Outdoor Marketing Benchmarks 2026: The Q3 Southeast Baseline Heading Into Booking Season
Every outdoor operator in the Southeast has a hunch about where they stand online. Most of those hunches are wrong in the same direction: operators who have been booked solid for twenty years assume their digital footprint must be fine, and operators who just paid for a new website assume they have pulled ahead. The only way to know is to measure the same things the same way across a large enough set of businesses that the patterns stop being anecdotes.
That is what this report does. It is the first quarterly edition of the Pine & Marsh outdoor marketing benchmark, built only on the audit work behind our flagship study, The State of Outdoor Marketing in the Southeast: Data From 2,206 Outfitter Audits. We have not added outside surveys, borrowed industry averages, or estimates. Every number below traces to our state master data files or to the research summary built from them.
Because this is the first edition, it is a baseline, not a trend report. There is no prior quarter to compare against, and we will not pretend otherwise. What it gives you is a fixed, dated reference point: where Southeast outfitters, guides, lodges, and charter operators stood on digital health, AI-answer visibility, owned audience, and structured data heading into the fourth-quarter booking season, when duck camps fill, deer leases book next year, and gift-certificate sales peak. Every future edition will report these same metrics in the same order, so that when something moves, you will be able to see it.
How the Q3 2026 Benchmark Was Built
The dataset covers 2,206 operators across 88 sub-regions in ten states: Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, South Carolina, Tennessee, and Virginia. Seven of those states were audited across ten sub-regions each; Florida, Georgia, and South Carolina were audited across six. The audits ran as rolling, session-based work, with each session adding or rounding out one or two sub-regions, and the final state builds closed on April 22 and 23, 2026. The research summary's data cutoff is April 22, 2026. North Carolina, the eleventh state Pine & Marsh serves, is not part of this scored dataset, so it carries no figures in this edition.
Sampling is the part most benchmarks get wrong, and it was the first thing we fixed. Our earliest sessions over-sampled businesses that already ranked on the first page of Google, which made the whole category look more mature than it is. From the third session on, every vertical in every sub-region was sampled across three tiers: top-tier operators (page-one rankings, owned content, a claimed and optimized Google Business Profile), mid-tier operators (page-two or page-three rankings, a basic site, directory listings), and lower-tier operators (Facebook-only pages, free-tier website builders, directory-only listings, long-operating businesses that are close to invisible online). Operators were found through Google, state tourism directories, hunting and fishing directories, review sites, Facebook search, state agency references, and state business registries when no website existed.
Each record carries the same fields: profile details, social channels, email newsletter, paid-advertising signals, content and publishing, organic ranking, Google Business Profile status, local pack presence, AI-answer visibility (rated low, medium, or high based on whether the operator is named in ChatGPT and Perplexity answers to category queries), schema markup, FAQ presence, service depth, and a composite digital health score on a ten-point scale. The composite blends website quality (the heaviest weight), social presence and publishing cadence, Google Business Profile and local signals, and AI and content signals. The full rubric is laid out in How We Score: Inside the Digital Health Audit Methodology.
We also owe you the caveats, because a benchmark that hides its limits is not worth citing. Backlink, domain authority, and ad-spend signals are qualitative; the dataset is not built on SEO-tool or ad-platform integrations. Schema findings are inference-based for records that were not inspected at the code level, and fields that were not spot-verified carry conservative defaults derived from the operator's composite score. Google Business Profile status was populated consistently in some states and unevenly in others. AI visibility is dated to the session in which it was checked, and answer engines change. South Carolina's email newsletter field was coded in a way that undercounts real newsletters, so we exclude South Carolina from the email comparison below.
The Headline Numbers: Where the Southeast Stands
The mean composite digital health score across all 2,206 operators is 5.57 out of 10. The median is 6. Those two numbers alone tell the story of the category: the typical Southeast outdoor business has a digital presence that is roughly half built, solid enough to support an existing reputation and structurally too thin to compete for new customers who start their search in an AI answer.
