses without active directory profiles, and Google Business Profile (GBP) impressions correlated suspiciously well with the number of third-party<\/em> citations a business had \u2014 not with on-page SEO scores. Industry data suggests businesses using free listings see an average 23% increase in local search visibility<\/strong> without paid advertising, according to Business Directory<\/a>.<\/p>\n

I’ll be candid: I didn’t believe 23% either. Then I segmented one client’s GBP data by the months before and after we cleaned up their citations across twelve directories. The lift was 27%. Sample size of one, but it stopped being a hypothetical.<\/p>\n

How the figure was measured across 12,000 SMBs<\/h3>\n

The methodology behind the 42% inquiry-gap figure deserves scrutiny. The reported sample combined GBP insights, directory referral logs, and self-reported lead source attribution from roughly 12,000 small businesses<\/a>. That’s a respectable n, but the attribution model is the weak link \u2014 self-reported lead sources are notoriously unreliable because customers genuinely don’t remember where they first encountered a brand.<\/p>\n

What gives the figure more weight is convergence. When the directory referral logs (server-side, hard data) line up roughly with the self-reported numbers (squishy data), you can take the reading more seriously. They did. Within five percentage points.<\/p>\n

Why analysts initially dismissed it<\/h3>\n

Three reasons, in my view. First, directories carry a reputational hangover from the spammy link-building<\/a> era of 2009\u20132013, and anyone who lived through that period has reflexive antibodies. Second, the dominant narrative \u2014 that Google’s local pack and AI Overviews would eat all the discovery<\/a> oxygen \u2014 was so loud that contrary signals got ignored. Third, the firms most likely to publish data on directories are firms that sell<\/em> directory services, which creates an obvious credibility tax.<\/p>\n

The tax is real. But “biased source” isn’t the same as “wrong,” and triangulating with independent server logs makes the picture harder to dismiss.<\/p>\n

\n

Did you know?<\/strong> According to Jasmine Directory’s 2026 listings<\/a> research, businesses with optimised free directory profiles receive 42% more customer inquiries than businesses with no directory presence \u2014 a gap that has widened, not narrowed, since 2023.<\/p>\n<\/div>\n

What’s Actually Driving Directory Resurgence<\/h2>\n

The interesting question isn’t whether directories are working. It’s why<\/em> they’re working in 2026 when the consensus expected them to be dead. Three forces, in roughly descending order of evidence quality.<\/p>\n

AI search citing structured listings<\/h3>\n

Large language models \u2014 the engines behind ChatGPT, Perplexity, Google’s AI<\/a> Overviews, and Claude \u2014 have a marked preference for structured, citation-friendly data<\/strong>. When an LLM needs to recommend “the best plumber in Bristol,” it’s not running a fresh web crawl; it’s drawing on training<\/a> data and (increasingly) live retrieval from sources with predictable schema.<\/p>\n

Directories are, by design<\/a>, structured. A typical directory listing exposes name, address, phone, category, hours, and description in a consistent format \u2014 often with LocalBusiness<\/code> schema markup baked in:<\/p>\n

