Keyword Research Example: A Full Worked Walkthrough (With Template)

A keyword research example is a step-by-step demonstration of how one business goes from a blank page to a ranked, prioritised keyword list. Below, we research a single niche end to end: seed keywords, expansion, intent, volume, difficulty, clustering, page mapping, and priority. Copy the table at the end as your own template.

Key takeaways

• A keyword research example is most useful when it is concrete, so we follow one sample business (a cold-brew coffee subscription in Singapore) from seed terms to a finished, prioritised plan.
• The workflow has six repeatable steps: pick seeds, expand, judge intent, score volume and difficulty, cluster, then map to pages and prioritise.
• Intent beats raw volume. A low-volume term that matches buyer intent often earns more revenue than a high-volume informational one.
• One page should target one cluster, not one keyword, so you cover a topic the way Google and AI engines now reward.
• The output is a single table you can rebuild for any niche in an afternoon.

The process: six steps before we touch the example

Keyword research is not a single search. It is a short pipeline you run every time. Here is the full sequence we will follow in the worked example below.

1. Choose seed keywords that describe what you sell in plain language.
2. Expand each seed using tools and the SERP itself to find real phrases people type.
3. Tag intent for every term: informational, commercial, transactional, or navigational.
4. Score volume and difficulty so you know the size of the prize and the cost of entry.
5. Cluster related terms that share the same intent into groups.
6. Map clusters to pages and prioritise based on intent, difficulty, and business value.

This matters because most content never gets seen. Ahrefs found that roughly 96% of pages get zero organic search traffic from Google, across a sample of around one billion pages. Skipping research is the fastest way to join that 96%.

Our sample business: a cold-brew coffee subscription

For this keyword research example we will use BrewHaus, a fictional Singapore brand selling cold-brew coffee on a monthly subscription. It sells single-origin beans, ready-to-drink bottles, and gift boxes. The numbers in this example are illustrative figures used to teach the method, not real measured data.

Why this niche? It has a clear product, obvious buyer intent, and a mix of local and informational searches. That spread lets us show every intent type in one walkthrough.

Step 1: Choose seed keywords

Seeds are the root terms a customer would use to describe the product. Write them before you open any tool. For BrewHaus, the seeds are:

• cold brew coffee
• cold brew subscription
• cold brew delivery Singapore
• coffee subscription Singapore
• how to make cold brew

Notice the spread. Some seeds are clearly commercial ("subscription," "delivery"), and one is informational ("how to make"). Good seed lists include both buying terms and the questions buyers ask before they buy.

Step 2: Expand each seed

Now we widen each seed into dozens of real phrases. Three sources do most of the work:

• Google autocomplete and "People also ask" show live phrasing straight from the SERP.
• A keyword tool (Google Keyword Planner, Ahrefs, or similar) returns volume and related terms. Google's own Keyword Planner help docs explain how to read its ranges.
• The "related searches" block at the bottom of the results page surfaces adjacent topics.

Expanding "cold brew subscription" alone gives us phrases like best cold brew subscription, cold brew coffee delivery, monthly coffee subscription Singapore, and cold brew gift box. We repeat this for every seed and collect everything in one sheet. This is also where the difference between short-tail and long-tail keywords starts to show: short seeds are broad and hard, while the longer phrases are specific and far easier to win.

Where the real phrases come from. Tools matter, but the richest expansion sources are free and show you exactly how people search. Here is where we mine for BrewHaus:

Two of these deserve emphasis. Google Search Console is the most underused source: it shows the queries your site already appears for on pages two and three, which are often the fastest wins. And competitor gap analysis reveals demand you would never have guessed. Ahrefs' own guidance notes that a single top-ranking page typically also ranks for around a thousand related keywords, so studying one strong competitor URL can hand you dozens of phrases in minutes.

After expansion we have roughly 60 raw phrases. The next three steps turn that pile into a plan.

Step 3: Tag the intent of every term

Intent is the single most important column. It tells you what the searcher wants and therefore what page should answer them. We use four tags:

• Informational: learning something (how to make cold brew).
• Commercial: comparing options before buying (best cold brew subscription).
• Transactional: ready to buy now (cold brew delivery Singapore).
• Navigational: looking for a specific brand.

This step matters because organic search is where buyers start. BrightEdge reports that organic search drives roughly 53% of all website traffic, so matching intent here decides whether that traffic converts or bounces.

Step 4: Score volume and difficulty

For each term we add two numbers: a rough monthly search volume band and a difficulty estimate. You do not need exact figures. Bands are enough to make decisions, and our guide on how to find keyword search volume walks through the tools. We use three bands:

• High: 1,000+ searches a month
• Medium: 200 to 1,000
• Low: under 200

For difficulty we use Low, Medium, or High based on how strong the ranking pages already are. The sweet spot for a young site is medium-to-high volume paired with low-to-medium difficulty. Chasing a High difficulty head term on a new domain usually wastes months, since the top organic result alone earns around 27 to 28% of clicks according to Backlinko and Advanced Web Ranking. If you cannot realistically reach the top few spots, the volume on paper never reaches your site.

Read the metrics correctly. Volume and difficulty are the headline numbers, but four metrics together tell the real story. Here is what each one means and the trap to avoid with it.