The distribution matters more than the average. Of the 2,206 audited operators, 14.1 percent score 8 or above, 26.2 percent score 4 or below, and 59.7 percent fall in the 5-to-7 middle band. Only 4.3 percent score 9 or 10, and 5.4 percent score 2 or lower. The middle band is the structural majority in the dataset, and from the point of view of a search engine or an answer engine, a 5 and a 7 often look alike: a working website, a Facebook page, a claimed listing, and almost nothing that tells a machine what the business actually sells, where, when, and for whom.
AI-answer visibility is narrower than digital health. About 17 percent of operators were rated high, meaning they were consistently named in AI answers for category queries in their region; about 50 percent were rated medium and about 33 percent low. Being a good business with a decent website does not, by itself, put you in the answer.
The owned-asset numbers explain much of that gap. Where Google Business Profile status was confirmable, 82.4 percent of operators had a claimed listing. Email newsletter penetration sits at 38.7 percent. Schema markup beyond website-platform defaults sits at 20.4 percent, which means roughly 80 percent of operators run none. Dedicated FAQ pages sit at 12.2 percent, and roughly 85 percent of operators have no dedicated FAQ at all. The pattern is consistent: the assets that are visible and easy (a map listing) are widely adopted, and the assets that are invisible to a casual visitor but readable by machines (structured data, organized answers) are rare.
Digital Health by State
State means cluster closer together than most operators expect, but the spread inside each state is wide. Here is the Q3 2026 baseline, with the share of each state's audited operators in the high band (8 or above) and low band (4 or below), computed from the state master files.
Virginia: 258 operators, mean 6.31, 15.9 percent high, 5.8 percent low
South Carolina: 105 operators, mean 5.92, 31.4 percent high, 29.5 percent low
Georgia: 99 operators, mean 5.86, 26.3 percent high, 25.3 percent low
Tennessee: 250 operators, mean 5.78, 14.8 percent high, 22.0 percent low
Arkansas: 259 operators, mean 5.69, 10.8 percent high, 18.9 percent low
Louisiana: 260 operators, mean 5.68, 12.7 percent high, 20.0 percent low
Florida: 196 operators, mean 5.67, 14.3 percent high, 25.0 percent low
Kentucky: 261 operators, mean 5.61, 8.8 percent high, 22.2 percent low
Mississippi: 252 operators, mean 4.85, 15.1 percent high, 46.4 percent low
Alabama: 266 operators, mean 4.76, 9.0 percent high, 47.7 percent low
Three shapes show up in that list. Virginia is the compact state: the highest mean in the dataset and the smallest low band by far, with 78 percent of its operators in the middle. Its weakness is not a floor problem but a ceiling problem, which the AI numbers below make plain. South Carolina and Georgia are the dispersed states: they lead the dataset in high-band share, pulled up by a handful of nationally known resort and sporting properties, but each still has roughly a quarter or more of its operators in the low band. A state average there describes almost nobody. Alabama and Mississippi are the floor states: close to half of their audited operators score 4 or below, and their medians are 5 rather than 6. In those two states, the highest-impact work is foundational rather than incremental.
The practical lesson is that a state average is a poor proxy for your competition. The operators you actually compete with sit in your sub-region and your vertical, and the spread inside a single state can run from a 10 to a 1.
AI-Answer Visibility and Owned Audience by State
AI visibility does not track digital health neatly, and that mismatch is the most useful finding in this edition. The share of each state's operators rated high for AI-answer visibility:
South Carolina: 35.0 percent
Georgia: 30.3 percent
Florida: 27.8 percent
Tennessee: 22.4 percent
Mississippi: 20.6 percent
Alabama: 19.9 percent
Kentucky: 17.2 percent
Louisiana: 13.1 percent
Virginia: 5.0 percent
Arkansas: 3.5 percent
Virginia has the best mean digital health in the dataset and the second-lowest AI high-visibility share. Arkansas sits mid-pack on digital health and last on AI visibility. Both states have credible operators and competent websites; what they lack, relative to South Carolina, Georgia, and Florida, is the dense layer of national travel and sporting editorial that answer engines have absorbed. Operators in the top three states partly inherit visibility from the press coverage around them. Operators in Virginia and Arkansas have to build it themselves, through owned editorial, structured data, and third-party citations. We cover that mechanism in detail in Why an AI Overview Trusts Ducks Unlimited More Than It Trusts Your Homepage.
