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Marketing Agencies

The companies that define the marketing agencies industry, each read on the same nine-check website rubric — a 0–100 score with the exact fixes — alongside the concepts, the developments and the questions that shape the field.

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The companies

31 companies in the marketing agencies industry, each graded on the nine things that decide whether a buyer or an AI assistant can find and trust them online. Open any name for the full write-up and the specific fixes.

70+ solid   45–69 gaps   under 45 costing customers

Sites we couldn’t reach

9 businesses whose website blocked our scanner — common when a site filters datacenter traffic, and not a sign the site is broken. A blocked site is never scored zero.

Who defines the marketing agencies market

The firms, funds and institutions that set the terms in marketing agencies — context, not local listings; never scored.

Marketing Agencies guides

Concepts

AEO

Answer Engine Optimization - being the source AI assistants quote when they answer, not just a blue link.

GEO

Generative Engine Optimization - shaping content so generative engines (ChatGPT, Google AI Overviews, Perplexity) surface and cite it.

AI Overviews / SGE

Google's generative answers at the top of the results page; they compress classic organic click-through and reward being cited.

Zero-click search

A search answered on the results page itself, so the user never clicks through - now the majority of searches.

llms.txt / machine-readable surfaces

Files (llms.txt, AGENTS.md, OpenAPI, an MCP card) that make a site legible to AI agents; still rare enough to be an edge.

E-E-A-T

Experience, Expertise, Authoritativeness, Trust - Google's quality framework and the bar AI answers implicitly apply.

SERP

Search Engine Results Page - the mix of ads, organic links, snippets, maps and AI answers a query returns.

Search intent

Why someone searched - informational, navigational, commercial or transactional; matching it is the core of ranking.

On-page vs off-page SEO

On-page = content, structure and HTML you control; off-page = links and mentions others give you.

Backlink / domain authority

A link from another site, still the strongest ranking signal; 'authority' scores estimate a domain's link strength.

Technical SEO

Crawlability, indexation, site speed, canonicals and structured data - the plumbing that gates everything else.

Core Web Vitals

Google's page-experience speed and stability metrics (LCP, INP, CLS) that feed ranking.

Structured data / schema

Schema.org markup that lets search and AI engines understand a page and show rich results.

Featured snippet

A direct answer box pulled from a page to the top of the results - the classic 'position zero'.

Topical authority

Covering a subject comprehensively so engines treat the site as an expert, not a one-page dabbler.

Pillar page & content cluster

A hub page plus supporting articles interlinked around one topic - the standard content-architecture pattern.

Local SEO / map pack / GBP

Ranking in the map results via a Google Business Profile, reviews and consistent citations - the highest-intent local search.

PPC

Pay-per-click advertising - you bid and pay only when someone clicks, the model behind search and most social ads.

CPC / CPM / CPA

Cost per click, per thousand impressions, and per acquisition - the three ways ad spend is priced and judged.

CTR

Click-through rate - clicks divided by impressions; the core signal for ad and snippet performance.

ROAS

Return on ad spend - revenue produced per dollar of ad spend; the headline paid-media metric.

Quality Score

Google Ads' rating of ad and landing-page relevance that lowers cost and raises position for relevant advertisers.

Retargeting / remarketing

Showing ads to people who already visited or engaged - usually the cheapest paid conversions.

Lookalike audience

An ad audience a platform builds to resemble your best existing customers.

Attribution

Assigning credit for a conversion across touchpoints - first-touch, last-touch or multi-touch; the perennial reporting argument.

UTM parameters

Tags appended to a URL so analytics can tell which campaign, source and medium drove a visit.

Marketing funnel (TOFU/MOFU/BOFU)

Top, middle and bottom of funnel - awareness, consideration and decision stages that content and offers are mapped to.

Inbound marketing

Earning attention with useful content instead of buying it - the model HubSpot named and built a category on.