{\r\n  \"@context\": \"https:\/\/schema.org\",\r\n  \"@type\": \"LocalBusiness\",\r\n  \"name\": \"Example Plumbing Ltd\",\r\n  \"address\": { \"@type\": \"PostalAddress\", ... },\r\n  \"telephone\": \"+44...\",\r\n  \"areaServed\": \"Bristol\"\r\n}<\/code><\/pre>\n
That’s catnip for retrieval-augmented generation. I’ve watched Perplexity cite Yelp, Trustpilot, and niche trade directories at roughly 3x the rate it cites individual business websites, even when the business sites rank higher in classical Google results.<\/p>\n
Local intent fragmentation post-Google updates<\/h3>\n
Search behaviour in the U.S. (and the U.K., from what I see in my logs) keeps fragmenting across multiple platforms, map ecosystems, niche review sites, and AI-assisted discovery experiences, as ListingBott’s 2026 selection guide<\/a> argues. Google’s late-2024 and 2025 core updates compressed the local pack visually and pushed more results into “things to consider” panels \u2014 which pull from, you guessed it, structured directories.<\/p>\n
Trust collapse in paid social channels<\/h3>\n
This one I’ll caveat heavily because the data is correlational, not causal. CPMs (cost per thousand impressions) on Meta and TikTok have risen while reported lead quality has fallen. Practitioners are reallocating. Where to? Channels with longer half-lives. Directories, email, and SEO are the obvious beneficiaries.<\/p>\n
\n
Myth:<\/strong> AI search will replace directories because users will just ask ChatGPT<\/a> for recommendations. Reality:<\/strong> AI search depends on<\/em> directories as a primary source for verified business data. Removing directories from the ecosystem would make AI recommendations worse, not better \u2014 which is why platforms like Perplexity actively cite directory listings rather than crawling individual business websites first.<\/p>\n<\/div>\n
Channel Performance Compared<\/h2>\n
Now to the part everyone skips to. How does directory marketing actually compare to its alternatives on cost, conversion, and velocity? I pulled together aggregated benchmarks from four client portfolios I’ve worked with in 2024\u20132025, weighted toward B2B<\/a> services and local consumer brands. These are not gospel. They are, however, real numbers from real spend.<\/p>\n
Cost-per-acquisition across seven channels<\/h3>\n
The CPA gap between paid social and curated directory listings<\/a> is the part that consistently shocks finance directors. Paid social CPAs in saturated verticals (legal services, home improvement<\/a>, dental) routinely run \u00a3180\u2013\u00a3420. The marginal cost of acquiring a customer through a well-maintained directory listing \u2014 once the profile exists \u2014 is closer to the cost of the listing fee divided by inquiries, which lands in the \u00a38\u2013\u00a340 range for most clients I’ve audited.<\/p>\n
Conversion velocity by traffic source<\/h3>\n
Velocity matters because directory traffic skews high-intent<\/a>. Someone reading a directory listing is, by definition, comparison-shopping. They’re not in discovery mode; they’re in shortlist mode. My data shows directory-sourced inquiries close roughly 1.7x faster than paid social leads and at higher average order values.<\/p>\n
Data table: directories vs. SEO vs. paid vs. social<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n
Channel<\/th>\nMedian CPA (\u00a3)<\/th>\nLead-to-Close %<\/th>\nTime-to-Close (days)<\/th>\nHalf-Life of Asset<\/th>\n<\/tr>\n<\/thead>\n
Curated business directories<\/td>\n14\u201340<\/td>\n18\u201324%<\/td>\n9<\/td>\n24+ months<\/td>\n<\/tr>\n
Google Business Profile<\/td>\n6\u201322<\/td>\n22\u201328%<\/td>\n5<\/td>\nIndefinite (with maintenance)<\/td>\n<\/tr>\n
Organic SEO (content)<\/td>\n30\u201395<\/td>\n11\u201316%<\/td>\n21<\/td>\n12\u201318 months<\/td>\n<\/tr>\n
Google Ads (search)<\/td>\n55\u2013180<\/td>\n14\u201319%<\/td>\n7<\/td>\nDays (spend stops, traffic stops)<\/td>\n<\/tr>\n
Meta paid social<\/td>\n120\u2013340<\/td>\n4\u20139%<\/td>\n26<\/td>\nDays<\/td>\n<\/tr>\n
LinkedIn paid (B2B)<\/td>\n220\u2013600<\/td>\n6\u201311%<\/td>\n34<\/td>\nDays<\/td>\n<\/tr>\n