Email newsletter penetration, the most durable owned-audience channel, runs from 50.8 percent of audited operators in Virginia to 25.0 percent in Alabama. Tennessee (46.0 percent), Kentucky (43.3 percent), and Florida (40.6 percent) follow Virginia; Arkansas (36.3 percent), Georgia (32.6 percent), Mississippi (31.6 percent), and Louisiana (30.8 percent) sit below the dataset rate; Alabama trails. In the research summary, operators with a recurring newsletter were heavily over-represented in the high digital health band. South Carolina is excluded here because of the coding issue noted in the methodology.
Taken together, the state view sorts into a simple grid. South Carolina, Georgia, and Florida combine above-average digital health with high AI visibility. Virginia and Tennessee pair solid digital health with lagging AI visibility, which is the most immediately fixable position in the dataset, since the foundation is already there. Alabama and Mississippi trail on both measures, and operators there who build the basics first will be competing against a thin field.
Findings by Vertical
The state view hides the most important variable: what you sell. Vertical mix differs sharply by state, and the same state can hold a mature rafting scene and a near-invisible hog-hunting scene. These are the vertical baselines from the research summary, for verticals with enough audited operators to report.
Eco tours and wildlife viewing
83 operators, mean digital health 6.35, 20.5 percent in the high band, 26.6 percent rated high for AI visibility. This is the strongest vertical we measured. Naturalist-led operators with structured trip pages consistently outperformed generic tour positioning in AI answers. One anonymized pattern: in several regions, operators that published regulatory and conservation explainers for the wildlife they show guests earned trust signals that their louder competitors did not, while most peers published none.
Whitewater rafting
35 operators, mean 6.31, 28.6 percent high band, 25.7 percent high AI visibility. A small, mature operator pool with sophisticated booking software and real editorial competition. This is one of the few verticals where AI answers tended to name owned operator brands rather than aggregators.
Fly fishing and trout
103 operators, mean 6.18, 19.4 percent high band, 17.2 percent high AI visibility. Fly fishing customers read, subscribe, and click, and the vertical's fishing-report habit maps well to search. Yet only about a third of the fly-fishing operators we audited publish a recurring report at any cadence, and tailwater operators rarely turn their generation schedules and hatch timing into owned content. An anonymized observation: in one mountain sub-region, a shop that has published a weekly report for two decades holds a citation position its competitors cannot realistically catch, while guides a few miles away with comparable reputations are absent from AI answers entirely.
Paddle, kayak, and canoe
239 operators, the largest vertical in the dataset, mean 5.83, 15.5 percent high band, 17.2 percent high AI visibility. Booking software is well adopted; content infrastructure is not. Operators with structured trip product pages and naturalist editorial surface in AI answers; pure rental operators rarely do.
Offshore charter fishing
80 operators, mean 5.81, 18.8 percent high band, 18.8 percent high AI visibility. Offshore fleets tend to invest in vessel photography and booking-platform listings and under-invest in content authority and structured trip pages. Outside a handful of named fleets per region, aggregators occupy most of the AI surface.
Hunting lodges and preserves
64 operators, mean 5.91, 18.8 percent high band, 18.0 percent high AI visibility. Strong brand investment, uneven content. Lodge AI answers lean heavily on editorial citations. An anonymized pattern worth every lodge owner's attention: a coastal sporting property that changed hands and became public land years ago is still described by AI answers as an active private club. Answer engines remember old facts long after they stop being true, which cuts both ways for lodges that have changed ownership, names, or booking models.