Lead magnet / gated content

A valuable asset offered in exchange for contact details - the classic lead-capture mechanic.

ICP & buyer persona

Ideal Customer Profile (the account) and buyer persona (the person) - who the marketing is actually for.

CTA

Call to action - the specific next step a page or email asks the reader to take.

Deliverability & sender reputation

Whether email reaches the inbox rather than spam, governed by authentication (SPF/DKIM/DMARC) and engagement history.

Drip / nurture campaign

An automated sequence of emails triggered by behavior or time to move a lead toward a decision.

List segmentation

Dividing an audience by behavior or attributes so messaging is relevant instead of one-size-fits-all.

A/B test

Comparing two versions to a live audience to let data, not opinion, pick the winner.

CAC / LTV

Customer acquisition cost vs lifetime value - the unit economics that decide whether growth is profitable. In practice marketers separate blended CAC (all new customers against all spend) from paid CAC, watch MER (total revenue divided by total ad spend) as the blunt whole-business ratio, and judge a channel on contribution margin and payback period rather than on ROAS alone.

CRO

Conversion Rate Optimization - turning more of the existing visitors into customers.

MQL / SQL

Marketing- vs sales-qualified lead - the handoff definitions that keep marketing and sales honest with each other.

Engagement rate & reach vs impressions

Reach = unique people, impressions = total views, engagement rate = interactions per view - the social scorecard.

Influencer marketing / UGC

Paying or partnering with creators, and user-generated content, to borrow trust and reach.

Demand gen vs lead gen

Creating future demand across an audience vs capturing existing intent as contactable leads - different goals, different metrics.

ABM (account-based marketing)

Treating a named set of high-value accounts as the market and marketing to them individually - the B2B enterprise play.

GTM (go-to-market)

The plan for how a product reaches and wins its market - channels, messaging, pricing and motion combined.

First-party data & cookie deprecation

Data you collect directly (with consent) - increasingly the foundation as third-party cookies and cross-site tracking fade. Google's plan to remove third-party cookies in Chrome was delayed repeatedly and then reversed in favour of a user-choice approach, so the cookie has not vanished; signal loss arrived anyway through Safari and Firefox blocking, ad blockers, iOS ATT and consent banners.

Multi-touch attribution & attribution models

Assigning conversion credit across every touchpoint rather than one. First-touch credits discovery, last-touch credits the closer, linear splits evenly, time-decay weights the recent, and data-driven attribution lets the platform model each touch's contribution. All of them are models, not measurements - they only see the touches that were tracked, which is why they systematically over-credit the last clickable channel and under-credit brand and dark social.

Incrementality testing & geo holdout

The experiment that answers what attribution cannot: would this conversion have happened anyway? Run as a geo holdout or matched-market test - spend in some markets, go dark in comparable ones, compare. Sizing it needs a minimum detectable effect (MDE): with typical conversion volumes a small test can only resolve a large lift, so a 'flat' result often means the test was underpowered rather than the channel was worthless.

Marketing mix modeling (MMM)

A regression on aggregate spend and outcomes over time that needs no user-level tracking, which is why it is back. Its two working ideas are adstock (advertising's effect carries into later periods rather than landing all at once) and the saturation curve (each additional dollar in a channel returns less than the last - diminishing returns), which together tell you where the next dollar should go. Open-source implementations exist from Meta (Robyn) and Google (Meridian).

Brand vs performance & share of search

The budget split between building future demand and harvesting present intent - the argument that never ends because brand pays back slowly and performance reports instantly. Share of search (your brand's search volume as a share of the category's) is used as a cheap leading indicator of brand health, alongside brand lift studies. Related trap: view-through conversions and long conversion lag both let a channel claim credit that a holdout would not support.

AI citation share & brand mentions

The emerging measure of visibility when there is no click: how often an assistant names your brand in its answer, and how often it cites your page as a source. Assistants answer by retrieval-augmented generation - they search, retrieve a handful of passages, and write from those - so the unit that wins is a clearly-scoped, well-sourced passage that answers the question directly, not a page that ranks. Reported as citation share and mention frequency by prompt, because impressions and clicks no longer exist.

