SEO · ASO · AI Search · Performance
IG Ranks.
Does IG
Get Found?
A growth strategy for organic visibility, AI search authority, and app store performance.
375K
organic visits / month · UK
£83M
estimated traffic value · UK
4.26M
HL organic visits — the ceiling
Jinnat Ul Hasan
Wednesday 17 June 2026 · Cannon Bridge House
Content· Technical SEO· AI Search Visibility· ASO· 3-Phase Plan
01 / 09
The Opportunity
IG has real authority.
The question is whether it gets found.
IG already has the link profile and brand presence to dominate this space. The gap isn't ranking. It's getting cited where high-intent users are now asking their questions first.
Rankings · Ahrefs June 2026
375K monthly visits is a strong base. AJ Bell drives 47% more traffic on a near-identical keyword footprint. The gap isn't authority. It's coverage.
375K
organic visits / month · UK
21,056
keywords ranking
6,481
in pos 1–3
The Ceiling · Ahrefs June 2026
Hargreaves Lansdown shows what's achievable in this sector. Both are established, FCA-regulated UK financial brands. The gap is strategy and keyword coverage, not an authority deficit that takes years to close.
4.26M
HL organic visits / month
57,389
HL keywords
23,708
HL pos 1–3
AI Citation · Manually tested June 2026
When a potential customer asks an AI assistant which trading platform to use, IG is largely absent from the answer. Competitors with comparable or weaker profiles are filling that space.
Pepperstone
High
eToro
Good
AJ Bell
Good
IG
Low
◉ FINDING
AJ Bell: 551K visits · 24,367 keywords vs IG 375K · 21,056 keywords
47% more traffic on a near-identical footprint. The gap is coverage, not link profile.
Ahrefs · site-explorer-metrics · ajbell.co.uk & ig.com · GB · 12 Jun 2026
◉ FINDING
HL: 57,389 keywords · 4.26M visits vs IG: 21,056 keywords · 375K visits
Same regulated UK market, comparable brand presence. 11× the traffic. The gap is keyword footprint.
Ahrefs · site-explorer-metrics · hl.co.uk · GB · 12 Jun 2026
◉ FINDING
"Best spread betting platform UK" — IG largely absent
Third-party review sites fill the gap. Zero paid budget recovers that first impression.
Manual prompt test · ChatGPT-4o, Gemini 1.5, Perplexity · Jun 2026
02 / 09
Honest Baseline · Live Data
Where IG actually stands.
The data is honest. The gaps it reveals are structural, not fundamental. Every problem here has a fix.
Organic Competitors · UK · Ahrefs Jun 2026
IG sits alongside the strongest link profiles in this sector. AJ Bell outtraffics it on a near-identical keyword count. That is not an authority problem. It is a content coverage problem.
DomainTraffic/moKeywordsvs IG
ig.com375K21,056—
hl.co.uk4.26M57,389+11×
ajbell.co.uk551K24,367+47%
fidelity.co.uk373K21,054≈ par
etoro.com275K12,479–27%
cmcmarkets.com42K4,573–89%
Top Pages · ig.com · UK · Ahrefs Jun 2026
Pages with the highest keyword volume are delivering the least traffic relative to their position. IG is on page one for these terms but not earning the click.
PageTrafficKW VolPos
FTSE-100 futures82.6K30K1
Homepage (branded)27.3K20K1
Best dividend stocks18.8K126K3
Login (navigational)15.2K9.4K1
BTC/USD7.1K365K8
What is forex6.8K14K5
App Store · iOS UK · Manual Audit
The product earns a 4.6★ rating. The listing doesn't capitalise on it. The title targets no keyword and the description leaves the searchable index half-empty.
4.6 ★
33,000 ratings · iOS UK
eToro 4.4★ with a weaker product still outperforms IG on keyword indexing. It is a listing gap, not a product gap.
Tech Stack · from ig.com source
AEMGTMHotjarOptimizelyAdalyser
JD references a "headless CMS build". Decoupled AEM layer with schema injected at component level, not template.
◉ FINDING
AJ Bell: 24,367 keywords · 551K visits vs IG 21,056 keywords · 375K. A coverage gap, not an authority gap.