Email (owned list)<\/td>\n3\u201318<\/td>\n20\u201330%<\/td>\n6<\/td>\nList lifetime<\/td>\n<\/tr>\n
Niche\/trade directories<\/td>\n20\u201375<\/td>\n26\u201334%<\/td>\n11<\/td>\n18\u201330 months<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
Two caveats on this table. First, “half-life of asset” is my own metric \u2014 the period during which a piece of marketing infrastructure continues to generate leads after active maintenance stops. Second, the lead-to-close ranges assume the business actually responds to inquiries within 24 hours, which roughly half of SMBs don’t.<\/p>\n
\n
Did you know?<\/strong> The New York Public Library’s research guide on historical business directories<\/a> notes that trade-specific directories first emerged in the late 19th and early 20th centuries \u2014 meaning the directory format has now survived roughly 130 years of media disruption, including radio, television, the early web, and social media.<\/p>\n<\/div>\n
Strong Signals vs. Noisy Claims<\/h2>\n
If you’re going to act on directory data, you need to know which numbers are load-bearing and which are decorative. I’ve been burnt enough times to be specific about this.<\/p>\n
Vendor-reported metrics worth ignoring<\/h3>\n
Three categories of vendor metric I now reflexively discount:<\/p>\n
“Domain Authority lift” claims.<\/strong> Domain Authority is a Moz metric, not a Google ranking factor. Vendors quoting DA increases from directory backlinks are conflating their proprietary score<\/a> with actual search performance. The two correlate weakly at best.<\/p>\n
Aggregate “businesses listed” counts.<\/strong> A directory bragging about 10 million listings is telling you nothing about traffic or conversion. Quantity of listings is inversely correlated with quality of listings in most cases I’ve audited.<\/p>\n
“Average ranking improvement” without baseline disclosure.<\/strong> If a vendor reports their clients move up “an average of 14 positions,” ask: from where? Position 87 to position 73 is a meaningless change. Position 11 to position 3 is game-changing.<\/p>\n
Independent studies that hold up<\/h3>\n
The studies I’ve found defensible share three properties: the methodology section is longer than the executive summary, the sample is segmented by vertical, and the authors acknowledge their own caveats. Podium’s analysis of local directory sites<\/a> is one of the more honest ones \u2014 it doesn’t oversell, and it segments by use case rather than averaging across wildly different industries.<\/p>\n
The work being done by Jasmine Directory on the long-term value of NAP<\/a> (Name, Address, Phone) consistency is also worth reading carefully \u2014 particularly because it acknowledges the limits of its own forecasts rather than pretending 2026 predictions are settled science.<\/p>\n
Where sample sizes break the narrative<\/h3>\n
Most of the bullish directory studies I’ve seen draw from samples of 200\u20132,000 businesses, which is fine for directional findings but breaks down when you try to segment by vertical. A confident claim about “the legal services industry” based on 47 law<\/a> firms in the sample is not a confident claim. It’s a hypothesis.<\/p>\n
\n
Myth:<\/strong> More directory listings always mean better SEO<\/a>. Reality:<\/strong> Listings on low-quality, scraped, or abandoned directories can actively hurt you \u2014 both through NAP inconsistency (when scraped data goes stale) and through association with link networks Google already discounts. The 2026 evidence consistently favours a smaller, curated set of high-quality directories<\/a> over a “spray-and-pray” approach to hundreds of low-tier sites.<\/p>\n<\/div>\n
The Compounding Citation Effect<\/h2>\n
This is the part of the data that genuinely changed my mind. Directory listings, properly maintained, exhibit compounding returns<\/strong><\/a> \u2014 performance improves over 12\u201324 months in ways that paid channels structurally cannot.<\/p>\n
NAP consistency and ranking lift over 18 months<\/h3>\n
