Buying-Journey Map
Every search term your buyers run, sorted into where they are in the purchase decision: just discovering you exist, comparing you to alternatives, or ready to buy right now.
04. Content
Keyword Research.
Map the demand before you build.
Most keyword tools sell you traffic that never adds to cart. We separate the searches that look impressive from the ones that actually move revenue, then we map every winner to a stage of your buying journey.
In plain words
Ecommerce keyword research is demand mapping: finding the full universe of search terms your buyers type before they purchase, classifying them by search intent, and sizing each one by search volume, keyword difficulty, and revenue potential. A free keyword tool hands you a list and a volume column, which is data, not a strategy. We use AI to cluster at catalogue scale, then a senior operator prunes for buying intent, so the roadmap targets the searches that move carts, not the vanity volume that fills a report.
Volume vs. Value Split
The low-volume searches that convert at 8% (worth chasing) and the high-volume searches that convert at 0.2% (volume theatre, not worth chasing). Most agencies sell you the second list.
Competitor Gap Set
Every search your competitors are ranking for that you're not, scored by your odds of catching them and the revenue at stake if you do.
Page Cluster Definitions
Which searches belong on the same page (so they reinforce each other) vs. on separate pages (so they don't compete). The single biggest unforced error in DTC SEO is getting this wrong.
Forecast Model
Conservative and aggressive revenue forecasts per cluster, so you can see, in dollars, what each piece of work is worth before we ship it.
Tracking Spec
Exactly which searches to monitor each month, drop into your existing rank-tracker. So you know whether the work is paying off without waiting for the quarterly report.
How it ships
- 01Week 1
Seed and competitor expansion
Your catalogue, Search Console queries, and competitor ranking pages expanded into the full universe of searches your buyers run before purchasing.
- 02Week 1 to 2
Intent clustering at catalogue scale
AI clusters tens of thousands of keywords by meaning and SERP overlap; a senior operator prunes for buying intent and assigns each cluster a page type.
- 03Week 2
Revenue modelling
Each cluster weighted by search volume, keyword difficulty, expected click-through, and your conversion economics, producing a forecast in dollars, not positions.
- 04Week 3
Roadmap handoff and tracking
The demand map becomes the content and architecture roadmap, with rank tracking configured on every target cluster from day one.
Go deeper
Anyone can export search volumes from a keyword tool. The value is in what happens next, turning a keyword list into a revenue-ranked roadmap.
Search intent classification
Every query is informational, navigational, commercial, or transactional, and the page type that can rank for it follows from that. We classify search intent before anything else, because targeting a transactional keyword with a blog post wastes the effort no matter how good the writing is. Getting the right keywords onto the right page types is most of the battle.
Seed keywords and the long tail
We start from seed keywords pulled from your catalogue, your Google Search Console queries, and your competitors' ranking pages, then expand them into the full set of related keywords, keyword suggestions, and the long-tail keywords that actually convert. The long tail is where ecommerce wins: lower search volume per term, far higher buying intent, and a fraction of the competition.
Search volume versus keyword difficulty
Monthly search volume is the number everyone chases and the one that misleads most. We weigh it against keyword difficulty and your store's real authority, so the roadmap targets keywords you can actually rank for, not high-volume terms that stay on page three forever. Raising the domain authority that puts harder keywords in reach is what ecommerce link building is for.
Clustering into keyword groups
AI clusters tens of thousands of queries into keyword groups by meaning and SERP overlap in hours, the work agencies used to bill weeks for. The output is a demand map: every cluster your buyers search, sized by volume, difficulty, expected click-through, and your conversion economics, so each one carries a revenue forecast instead of just a search count. Turning that demand map into pages that rank is the work of an ecommerce content strategy.
SERP evidence and keyword gap analysis
The live search engine results page is ground truth: who ranks, which page types Google rewards, and which results carry rich snippets or AI Overviews. We run a keyword gap analysis against your top competitors to find the searches they rank for and you don't, scored by your odds of catching them and the revenue at stake if you do.
The tools, and where AI changes the job
Google Keyword Planner, Search Console, and Google Trends are free and show real search volume and the queries you already rank for; paid tools like Ahrefs and Semrush add keyword difficulty and larger databases. We use all of them as inputs, but none of them classify intent or size a cluster against your margins for you. AI adds the newest layer: buyers now phrase questions to ChatGPT and Perplexity in fuller sentences, so we map those queries too, and the same research earns both rankings and citations.
FAQ
You'd get the same raw numbers we start with; a tool doesn't gatekeep search volume. The difference is everything that turns those numbers into decisions: which intent each keyword serves, which cluster it belongs in, what it's worth against your margins, and which two-thirds of the list to ignore. That's a week of an operator's judgment, not a software subscription.
The tool matters less than how you use it. Google Keyword Planner and Search Console are free and show real search volume and the queries you already rank for; Google Trends adds seasonality; paid tools like Ahrefs and Semrush add keyword difficulty, competitor gap analysis, and larger keyword databases. We use all of them as inputs, then layer AI clustering and human judgment on top, because no tool will classify intent or size a cluster against your margins for you.
Search volume is how many people search a term each month; keyword difficulty estimates how hard it is to rank for it. Chasing high search volume alone is the most common ecommerce mistake, those terms are usually the hardest to rank for and the least likely to convert. The sweet spot is long-tail keywords: lower volume, higher buying intent, far less competition. We score every keyword on both axes plus revenue potential before it earns a place on the roadmap.
Yes. Buyers phrase questions differently to ChatGPT and Perplexity than to Google, in longer, fuller sentences. We map both surfaces so the same content investment earns rankings and citations.
A full rebuild yearly; cluster-level refreshes quarterly. Search demand shifts with seasons, trends, and new competitors, and Search Console keeps revealing queries you didn't know you ranked for. The map has to keep up with the territory.
A demand map: every cluster your buyers search, classified by intent, sized by volume and difficulty, modelled in revenue, and assigned to the page that should own it. It doubles as your content roadmap and your rank-tracking spec.
Where this fits
RUNS INSIDE
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