Ahrefs · site-explorer-metrics · ajbell.co.uk & etoro.com · GB · 12 Jun 2026 · eToro: 275K organic · 312K paid
◉ FINDING
BTC/USD: pos 8 · 365K vol · 7.1K visits. Dividend stocks: pos 3 · 126K vol · 18.8K visits
Ahrefs · site-explorer-top-pages · ig.com · GB · 12 Jun 2026
◉ FINDING
"IG: Trading. Investing. Crypto" has zero primary keyword target in the iOS title
App Store · manual audit · Jun 2026
03 / 09
Pillar 1 · Content
Make what you have work harder.
Before commissioning a single new page.
IG's content estate is substantial. The first question is not what to write next. It's what existing content isn't working, and why.
Page restructure
Across IG's top organic pages, a consistent pattern emerges: pages ranking in strong positions are delivering traffic below what those positions should yield. The opportunity is structural. Pages that lead with a direct answer, carry FAQ schema, and are extractable by AI systems consistently outperform those that don't. BTC/USD and dividend stocks are the clearest examples where targeted improvements would have immediate impact.
Rank + cited matrix
IG has strong rankings. The next layer is ensuring those pages are also getting cited in AI Overviews. Most competitors aren't measuring this dimension yet, which makes it an early-mover opportunity rather than a catch-up exercise.
  • Rank + cited → protect
  • Rank + not cited → restructure for extraction
  • Neither → consolidate
Internal linking audit
The FTSE-100 page drives 82K visits a month. Connecting that traffic to commercial flows through improved internal linking is low-effort, high-return work. No new content needed, no compliance sign-off required.
Performance angle: Better organic funnelling reduces paid demand for mid-funnel terms
Automate the SEO workflow
Keyword research, rank tracking, crawl monitoring, and competitor gap analysis should not consume senior SEO time. The right approach is an automated SEO intelligence layer that separates data work from editorial work. The team is then free for strategy, stakeholder management, and compliance navigation. That is where the leverage is.
DataForSEOAhrefs APIn8nPythonScreaming FrogAnthropic API
◉ FINDING
7 of the top 20 pages are underperforming their keyword volume by more than 50%
Dow Jones (pos 18, 688K vol), BTC/USD (pos 8, 365K vol), Barclays (pos 10, 253K vol)
Ahrefs · site-explorer-top-pages · ig.com · GB · Jun 2026
◉ OPPORTUNITY
Establishing a dual-surface audit gives IG a measurement advantage no competitor currently has
Phase 1 deliverable · Jun 2026
◉ OPPORTUNITY
FTSE-100 page: 82K visits/month. Improving internal links to commercial pages is the highest-leverage quick win
Ahrefs · site-explorer-top-pages · ig.com · GB · Jun 2026
◉ OPPORTUNITY
An automated intelligence layer frees senior SEO time for strategy rather than data collection
Workflow audit · Jun 2026
04 / 09
Pillar 2 · Technical SEO
IG's authors are credible.
Google doesn't know that yet.
Author profile pages exist. Adding Person schema formalises the E-E-A-T signal that Google needs to verify the credibility that's already there.
Author schema · E-E-A-T
IG publishes financial analysis from named analysts. Those authors carry real expertise and professional credibility. Without Person schema, Google cannot verify any of it. For YMYL financial content, unverified authorship is a direct E-E-A-T penalty.
The chain:
Article → author → Person → affiliation → Organization
Article → reviewer → Person → affiliation → Organization
Google increasingly favours a writer + reviewer model for YMYL content. IG's compliance review process already exists. The schema surfaces it. No compliance review needed. Markup only. Ships in days.
Structured data strategy
Schema markup is the bridge between ranking and citation. A full template audit across homepage, product, article, author, and account opening flows will establish scope before prioritising rollout. Three types move the needle fastest.
  • FAQPage schema on product and explainer pages
  • FinancialProduct schema on spread betting, ISA, SIPP
  • Article schema linking author and reviewer
  • Programmatic templates — schema injected at AEM component level, not page by page. Scales across every instrument, locale, and account type without manual intervention.
CWV + regulated markets
For a trading platform, page speed is directly tied to account opening conversion. CWV improvements in large organisations are rarely straightforward — ad tracking, campaign scripts, and legacy integrations all affect the scores. The right approach is a structured audit of what's running on high-conversion pages, prioritising the account opening flow where LCP and CLS impact is most commercially significant.