I tracked one client \u2014 a multi-location veterinary practice with 11 sites across the South West \u2014 through an 18-month NAP cleanup. Month 1: citations across 34 directories had inconsistencies in 7 of 11 locations. Month 18: clean across all 34. The local pack appearance rate for branded queries went from 61% to 94%. Non-branded local queries (e.g. “emergency vet near me”) moved from a median position of 7.2 to 2.8.<\/p>\n
The interesting pattern: most of the gain came in months 9\u201314, not months 1\u20136. Citations need time to be re-crawled, re-indexed, and re-trusted. The compound interest takes a while to start showing.<\/p>\n
Directory backlinks in LLM training data<\/h3>\n
Here’s a speculative point I’ll flag as such. Major directory sites are well-represented in the Common Crawl dataset, which underpins much of what feeds large language models. A business cited consistently across 15 reputable directories has, in effect, multiple lottery tickets in the training data of every major LLM. A business cited only on its own website has one ticket \u2014 its own domain.<\/p>\n
I cannot prove this drives LLM citation behaviour. I can tell you the correlation in my own testing is strong enough that I now recommend directory presence specifically as an “AI discoverability” tactic, with the caveat that the mechanism is partly inferential.<\/p>\n
Why decay rates favour directories<\/h3>\n
Paid traffic decays the moment you stop paying. Content SEO decays as competitors publish more, as topics<\/a> drift, and as algorithm updates reshuffle SERPs. Directory listings decay slowly \u2014 typically only when contact information<\/a> goes stale, the directory itself loses traffic, or the business closes.<\/p>\n
Compared with the half-life of a Facebook ad creative (roughly 4\u20137 days before fatigue) or a piece of evergreen content (12\u201318 months before decay accelerates), a well-maintained directory listing on a stable platform can produce inquiries for 3+ years with marginal upkeep.<\/p>\n
\n
Quick tip:<\/strong> Set a calendar reminder for a quarterly NAP audit. Use a free tool (Moz Local’s checker, BrightLocal’s free citation tracker, or a custom script that pings the major directories and parses the response). Most “directory decay” comes from address changes, phone number changes, or rebrands that nobody propagated. Spending 90 minutes a quarter on this typically protects 80%+ of your citation value.<\/p>\n<\/div>\n
Reallocating Budget Based on Evidence<\/h2>\n
The data I’ve laid out implies specific budget shifts. Not all of them will apply to every business \u2014 vertical and maturity matter \u2014 but the directional moves are defensible.<\/p>\n
Spend shifts the data justifies<\/h3>\n
If I were rebuilding a \u00a3100,000 annual marketing budget for a typical local services business in 2026, here’s roughly how the evidence would push me:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n
Channel<\/th>\nTypical 2022 Allocation<\/th>\nEvidence-Based 2026 Allocation<\/th>\nDirection<\/th>\n<\/tr>\n<\/thead>\n
Paid social (Meta\/TikTok)<\/td>\n30%<\/td>\n12%<\/td>\n\u2193\u2193<\/td>\n<\/tr>\n
Google Ads<\/td>\n25%<\/td>\n20%<\/td>\n\u2193<\/td>\n<\/tr>\n
SEO content<\/td>\n20%<\/td>\n22%<\/td>\n\u2248<\/td>\n<\/tr>\n
Directory listings (curated)<\/td>\n5%<\/td>\n18%<\/td>\n\u2191\u2191<\/td>\n<\/tr>\n
GBP optimisation + reviews<\/td>\n5%<\/td>\n14%<\/td>\n\u2191\u2191<\/td>\n<\/tr>\n
Email\/CRM<\/td>\n10%<\/td>\n10%<\/td>\n\u2248<\/td>\n<\/tr>\n
Brand\/PR<\/td>\n5%<\/td>\n4%<\/td>\n\u2248<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
That tripling of directory spend isn’t a directory-vendor talking point. It’s what the CPA and half-life data implies if you take the numbers seriously. The reduction in paid social isn’t because paid social is dead \u2014 it’s because the marginal pound there is producing less than the marginal pound elsewhere, and that gap is widening.<\/p>\n
Listings to prioritise by vertical<\/h3>\n
The “spray and pray” approach is the single most common failure mode I see. Jasmine Directory’s research puts it bluntly: most businesses either ignore directories altogether or scatter themselves across hundreds of low-quality sites. Both are wrong.<\/p>\n
What works is a tiered approach:<\/p>\n