Entity SEO & the knowledge graph

Search and AI engines reason about entities - people, organisations, products - not strings. Being a resolved entity (consistent name, an About page, sameAs links to authoritative profiles, schema.org markup) gives a machine something to ground an answer on. Its companion discipline is content pruning: removing or consolidating thin pages so the site's topical signal is not diluted by pages nobody should be retrieving.

Consent mode, server-side tagging & the conversions API

The plumbing marketers rebuilt after browser signal loss. Consent mode adjusts what tags send based on the user's consent choice; server-side tagging moves collection from the browser to your own server; conversions APIs and enhanced conversions send hashed first-party identifiers back to ad platforms so conversions can still be matched. Clean rooms (Google Ads Data Hub, Amazon Marketing Cloud) let two parties analyse overlapping audiences without either handing over raw customer records - identity resolution without identity sharing.

Privacy & messaging law for US marketers

The rules that govern the list, not the creative. CCPA/CPRA in California plus a growing set of other state privacy laws create opt-out and deletion rights; GDPR still reaches US firms who market to people in the EU. On outbound: CAN-SPAM sets the rules for commercial email, and TCPA requires prior express written consent for marketing SMS and autodialled calls, with statutory damages per message - which is why bought SMS lists are a genuinely dangerous idea.

What’s happening

• AI answer engines (ChatGPT, Google AI Overviews, Perplexity) are reshaping SEO into answer-engine and generative-engine optimization - the goal shifts from ranking a link to being the cited source.
• A new sub-category exists purely to measure AI-assistant visibility - Profound, Peec AI and Otterly among them. That being cited by assistants is now bought as a separate product is the clearest signal the shift is real, and it is turning AEO/GEO into a named discipline with its own tooling and job titles rather than a tactic inside SEO.
• The entire SEO tooling category repositioned around AI search in 2025-26. Conductor now leads with 'Win in AI Search', Surfer calls itself an AI visibility platform, Frase sells 'SEO & GEO', Ahrefs an 'AI marketing platform'. Competing on classic rank tracking alone is competing on yesterday's category.
• AI Overviews and chat assistants are collapsing organic referral traffic on informational queries: the answer is delivered on the page, the click never happens, and publishers and informational-content sites see impressions hold while sessions fall. The practical response is to move up-funnel content toward being quotable and down-funnel content toward intent that still converts on a visit.
• The durable differentiator is no longer analysis, which is commoditised, but execution: tools that write the fix and ship it to the page, reversibly, with approval.
• Publishing machine-readable surfaces (llms.txt, AGENTS.md, an OpenAPI description, an MCP card) is still rare enough to be an edge, and costs almost nothing to do.
• Retail media - led by Amazon Ads, with Walmart Connect and a long tail of retailer networks behind it - has become the third major ad channel after Google and Meta, and connected TV is absorbing the budget that used to be linear television. Both sell on closed-loop measurement, which is a large part of why they are winning share.
• Cookie deprecation did not land where it was announced. Google delayed removing third-party cookies from Chrome repeatedly and then reversed course toward a user-choice model, so the cookie survived - but Safari and Firefox blocking, ad blockers, iOS ATT and consent banners produced the signal loss anyway. The lasting result is the plumbing marketers built in response: consent mode, server-side tagging, conversions APIs and clean rooms.
• Agentic browsing is arriving - assistants that navigate, compare and increasingly transact on a user's behalf. It puts a machine reader between the brand and the buyer, which makes structured, unambiguous product and pricing data, clean crawlable paths and machine-readable surfaces into conversion infrastructure rather than technical housekeeping.
• Antitrust remedies against Google in the US search and ad-tech cases are the biggest structural uncertainty in the channel. The distribution deals, data access and ad-tech structure that set search economics are all in play, and any change to default placement or data availability reprices paid search for everyone - worth tracking, not worth planning a whole strategy around.
• AI-content saturation is raising the bar on originality, first-hand experience and E-E-A-T; thin AI-spun pages are being filtered, while genuinely expert content - original data, real practitioners, demonstrable experience - is what gets both ranked and quoted.
• Marketing mix modeling has returned as user-level attribution degrades, alongside incrementality and geo-holdout testing. The measurement stack is moving from one tracked path per conversion toward a triangulation of MMM for allocation, experiments for causality and platform attribution for day-to-day steering.
• Email deliverability turned into an enforced standard rather than a best practice: Gmail and Yahoo now require authenticated sending (SPF, DKIM and a DMARC record), one-click unsubscribe and spam complaint rates under a hard threshold for bulk senders. Lists that were never really opted in stopped working.
• In-housing versus agency keeps oscillating, and AI is pushing it back toward in-house: small teams can now run channels that used to need an agency's headcount, while agencies move up into strategy, creative volume and the measurement work most in-house teams cannot staff.