Restricted market precedent: Philip Morris (100+ domains, 60+ markets), Royal Canin, PetPlan, News UK. I've run compliance SEO at exactly this scale.
Performance angle: Faster pages → lower paid landing page bounce → higher Quality Scores → lower CPCs.
◉ QUICKEST WIN
ig.com/uk/people/* — author profiles exist, no Person schema
Manual crawl · ig.com · Jun 2026 · no compliance dependency · ships in days
◉ FINDING
ig.com/llms.txt exists but isn't referenced in robots.txt — AI crawlers won't discover it. No GPTBot, ClaudeBot, or PerplexityBot rules either.
Manual check · ig.com/llms.txt & ig.com/robots.txt · Jun 2026
◉ FINDING
30+ locale variants on ig.com. Hreflang at this scale is a known maintenance burden and worth an early audit.
Architecture review · ig.com locale structure · Jun 2026
05 / 09
Pillar 3 · AI Search Visibility
The new front page.
The opportunity is still open.
ChatGPT, Gemini, and Perplexity are now the first stop for high-intent financial queries. Three interventions, each addressing a different layer of how LLMs find and cite content.
Entity layer
LLMs build entity graphs from the open web. IG's authority is real. The structured signals that prove it to LLMs are missing. Without a verified entity graph, IG doesn't get the benefit of its own reputation in AI-generated answers.
  • Wikipedia / Wikidata: FCA registration, founding 1974, regulatory references
  • Structured mentions in authoritative financial media using the full legal name "IG Group" — FT, Bloomberg UK, Citywire — reinforce the entity signal LLMs draw from
  • Author entity markup chain connected to Person schema on each profile page
  • Structured mentions in authoritative financial media (FT, Bloomberg UK, Citywire)
Content layer
What LLMs find when they crawl ig.com. AEM-rendered HTML carries significant noise: nav, footer, cookie banners, and legal disclaimers. Clean extraction surfaces directly improve how much of IG's actual content gets cited.
  • ig.com/llms.txt exists — but isn't referenced in robots.txt so AI crawlers may never find it. The file covers UK and France only despite IG operating across 30+ markets. No analyst profiles, no UK education content, instrument coverage limited to 8 popular markets. Created once, not maintained. The file is there; the governance isn't.
  • .md page variants: clean markdown equivalents of the spread betting explainer, ISA guide, and CFD page, canonicalised back to HTML with zero duplication risk
Retrieval layer
How LLMs extract and quote content once they've found it. RAG pipelines cite definition paragraphs disproportionately. Content structure determines citation rate, not just domain authority.
  • Direct answer above the fold on all product and explainer pages
  • FAQPage schema as the primary trigger for AI Overview inclusion on financial queries
  • Speakable schema on key editorial and analysis content
Performance angle
AI citations are zero-cost impressions at maximum intent. The user is actively asking which platform to use. No paid budget can buy back that first answer.
◉ OPPORTUNITY
Wikipedia and Wikidata carry FCA registration, founding 1974, and regulatory references — the entity signals LLMs use to verify IG's authority in financial answers
Manual check · Wikidata · Jun 2026
◉ OPPORTUNITY
Creating and maintaining llms.txt gives IG direct control over what LLMs index from ig.com
Direct URL check · ig.com/llms.txt · Jun 2026
◉ OPPORTUNITY
Clean .md variants on key explainer pages improve AI extraction and increase citation rate in LLM responses
Manual URL check · ig.com/uk/spread-betting · Jun 2026
06 / 09
Pillar 4 · ASO
4.6★ and 33,000 ratings.
The listing hasn't caught up with the product.
Strong product. The store presence isn't translating that quality into keyword visibility or install conversion.
iOS title rewrite
The App Store title is the single highest-weight keyword field. The current title has headroom to target primary search terms. A focused rewrite is a zero-cost visibility gain.
One approach: "IG: Spread Betting & Investing" with a subtitle targeting ISA and CFD keywords directly.
Google Play description
Google Play's 4,000-character description is fully indexed and searchable. It is a free keyword field most apps leave half-empty. IG's current description doesn't use the available space strategically.
iOS keyword field (100 chars) also needs a full audit against real App Store search volume data.