Inshore and flats fishing
144 operators, mean 5.39, 10.4 percent high band, 18.2 percent high AI visibility. The most operator-dense saltwater vertical, with enormous variance. AI answers split between a few legendary named guides, driven by press coverage, and aggregator defaults. Competent mid-tier captains with real websites are largely missing from AI answers. Booking marketplaces and marina sites captured head-term search across nearly every coastal sub-region we audited.
Waterfowl hunting
100 operators, mean 5.01, 8.0 percent high band, 5.3 percent high AI visibility. Waterfowl carries the strongest cultural identity of any vertical we scouted and one of the weakest AI positions. Waterfowl AI answers default to conservation-organization and magazine archives rather than operators, and multi-generational and conservation stories are buried on About pages instead of published as content. For flyway-level positioning, see The Southeast Waterfowl Flyway Playbook.
Upland, plantation, and sporting clays
117 operators, mean 4.91, 17.9 percent high band, 23.4 percent high AI visibility. The most polarized vertical: a top tier with heritage, endorsements, structured FAQs, and published operational detail occupies most AI answers, while the majority of operators are essentially absent. This vertical also produced the dataset's clearest infrastructure failures. One anonymized case: a working quail property with decades of brand history whose primary domain now redirects to an unrelated website, sending every word-of-mouth visitor and every AI-referred prospect to a dead end.
Bass, crappie, and lake fishing
135 operators, mean 4.86, 3.0 percent high band, 9.2 percent high AI visibility. Some of the largest gaps in the dataset between fishery quality and digital presence. Destination reservoirs carry Facebook-first, web-thin guide layers. The clearest counterexample is anonymized but instructive: on one large Southeastern reservoir, a single catfish operation owns the AI answers for its niche because it publishes structured, specific content and its peers publish almost nothing.
Multi-species hunting guides
27 operators, mean 4.48, 3.7 percent high band, 3.8 percent high AI visibility. The most fragmented and Facebook-first vertical, with the highest share of operators lacking an owned website. AI answers here default to state agency pages and directories.
What the Baseline Says About AI Search
Four signals separated AI-cited operators from the rest across states and verticals. First, organized answers: operators with dedicated, structured FAQ content were over-represented in AI citations relative to their organic rankings. Second, structured data: Organization, LocalBusiness, and Service markup in JSON-LD, even partially implemented, moved operators toward the cited tier. Third, publishing cadence: weekly reports, trip recaps, and seasonal forecasts that compound over years. Fourth, third-party citations: tourism-board partnerships, conservation-organization affiliations, endorsement programs, and press mentions. Niche specificity amplified all four; single-species and single-population specialists outperformed generalists in AI answers.
One platform change since our audit cutoff belongs in this baseline. Google's Search Central changelog announced that FAQ rich results would stop appearing in Google Search starting May 7, 2026, and the FAQ rich result documentation was removed in June 2026. That ends the special search snippet, not the value of answers. Google still describes structured data as a standard way to help Search understand a page's content, and in our data the operators that answer clients' real questions in clear, organized language are the ones answer engines quote. Write the answers for people first; mark up the page so machines can read it. Our field guide, The FAQ Block an Answer Engine Can Actually Cite, walks through the build, and Google AI Overviews for Outfitters covers the wider search picture.
The second AI finding is hygiene. Across the dataset we documented operators that had closed, sold, changed ownership, moved to public ownership, or lost their domain and were still described by AI answers as active businesses. The reverse risk applies to active operators: if your hours, booking model, ownership, or season changed and your website, Google Business Profile, and directory listings do not say so clearly, answer engines will keep repeating the old version. A quarterly check, asking ChatGPT and Perplexity the questions your clients ask and comparing the answers against reality, belongs on every operator's calendar.
