A sequence, not secret technology

Weeks 1 to 3

Map the market

What does the demand around this product actually look like?

We build the query universe for your category and markets, group it by journey stage, and identify who holds each cluster today: you, direct competitors, affiliates, comparison publishers or forums.

Worked example · Illustrative example: a broker entering a new region might see demand split into fee comparison queries held by affiliates, platform queries held by review publishers, and regulatory queries answered only by official sources. The worked output groups each cluster by journey stage and names the current holder, so the plan starts from who must be displaced rather than from search volume.

• ◆ Query universe segmented by journey stage and market
• ◆ Share-of-voice read on your commercial query set
• ◆ Competitor and affiliate holdings map

Weeks 2 to 4

Price the opportunity

What is each cluster worth, and what would it cost to buy instead?

Volume alone decides nothing. We rate clusters on commercial proximity, competitive difficulty and what you currently pay for the same demand through paid search and affiliate commission. That produces a ranked list, not a keyword dump.

Worked example · Illustrative example: two clusters with similar search volume can carry very different weight once priced. One might sit beside expensive paid search bids and high affiliate payouts, marking it as contested commercial ground. Another might show modest volume but a short path from reader to funded account, which moves it above larger but vaguer clusters in the ranked list.

• ◆ Clusters ranked by commercial value and winnability
• ◆ Paid and affiliate equivalent cost of the same demand
• ◆ The clusters we recommend leaving alone, and why

Weeks 3 onward, continuous

Fix the infrastructure

Can search engines reach, render and trust what you already have?

Rendering, indexation, internal linking, faceted navigation, country targeting, page experience and migration risk. Written as specifications your developers can put in a sprint, with us in the review.

Worked example · Illustrative example: a specification item might read that faceted market pages generate unbounded crawlable URLs, with the fix defined as canonical consolidation plus noindex rules for filtered views and an acceptance test the developer can run before marking the ticket done. Each item ships with that level of testability, so fixes stay fixed through later releases.

• ◆ Prioritised technical specification, sprint-ready
• ◆ Indexation and rendering fixes with acceptance criteria
• ◆ International targeting and hreflang correction

Month 2 onward

Build commercial coverage

Do you have a page worth ranking for every cluster that matters?

Comparison structures, fee and product transparency, country pages, educational clusters and reputation-facing coverage. Produced inside your compliance cycle, with the reviewer named before the brief is written.

Worked example · Illustrative example: a coverage plan for one cluster might specify a single comparison page with its claim schedule attached, three supporting explainers linked beneath it, and the reviewer named on each brief before drafting starts. The internal linking model then concentrates authority on the comparison page rather than scattering it across overlapping drafts.

• ◆ Page-by-page coverage plan mapped to clusters
• ◆ Briefs written for expert or compliance review
• ◆ Internal linking model that concentrates authority

Month 3 onward

Earn authority

Why would a search engine trust you on a money question?

Proprietary data, market commentary, expert attribution and editorial coverage in publications your category actually reads. Slower than buying links, and it survives updates.

Worked example · Illustrative example: a research asset might analyse the published rule pages across the category and document how daily loss calculations differ, which independent publishers then cite when explaining the mechanics to traders. The asset earns references because it holds neutral ground no single firm has an incentive to hold, and each citation is verifiable rather than placed.

• ◆ Data or research asset built for citation
• ◆ Expert attribution and author infrastructure
• ◆ Editorial and commentary programme

Baseline week 1, reported monthly

Measure funded outcomes

Did this produce funded accounts, or just sessions?

Reporting built on applications, verified accounts, deposits and funded status from non-branded organic. We agree the definitions and the data access in week one, because retro-fitting attribution never works.

Worked example · Illustrative example: a quarterly review might show non-branded organic applications rising while funded accounts stay flat, which reframes the problem from acquisition to application-to-funded conversion. The report states that plainly, with the failing step named and the next test proposed, rather than leading with the sessions figure that flatters the channel.

• ◆ Non-branded organic reporting separated from brand
• ◆ Outcome definitions agreed with your analytics owner
• ◆ Board-ready quarterly review, with what failed included