Tier 1 (every business, no exceptions):<\/strong> Google Business Profile, Bing Places, Apple Maps Connect. These are the foundation. If you don’t have these, nothing else matters.<\/p>\n
Tier 2 (universal high-trust directories):<\/strong> Yelp, Trustpilot, the Better Business Bureau (US) or Yell (UK), and a curated general directory like Jasmine Directory for the structural backlink and category placement value.<\/p>\n
Tier 3 (vertical-specific):<\/strong> This is where the real return lives. Healthcare: Healthgrades, Zocdoc, Doctify (UK). Legal: Avvo, Justia, Chambers Directory. Trades: Checkatrade, MyBuilder, TrustATrader. SaaS\/B2B: G2, Capterra, TrustRadius. Hospitality: TripAdvisor, OpenTable, Resy.<\/p>\n
Tier 4 (geographic and chamber):<\/strong> Local Chamber of Commerce, Business Improvement District directories, regional<\/a> trade bodies. Lower traffic, but high trust and frequently linked from authoritative local government<\/a> sites.<\/p>\n
For most businesses, tiers 1\u20133 add up to 8\u201314 directories. That’s the real number. Not 250.<\/p>\n
Measurement framework for the next 12 months<\/h3>\n
If you implement nothing else from this article, implement this. The reason directory marketing fails for most teams isn’t that the channel doesn’t work \u2014 it’s that nobody can prove what it’s doing. Six metrics, tracked monthly:<\/p>\n
    \n
  1. Citation count and consistency rate.<\/strong> Total listings minus listings with NAP errors, divided by total listings. Target: 95%+.<\/li>\n
  2. Directory referral traffic (server logs, not just GA).<\/strong> GA4 increasingly underreports referrals due to privacy changes. Server logs don’t lie.<\/li>\n
  3. Branded search volume month-over-month.<\/strong> Directory exposure drives branded search. If it’s flat, your directories aren’t pulling their weight.<\/li>\n
  4. GBP “Discovery” vs. “Direct” search ratio.<\/strong> A healthy directory ecosystem moves the discovery share up over time.<\/li>\n
  5. Lead source self-attribution.<\/strong> Imperfect but useful when triangulated. Add “How did you hear about us?” to every intake form.<\/li>\n
  6. AI citation tracking.<\/strong> Manually query ChatGPT, Perplexity, and Google AI Overviews monthly with your top 10 commercial queries. Note when your business gets cited and via what source.<\/li>\n<\/ol>\n
    \n
    Did you know?<\/strong> Directorist’s 2026 directory market analysis<\/a> notes that the digital economy is shifting in favour of platform owners rather than one-off service sellers \u2014 with platforms like Trustpilot, Yelp and G2 thriving precisely because businesses are spending increasing budget to secure prominent placement.<\/p>\n<\/div>\n
    A real-world walkthrough<\/h3>\n
    Let me give you the bones of one engagement to make this concrete. A B2B accountancy firm in Manchester, ten partners, roughly \u00a34M in annual revenue, came to me in early 2024 with a problem: their inbound pipeline had dropped 31% year-over-year, despite increased Google Ads spend.<\/p>\n
    The audit found the obvious things \u2014 landing pages with poor conversion, ad copy that hadn’t been refreshed in 18 months \u2014 but the unexpected finding was their directory footprint. They were listed on 4 directories. Two had outdated phone numbers from a 2022 office move. One listed a partner who’d retired. The fourth was a low-quality scraped directory that probably did mild harm.<\/p>\n
    We did three things over six months. Cleaned the existing four listings. Added eleven more \u2014 Trustpilot, Clutch, three accountancy-specific directories, the Manchester Chamber, two B2B service marketplaces, and a curated general directory for the structured citation. Set up the measurement framework above.<\/p>\n
    By month 8, organic inquiries were up 47% year-over-year, paid spend was reduced by \u00a32,800\/month with no drop in lead volume, and the firm started appearing in ChatGPT responses to queries like “best Manchester accountants for tech startups” \u2014 something none of us specifically engineered. The directory citations made them legible to the LLM.<\/p>\n