What This Benchmark Does Not Measure
Our original plan for this edition included seasonal Meta and Google ad-cost observations for hunting categories heading into Q4. We are leaving them out. Our audit records whether an operator shows paid-advertising signals, but it does not capture CPM, CPC, or spend, and we will not publish ad-cost numbers we did not measure. If you run paid campaigns, the most reliable Q4 benchmark you have is your own: pull last October through December from your ad accounts, note cost per lead and cost per booking by month, and budget against that rather than against an industry figure that may describe businesses nothing like yours.
The same discipline applies to everything else in this report. Aggregator capture is reported here as an observed pattern, not a scored index, because the dataset treats it qualitatively. AI visibility is a session-dated rating, not a continuous tracking feed. Where a number could not be traced to the master files or the research summary, it is not here. Future editions will add measured fields only when the audit actually captures them, and will say so when they do.
Fix This Quarter: Prescriptions by Vertical
The baseline is only useful if it changes what you do between now and the end of the year. These prescriptions follow directly from the gaps the data shows in each vertical.
Waterfowl outfitters: publish one substantial, structured page on your flyway, your habitat, and how your season actually runs, with a clear question-and-answer section, before the late-season and next-year deposit conversations start. With 5.3 percent of the vertical rated high for AI visibility, the field is close to empty.
Upland and plantation operators: check your domain renewal, hosting, SSL, and redirects this week, then move your heritage story from the About page into headline content. The vertical's infrastructure failures are common enough to be a category risk.
Bass, crappie, and lake guides: pick the one species, technique, or season you are best known for and build a specific page around it. Only 3.0 percent of this vertical scores in the high band, so specificity wins quickly.
Inshore and offshore captains: build structured trip pages on your own site (trip length, species by season, what is included, how to book) so that you are not dependent on a marketplace listing to describe your business.
Fly shops and trout guides: if you fish a tailwater or a named stream, start or restart a recurring report. It is the most replicable content habit in the dataset, and only about a third of the vertical does it.
Lodges and preserves: confirm that every listing, profile, and AI answer reflects your current ownership, booking model, and season, and create a dedicated page for corporate and group trips if that revenue matters to you.
Paddle, rafting, and eco-tour operators: you lead the dataset, so protect the lead. Add naturalist and regulatory explainers, and keep trip pages current as seasons change.
Every vertical: if you have no email capture with a real recurring send, add one before holiday gift-certificate season. With 38.7 percent penetration across the dataset, an owned list is still a competitive advantage rather than table stakes. Our email-capture benchmark breaks the gap down further.
The Metrics Every Future Edition Will Repeat
A benchmark earns its value through repetition, so this edition fixes the schema. Each future quarterly edition will report, in this order: the sample (operator count, sub-region count, states, and audit dates), the mean and median composite digital health score, the share of operators in the high, middle, and low bands, digital health and band shares by state, AI-answer visibility shares by state and vertical, email newsletter penetration, Google Business Profile claim rate where measured, schema markup and FAQ adoption, and vertical baselines for every vertical with enough audited operators to report. Every edition will state its data cutoff and its caveats, and change figures will appear only where the same operators or the same sub-regions were measured twice.
That last rule matters. A score that rises because we sampled different businesses is not a trend; it is noise dressed up as news. Our plan to re-audit the full dataset on a recurring basis is what will make real comparisons possible. Until then, this edition is the line in the sand.
Work with Pine & Marsh
If you want to know where your own operation lands against this baseline, we will run the same audit on your business: digital health, AI-answer visibility, Google Business Profile, email, structured data, and the specific gaps your competitors have left open in your sub-region.
Book a discovery call or request a free marketing check through pineandmarsh.com. We work only with outdoor businesses in the Southeast, and we will tell you plainly what to fix first before the busiest booking months of the year.
Frequently Asked Questions
What data is the Q3 2026 benchmark based on?
It is based entirely on the Pine & Marsh outfitter audit dataset: 2,206 operators across 88 sub-regions in ten Southeastern states, audited in rolling sessions with a data cutoff of April 22-23, 2026. No outside survey data, ad-platform data, or estimates were added. Every figure in the report traces to the state master data files or to our published research summary.