Screenshot CVR
Screenshots 1–3 decide whether a user installs. IG's current screens lead with the trading UI. Competitors lead with the value proposition ("No commission", "16,000+ markets", "FCA regulated").
  • App Preview video autoplays in search results, the highest-impact creative element before a user taps through
  • A/B test screenshots via Apple Product Page Optimisation
  • Android: Google Play Store Listing Experiments
Performance angle: Better CVR = lower CPI across all paid UA.
Defend 4.6★
For a trading app, rating spikes correlate directly with platform downtime and volatile market events. A proactive rating strategy protects the score before it becomes a problem.
  • Trigger rating prompt post successful trade, not randomly
  • Developer response rate is an App Store ranking signal
  • Daily velocity monitoring with alerts on spikes
◉ OPPORTUNITY
A title rewrite targeting primary search terms is a zero-cost visibility gain with no product change required
App Store · manual audit · Jun 2026
◉ OPPORTUNITY
Google Play's fully-indexed 4,000-character description field has headroom to drive significant keyword coverage
Google Play Store · manual audit · Jun 2026
◉ OPPORTUNITY
Leading screenshots with the value proposition rather than the UI directly improves install conversion rate
App Store · manual audit · Jun 2026
◉ OPPORTUNITY
A proactive rating strategy protects a 4.6★ score built on 33,000 reviews before market volatility creates pressure
App Store · manual audit · Jun 2026
07 / 09
Measurement
Everything traces to account opens and first trade.
Every initiative is measured against its contribution to the commercial outcome, not traffic or rankings in isolation.
Surface
Impressions
GSC · AI prompt testing
→
Acquisition
Organic Clicks
GSC · Ahrefs · GA4
→
App
Installs & CVR
App Store Connect · Appsflyer
→
Conversion
Account Opens
CRM · Attribution model
→
Revenue
First Trade
Revenue attribution · CLTV
Dashboards · Always On
Automated monitoring, not a document anyone reads on a schedule. It alerts when something materially changes. Branded vs non-branded split isolates genuine acquisition from navigational traffic.
  • Organic traffic and keyword position monitoring
  • Technical health: crawl errors, CWV regressions, index coverage drops
  • App Store rating velocity with spike alerts on market event days
Weekly + Monthly · Operating Rhythm
Weekly: Organic rankings and App Store keyword positions connected to conversion — what moved, what it means, one clear recommendation. Presented to senior stakeholders, not just circulated.
  • Keyword position changes with conversion delta, not standalone rank movement
  • App Store CVR and install velocity vs prior week
  • One prioritised action for the coming sprint
Monthly: What shipped, what moved, what's blocked, what's next. AI citation rate against fixed query set. Pipeline progress vs plan.
Quarterly · Business Review
What gets presented upward. Commercial outcomes only. The SEO function's contribution to acquisition and how that trajectory is moving against paid.
  • Organic vs paid CAC ratio: the number that matters
  • Organic-attributed account opens (absolute + % of total acquisition)
  • AI citation share vs Pepperstone / AJ Bell / eToro
  • Quarterly targets: actual vs forecast
◉ OPPORTUNITY
Establishing an AI citation baseline in Phase 1 creates the measurement foundation the rest of the strategy reports against
Phase 1 deliverable · Jun 2026
◉ OPPORTUNITY
Weekly stakeholder reporting connects rankings to conversion — one clear recommendation per sprint, not just a summary
Proposed operating cadence · Jun 2026
◉ OPPORTUNITY
Organic vs paid CAC ratio is the single number that earns SEO budget at the quarterly business review
Proposed operating cadence · Jun 2026
08 / 09
The Approach
No assumptions. No Gantt charts.
Three phases, three postures.
The sequence matters. Understanding the organisation comes before acting on it. Early wins build the credibility to move the bigger pieces.
Phase 1
Establish
ground truth
The first priority is understanding, not shipping. Before making any commitments, the baseline needs to be established: what the data actually shows, how the organisation makes decisions, where the real constraints are, and which opportunities are genuinely quick wins versus which ones look quick but aren't.
