DEV Community: rana fathima

The DIY GEO Playbook for Consultancies: What You Can Do In-House (and What You Can't)

rana fathima — Wed, 28 Oct 2026 10:27:54 +0000

Consultancies in Manchester and across the North West are being pitched "done-for-you GEO" retainers. Some are excellent. Some are an expensive way to do things your own team could handle.
This post is a practical playbook for the done-for-you geo agency vs doing it yourself decision. It's based on Kiyado's article on GEO vs SEO vs AEO vs AIO and is aimed at the technically minded person who usually ends up owning the website.
The four layers (and who can own them)
Layer
What it is
DIY difficulty
SEO
Pages crawlable, indexed, ranking
Medium; technical issues may need a specialist
AEO
Content shaped into liftable answers
Low; your consultants know the answers
AIO
Appearing in Google's AI Overviews
Low to medium; mostly follows SEO and AEO
GEO
Brand named and recommended by AI assistants
High; mostly off-site and slow

The article frames these as four layers of one job, so even if you outsource part of it, one person should own the whole plan.
Step 1: Run a technical SEO baseline
Start with Search Console:
Pages report: list every service, sector and people page. Anything not indexed is invisible to every layer above.
Performance report: filter by your priority queries. Note anything beyond page two.
Then a quick crawl check:

Check that key pages return 200 and aren't noindexed

for url in /services/ /sectors/ /people/ /insights/; do
curl -s -o /dev/null -w "%{http_code} $url\n" "https://example-consulting.co.uk$url"
curl -s "https://example-consulting.co.uk$url" | grep -i 'name="robots"'
done
If you find redirect chains, JavaScript-only content or canonical confusion, that's where a specialist pays for themselves.
Step 2: Rewrite answers (AEO)
AEO differs from SEO in three ways, according to the article: it targets the single answer slot, rewards a clean answer under a question-style heading, and is measured by ownership rather than clicks.
For each service page:

List the five questions clients ask in first meetings.
Add each as an H2.
Write a direct answer immediately below. Practitioners often suggest 40–60 words; the article calls it a guideline, not a rule. ## How long does an operational due diligence review take?

A typical operational due diligence review takes four to six
weeks for a mid-market acquisition. It covers people,
processes, systems and key risks, and ends with a written
report and a partner briefing. Timelines shorten when the
target provides data-room access early.
Your consultants can draft these in an afternoon. This layer is very DIY-friendly.
Step 3: Track AI Overviews (AIO)
Pick 20 priority queries. Once a month, record:
query,rank,snippet_owner,ai_overview,cited_us
"operational due diligence manchester",4,competitor,yes,no
"interim cfo north west",7,none,no,no
Pages that rank in the top five but aren't cited usually need clearer answers (Step 2) and more visible evidence: named consultants, credentials and examples.
Step 4: Build a GEO prompt baseline
Run the same prompts monthly across ChatGPT, Gemini and Perplexity:
prompts:

"Which consultancies in Manchester specialise in operational due diligence?"
"Best interim CFO providers in the North West of England"
"What is Example Consulting known for?"
"Example Consulting vs " Record named, cited and accurate for each. Use official APIs where available, or collect manually, and respect each provider's terms. Step 5: The off-site work (the hard part) The article explains that GEO goes further than AEO in three ways: engines combine many sources, answer "who should I use" questions and depend on what the wider web says about you. For a consultancy, that means: Consistent firm and consultant details on LinkedIn, professional bodies and directories Speaker pages from events and conferences Commentary in trade and regional business press Client case studies on partner or client sites (with permission) Reviews on platforms where your buyers look The article cites G2's 2026 research: buyers trust AI recommendations but still check them against review sites. This is where DIY usually stalls. It isn't technical; it's persistent outreach and relationship work. Many firms keep Steps 1–4 in-house and bring in help for Step 5. Decision matrix Use the article's diagnostic to decide: Finding DIY? Get help? Pages not indexed or beyond page two If you have a technical person If issues are complex Ranking, but no snippets or AI Overviews Yes Rarely needed Competitors named by AI, you aren't Partly Often worth it All three Plan in-house Execute with a partner

Step 6: Keep a single fact sheet
Most identity problems come from people describing the firm differently: a partner's speaker bio says one thing, the website another, an old directory entry a third. Keep one fact sheet in version control or a shared document:
firm: "Example Consulting"
one_liner: "Operational due diligence and interim finance leadership for mid-market deals in the North West."
offices: ["Manchester"]
services: ["Operational due diligence", "Interim CFO", "Post-merger integration"]
Every bio, listing and proposal template should copy from it. When something changes, update the sheet first, then everything that uses it. It's the cheapest GEO improvement available, and it's entirely DIY.
Mistakes to avoid
Splitting vendors by acronym. The article warns that layers share pages and content; separate vendors can work against each other.
Starting with GEO before fixing indexation. GEO stalls on an uncrawlable site.
Measuring only rankings. You'll miss three of the four layers.
Expecting guarantees. No one controls AI answers.
A realistic in-house rhythm
Monthly: Steps 3 and 4 tracking (about half a day)
Quarterly: rewrite five service pages (Step 2)
Ongoing: one piece of off-site work per month (Step 5)
That's enough to make steady progress without a large retainer. Review the rhythm after two quarters: if the prompt baseline isn't moving and Step 5 keeps slipping, that's the clearest sign it's time to bring in outside help for the off-site layer.
If you'd like an outside audit to decide what to keep in-house, Kiyado offers one free: SEO and GEO for Manchester businesses →

Docs as GEO: 8 Ways to Make Developer Documentation Quotable by AI Assistants

rana fathima — Wed, 28 Oct 2026 10:10:21 +0000

Developers increasingly ask AI assistants questions like "Which feature-flag platforms support server-side evaluation in Go?" The answer often draws on documentation. If your docs are hard to parse, you lose that recommendation, even if your product is the best fit.
This guide shows how to make docs AI-friendly. For the strategic background, Kiyado's explainer on GEO is a short read, and it's useful context before you evaluate the best tools for generative engine optimization.