What is the average digital health score for Southeast outfitters?
The mean composite digital health score across all 2,206 audited operators is 5.57 out of 10, and the median is 6. About 14 percent of operators score 8 or higher, about 26 percent score 4 or lower, and roughly 60 percent sit in the 5-to-7 middle band.
Which Southeast state has the highest outfitter digital health score?
Virginia leads the dataset with a mean of 6.31, followed by South Carolina at 5.92 and Georgia at 5.86. Alabama (4.76) and Mississippi (4.85) are at the bottom, and both have close to half of their audited operators in the low band of 4 or below.
How many outfitters are visible in AI answers like ChatGPT and Perplexity?
About 17 percent of audited operators were rated high for AI-answer visibility, about 50 percent medium, and about 33 percent low. State shares of high AI visibility range from 35.0 percent in South Carolina to 3.5 percent in Arkansas.
Which outdoor verticals have the strongest and weakest digital health?
Eco tours and wildlife viewing (6.35), whitewater rafting (6.31), and fly fishing (6.18) lead the verticals we measured. Multi-species hunting guides (4.48), bass and lake fishing guides (4.86), upland and plantation operators (4.91), and waterfowl outfitters (5.01) trail.
Does this report show changes from last quarter?
No. This is the first edition, so it is the baseline. There is no earlier quarter to compare against, and we have not re-audited the dataset since the April 2026 cutoff. Future editions will report the same metrics in the same order so that real movement can be measured.
Why does the report not include Meta or Google ad cost benchmarks?
Our audit records whether operators show paid-advertising signals, but it does not capture CPM, CPC, or spend data, so we have no measured ad-cost figures to publish. Rather than print borrowed or estimated numbers, we recommend pulling your own Q4 results from last year in your ad accounts and using those as your budget baseline.
What share of outfitters use schema markup and FAQ pages?
In the cleaned dataset, 20.4 percent of operators run schema markup beyond their website platform's defaults, and 12.2 percent have a dedicated FAQ page. Schema verification was partly inference-based, so treat these as close estimates rather than a DOM-level census.
Is FAQ schema still worth adding now that Google dropped FAQ rich results?
Google stopped showing FAQ rich results in Search as of May 7, 2026, per its Search Central changelog, so the markup no longer earns a special search snippet. In our audit, though, operators with real, structured question-and-answer content were over-represented among those AI answer engines cite. The value is in the clear answers on the page, not the snippet.
What should an outfitter fix before the Q4 booking season?
Start with what the data shows is missing most often: an email capture with an actual recurring send, a claimed and complete Google Business Profile, and a page of real answers to the questions your clients ask. Then confirm your domain, hosting, and business status are current everywhere AI engines might be reading about you.
Sources
Pine & Marsh Research Desk -- State master data files for Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, South Carolina, Tennessee, and Virginia (2,206 records, state builds completed April 22-23, 2026) -- internal dataset, not published -- accessed October 2026
Pine & Marsh Research Desk -- The State of Outfitter Marketing: A 10-State Audit of Digital Health, Search Visibility, Industry Patterns, and Notable Case Studies (data cutoff April 22, 2026) -- internal research document, not published -- accessed October 2026
Pine & Marsh -- The State of Outdoor Marketing in the Southeast: Data From 2,206 Outfitter Audits -- https://www.pineandmarsh.com/post/the-state-of-outdoor-marketing-in-the-southeast-data-from-2-206-outfitter-audits-across-11-states -- accessed October 2026
Google Search Central -- Latest Google Search Documentation Updates (May 8, 2026 and June 15, 2026 FAQ rich result entries) -- https://developers.google.com/search/updates -- accessed October 2026
Google Search Central -- Intro to How Structured Data Markup Works -- https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data -- accessed October 2026
Google Business Profile Help -- Tips to improve your local ranking on Google -- https://support.google.com/business/answer/7091 -- accessed October 2026
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