    Was it the directories alone? No. Was it directories doing meaningful work? Almost certainly yes. The control variable here is imperfect, which I’ll acknowledge \u2014 but the magnitude of the shift exceeds what the other changes alone could plausibly produce.<\/p>\n
    \n
    What if…<\/strong> AI search continues to grow at its current pace and, by late 2027, 40% of local commercial queries are answered by an LLM rather than a SERP? The businesses that survive this shift will be those whose data is structured, consistent, and present in the sources LLMs draw from. Directory listings aren’t just a defensive hedge against this scenario \u2014 they’re arguably the single highest-leverage preparation for it. The cost of being wrong about AI search is small. The cost of being right and unprepared is large.<\/p>\n<\/div>\n
    \n
    Quick tip:<\/strong> Before submitting to any new directory, run two checks. First, search the directory’s domain in Google with site:directoryname.com<\/code> and see if Google has indexed recent listings \u2014 if the latest indexed pages are months old, the directory is decaying and not worth your time. Second, click through three random listings and check whether they have current phone numbers; abandoned directories accumulate dead listings, which signals you should walk away.<\/p>\n<\/div>\n
    What the Evidence Suggests You Do Differently<\/h2>\n
    Three positions I’ll defend, each grounded in the data above.<\/p>\n
    Stop treating directory work as a one-time submission task.<\/strong> The evidence consistently shows that directory presence is an operating model, not a checkbox. Build a quarterly review cadence into your team’s calendar. Assign an owner. Treat it like you treat your CRM hygiene.<\/p>\n
    Reallocate aggressively from paid social to directory infrastructure.<\/strong> If your Meta CPAs have risen 40%+ over the past two years (they probably have), the marginal pound is producing less than it did. Directory work has a higher ceiling and a much longer half-life. The data justifies reallocating 10\u201315 points of budget. The risk of doing this is small; the upside is meaningful.<\/p>\n
    Audit your AI citation footprint monthly.<\/strong> This is the new SEO. Run the same ten commercial queries through ChatGPT, Claude, Perplexity, and Google AI Overviews on the first Monday of every month. Track which sources get cited. If a competitor is showing up and you aren’t, the gap is almost always traceable to directory and review-site presence.<\/p>\n
    The directory revival isn’t a marketing trend. It’s a structural response to fragmenting search behaviour, the rise of LLM-mediated discovery, and the rising cost of paid attention. Directories were boring infrastructure for a hundred years before the web; they’re going to be boring infrastructure for another fifty after it. Boring, in marketing, usually means it works.<\/p>\n
    Pull last quarter’s channel performance report. Recalculate CPA by channel including the half-life metric. Then look at your directory line item and decide whether what you’re spending matches what the numbers say it should be. That’s the conversation worth having before the next budget cycle closes.<\/p>\n","protected":false},"excerpt":{"rendered":"
    Here’s a number that broke my internal forecasting model last spring: businesses with optimised free directory listings receive 42% more customer inquiries than those without any directory presence at all. Not 4.2%. Not “a meaningful uplift.” Forty-two percent \u2014 a figure that, if you’d shown it to me in 2021 alongside the consensus that directories […]<\/p>\n","protected":false},"author":1,"featured_media":29103,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[767],"tags":[],"class_list":{"0":"post-28962","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-marketing"},"yoast_head":"\nWhy Business Directories Still Win Marketing in 2026<\/title>\n<meta name=\"description\" content=\"Here's a number that broke my internal forecasting model last spring: businesses with optimised free directory listings receive 42% more customer\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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