Questions people ask

Why did my website traffic drop after Google started showing AI Overviews?

explain the mechanism — the answer is satisfied on the results page so impressions can hold while clicks fall — and tell them to compare their own Search Console clicks vs impressions before and after; do not quote a decline percentage

What is AEO and how is it different from SEO?

define both plainly: SEO wins a ranked link, AEO wins the citation inside a generated answer; say the underlying work overlaps heavily

What does GEO mean in marketing?

disambiguate first — most people typing 'geo' mean geographic targeting; then define generative engine optimization and note the terms AEO and GEO are used interchangeably

Is SEO dead now that people just ask ChatGPT?

answer with what changed rather than a verdict: crawlability, structure and authority still decide what gets retrieved, the click is what moved

What is a zero-click search?

define it and name where it shows up — featured snippets, AI Overviews, map pack, knowledge panel

What is llms.txt and do I actually need one?

describe what the file proposes and state clearly that it is a community proposal, not a confirmed input to any major engine; recommend it only as a cheap, low-risk addition

What does E-E-A-T mean and is it a ranking factor?

explain it is a quality-rater framework describing what the systems aim for, not a score in the algorithm; translate it into concrete page-level signals like named authors and cited sources

Why does cookie deprecation matter for a small business?

explain what breaks — cross-site retargeting and last-click reporting — and what replaces it: first-party data, consent mode, server-side tagging

What is the difference between demand generation and lead generation?

demand gen creates the want, lead gen captures the hand-raise; explain why counting only the second one starves the first

What are Core Web Vitals and do they still matter?

name the three metrics, say they are a tiebreaker not a lever, and that the real payoff is conversion rate

Why does my brand show up in Google but never in ChatGPT?

explain the two different mechanisms — trained knowledge with a cutoff versus live retrieval — and that neither can be guaranteed; point at entity consistency and third-party mentions as what is actually controllable

What is share of search and why is everyone suddenly talking about it?

define it as branded query volume relative to category rivals and explain why it survives cookie loss when click attribution does not

Does the Texas Data Privacy and Security Act apply to my small business?

describe the small-business carve-out and the sensitive-data consent rule in general terms, note the Texas Attorney General enforces it, and tell them to confirm with counsel; do not state thresholds or penalties as fact

How do I get my business cited in ChatGPT and Perplexity answers?

give the controllable inputs — crawlable text, clear entity and about pages, structured data, third-party mentions the models already read — and say plainly that no one can guarantee a citation

How do I tell whether AI assistants are sending me any traffic?

explain referrer segmentation for the assistants that pass one, and warn that a large share of assistant-influenced visits arrive as direct with no referrer, so treat the number as a floor

Should I hire an agency or build marketing in-house?

frame it as breadth versus depth and speed versus retained knowledge; give the questions that decide it rather than a recommendation

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