Lead every page with a factual summary The first paragraph of each docs page should answer "what is this and what does it support?" on its own: "Example Flags is a feature-flag platform with server-side SDKs for Go, Java, Python and Node.js. Flags evaluate locally in under 1 ms using a cached ruleset synced every 30 seconds." AI engines extract passages. This one survives extraction.
Name the product, not "it" Pronouns break when passages are lifted. Prefer "Example Flags' Go SDK supports…" over "It supports…" at the start of sections.
Keep a single source of truth for capabilities Supported languages, regions, limits and compliance certifications often drift between docs, marketing pages and changelogs. Generate them from one data file: # capabilities.yml – single source of truth product: Example Flags sdks: [go, java, python, nodejs] evaluation: server-side, local cache sync_interval_seconds: 30 regions: [ca-central, us-east, eu-west] certifications: [SOC 2 Type II] import yaml

caps = yaml.safe_load(open("capabilities.yml"))
summary = (
f"{caps['product']} supports server-side SDKs for "
f"{', '.join(s.title() for s in caps['sdks'])}, with data hosted in "
f"{', '.join(caps['regions'])}. Certifications: {', '.join(caps['certifications'])}."
)
print(summary) # reuse in docs, marketing pages and partner listings
One source means fewer contradictions, and contradictions make AI engines hesitate.

Render docs as static HTML Client-side-only docs can be invisible to some crawlers. Use a static site generator or server rendering so headings, code and text are in the initial HTML.
Use descriptive headings "Overview" and "Getting started" are fine, but add specificity: "Install the Go SDK (Go 1.21+)", "Evaluate flags server-side". Headings help retrieval and give engines context.
Write a changelog that says what changed, plainly "2026-09-14: Added Ruby SDK (beta). Raised the flag-evaluation rate limit to 10,000 requests per second on the Team plan." Specific changelog entries are frequently cited when people ask about new capabilities.
Add comparison and migration pages Developers ask, "How do I migrate from Competitor X to Example Flags?" An honest, specific migration guide is both helpful and highly quotable.
Treat llms.txt as optional An llms.txt file is an emerging convention for pointing AI systems at key content. It's cheap to add, but major engines haven't committed to it as a standard, and it won't fix vague docs. Prioritise steps 1–7. Worked example: a docs page before and after Here's how the principles combine on one documentation page for a Toronto developer-tools startup. Before: # Getting started It's easy to get going! Just install it and you're ready. After: # Getting started with Example CLI

Example CLI is an open-source command-line tool for deploying
static sites to AWS S3 and CloudFront. It requires Node.js 18+
and an AWS account. Install it with npm, authenticate once,
and deploy with a single command.

Install Example CLI

Authenticate with AWS

Deploy your first site

The "after" version passes every test in this post. The first paragraph is a self-contained summary. The product is named instead of "it". The headings describe exactly what each section does. And because it's plain HTML when rendered, any crawler can read it.
Make it part of your workflow
Docs drift because nobody reviews them for clarity, only for accuracy. Add three questions to your docs pull request template:

Does the first paragraph say what this page is for, in a sentence someone could quote?
Is the product named rather than referred to as "it" or "the tool"?
Do the headings describe the task, not just the topic? Three checkboxes cost reviewers seconds. Over a year, they change the quality of everything an AI engine can find about your product. Pair them with a linter rule that flags pages without a summary paragraph, and the habit enforces itself. Common objections "Our docs are for developers, not marketers." True, and developers increasingly ask AI assistants how to use your product. Clear summaries help them as much as any engine. "We'll lose our brand voice." You won't. A factual first paragraph can be followed by as much personality as you like. Only the opening needs to be plain. "We don't have time." Start with the ten pages that get the most traffic. That's usually an afternoon's work for one technical writer. Measuring the effect Use the ten-minute test from the Kiyado post, adapted for developers:
Which [category] tools support [language/feature]?
How do I [common task] with [your product]?
[Your product] vs [competitor] for [use case]
What are the limits of [your product]'s free tier? Score each answer: named, cited (links to your docs) and accurate. Repeat monthly. What the research says The 2024 paper that named GEO (Princeton, Georgia Tech, the Allen Institute for AI and IIT Delhi; KDD 2024) found that evidence-rich content was used more often (gains of up to 40%, varying by domain), and that keyword stuffing had little or negative effect. Clear, factual docs are evidence. A practical rollout Week 1: Add factual summaries to your 10 most-visited docs pages. Week 2: Create capabilities.yml and wire it into docs and marketing. Week 3: Fix rendering and headings; publish one migration guide. Week 4: Run the test and record a baseline. Searches for an ai seo agency toronto suggest Toronto's software companies are starting to treat AI visibility as an engineering concern, not just a marketing one. If you'd like an outside review, Kiyado's Toronto team offers a free audit: SEO and GEO for Toronto businesses →