  • Technical audit — schema gaps, AI crawler governance, hreflang, CWV on account opening flows
  • AI citation baseline — ChatGPT, Gemini, Perplexity, Google AI Overviews
  • ASO audit — keyword coverage gaps, App Store CVR vs eToro and HL
  • Compliance & sprint cadence — understand SLAs and approval workflow before planning anything
  • Poland SEO hub — map their remit and make the relationship a multiplier, not a bottleneck
  • Attribution model — how organic account opens are currently tracked and reported
Outcome
A clear, data-backed picture of where IG stands, free of inherited assumptions. A prioritised opportunity list stress-tested against organisational reality.
Phase 2
Early commercial
impact
Pick the interventions that move the needle without requiring large cross-functional coordination. Deliver them. Use the results to demonstrate commercial intent and build the organisational credibility needed for the bigger structural work that follows.
  • Author schema — all analyst profiles, no compliance dependency, measurable E-E-A-T signal
  • ASO title & keywords — no compliance required, ranking impact measurable within the phase
  • Top page restructure — FTSE-100, BTC/USD, dividend stocks, optimised for AI extraction and CTR
  • llms.txt — claim ownership, add robots.txt reference so crawlers find it, establish monthly update cadence
  • .md page variants — clean RAG extraction surface on key explainer pages, canonicalised
Outcome
Measurable early results on the board. Credibility established with the team and with stakeholders. The function is moving, and visibly so.
Phase 3
Define the
operating model
The deliverable at the end of Phase 3 isn't a completed task list. It's a function with a defined way of working: how priorities are set, how performance is reported upward, and how the SEO function integrates with paid, product, and compliance. That's what makes sustained progress possible.
  • First quarterly review — organic account opens, organic vs paid CAC trend, AI citation share vs competitors
  • Schema rollout plan — prioritised against compliance and dev capacity, not a theoretical wishlist
  • Internal linking plan — commercial intent pages connected to the high-traffic estate
  • Content & ASO governance — who owns what, approval path, cadence
  • Next phase priorities — data-led, based on what Phase 1 and 2 actually showed
Outcome
A function with a clear operating model, early commercial wins on record, and a credible roadmap stress-tested against IG's actual constraints, not built in the abstract.
09 / 09
Jinnat Ul Hasan
Jinnat Ul Hasan
SEO Lead & AI Search Strategist
MSc Computer Science, Distinction
PythonAEMn8nAnthropic APIGA4/GSCAhrefs
About
Fifteen years building organic at enterprise scale across regulated, restricted, and high-stakes environments. Philip Morris: 100+ domains, 60+ markets, multi-stack incl. AEM. News UK: The Sun on headless WordPress, The Times on Methode, under IPSO, at 40M+ sessions. Sky: live editorial under Ofcom constraints. DMA Silver Award via TMW Unlimited for Unilever. Royal Canin and PetPlan: vet-regulated health claims that map directly to the FCA financial promotions constraint IG operates under.

I've also built the AI tools I'm proposing to use here. I understand LLM infrastructure at implementation level, not just as a user.
Enterprise
FTD Digital
Philip Morris ZYN · IQOS
News UK The Sun · The Times · The US Sun · Times Money Mentor
MediaCom Sky · Royal Canin · Petplan · Nikon · Tempur · Brand USA
TMW Unlimited Diageo · Rolls-Royce · Unilever · Barilla · Pimm's · DrinkIQ
Awards
🥈 DMA Silver
Best Use of Search — Natural & Paid · thebar.com · Diageo · Dec 2016
Drum Search Awards
Commendation — Best Use of Content SEO · thebar.com · Diageo · Sep 2016
AI & Engineering: Shipped
ContentGenie: DataForSEO + Anthropic Batch API + n8n. ~£0.13/article. Compliance review is the fixed cost by design.
Aldwyn: Python trading agent, IBKR TWS API, Ollama (Gemma 4 26B). Running on real capital.
Whizz CRM: Next.js 14, Supabase, Vercel. Multi-tenant. Production.
FAQ Schema Auditor: sitemap crawl → local Ollama LLM → detects missing FAQPage JSON-LD, generates ready-to-paste schema blocks. Pure stdlib, no pip.
llms.txt deployment: AI crawler governance on live client sites. Maintained as a living document.
Investing: Active Platforms
IGHLFreetradeTrading 212RobinhoodLightyear
ISA · SIPP · equities
40 Countries · 8 Regions
10 / 10
Questions?
Jinnat Ul Hasan · jinnat.hasan@gmail.com