Ahrefs popularised traffic potential for a reason: because a single page ranks for roughly a thousand related terms on average, the headline volume of your target keyword understates what the page can actually earn. Score business value alongside it so you never ship a popular page that no customer cares about.

Step 5: Cluster related terms

A cluster is a group of keywords that share one intent and can be answered by one page. Search engines now reward topical depth, so we stop targeting single keywords and start targeting topics.

For BrewHaus, the 60 phrases collapse into five clusters:

• Cluster A: Buy / subscribe (transactional): cold brew subscription, cold brew delivery Singapore, monthly coffee subscription Singapore.
• Cluster B: Compare subscriptions (commercial): best cold brew subscription, cold brew vs iced coffee delivery.
• Cluster C: How to make cold brew (informational): how to make cold brew, cold brew ratio, cold brew steep time.
• Cluster D: Gifting (commercial/transactional): cold brew gift box, coffee gift subscription Singapore.
• Cluster E: Cold brew basics (informational): what is cold brew, cold brew vs iced coffee, is cold brew stronger.

Each cluster becomes one focused page, not five thin ones.

Step 6: Map clusters to pages and prioritise

Here is the payoff: the finished keyword research example table. Each row is a primary keyword, tagged, scored, clustered, and assigned to a real page. Volume and difficulty here are illustrative example values to show the method.

Now prioritise. Rank rows by business value first, then by the gap between volume and difficulty:

1. Quick wins first: low-difficulty transactional terms like cold brew delivery Singapore and cold brew gift box. They convert and rank fast.
2. High-value commercial next: best cold brew subscription earns trust and links.
3. Informational last but not least: how to make cold brew and cold brew vs iced coffee pull in top-of-funnel readers you can retarget.

This order means BrewHaus ships the pages most likely to drive revenue before the slow-burn educational content.

How to act on your finished list

A keyword table is only useful once it becomes pages. Three moves turn the plan into rankings.

• Write one page per cluster, with the primary keyword in the title, the H1, and the first 100 words.
• Cover the whole cluster on the page, including the related sub-terms, so the page reads as the complete answer.
• Interlink the pages, pointing your informational posts toward the transactional product page so authority flows to the money page.

This is the same approach behind our SEO content optimization service, where research and on-page work are one connected process. When BrewHaus-style research is paired with disciplined publishing, the compounding is real: one Rankite client, Swordfish AI, grew revenue by 400% from organic search by mapping clusters to pages and shipping them in priority order. For more on turning a list into rankings, see our guide on how to rank on Google.

Which tools fit each step

You can run this entire example with free tools, then add a paid one when you need volume and difficulty at scale. Pricing changes often, so treat the labels below as tiers rather than exact figures.

For BrewHaus we would do the seeds, expansion, and intent tagging with the free Google tools, then use one paid tool only to confirm volume bands and difficulty before clustering.

Myths that quietly ruin keyword research

A few widely repeated ideas waste effort or actively hurt rankings. Correct these before you start.

• Myth: "LSI keywords" boost rankings. There is no such thing. Google's John Mueller has stated plainly that "there's no such thing as LSI keywords." Cover the topic thoroughly and the related terms appear naturally; you do not need to sprinkle synonyms.
• Myth: hit an exact keyword density. There is no magic percentage. Writing for one cluster, in natural language, beats any density target. Keyword stuffing reads badly and can trigger Google's spam policies.
• Myth: one page should target exactly one keyword. Because the average top-ranking page also ranks for around a thousand related keywords (per Ahrefs), targeting a whole cluster on one strong page is how modern ranking actually works.
• Myth: zero-volume keywords are worthless. Many tools under-report new or niche demand. A "zero-volume" buyer term that converts can be worth more than a high-volume term that never does.

Common mistakes in keyword research

Even a clean process fails if you trip on these.

• Chasing volume over intent. A 5,000-search head term you cannot rank for is worth less than a 150-search buyer term you can win this month.
• Targeting one keyword per page. This creates thin, overlapping pages that compete with each other. Cluster instead.
• Ignoring difficulty. New sites that attack High difficulty terms see nothing for months.
• Skipping the SERP check. Always look at what currently ranks. If the page-one results are all guides and you built a product page, your intent is wrong.
• Causing keyword cannibalization. When two pages chase near-identical terms, they split signals and compete with each other. Clustering prevents this: one cluster, one page.
• Ignoring SERP features. Check whether the results show a featured snippet, "People also ask," or a map pack. Those features change how much organic click-through is even available to win.
• Forgetting AI surfaces. Google's AI Overviews now reach more than 1.5 billion users a month across 100+ countries, so structuring content as a clear, complete answer helps you appear there too. Google's own Search Central documentation explains what "helpful" looks like.

Frequently asked questions

What is a keyword research example? It is a worked demonstration that follows one business from seed keywords through expansion, intent tagging, scoring, clustering, and page mapping, ending in a prioritised table. The example above uses a cold-brew coffee subscription so every step is concrete rather than theoretical.

How many keywords should a keyword research example include? Start with five to ten seed terms, expand to 40 to 80 phrases, then collapse those into four to eight clusters. The cold-brew example moved from five seeds to about sixty phrases to five clusters and ten primary keywords.

Should I prioritise high-volume or low-difficulty keywords? For a younger site, prioritise low-to-medium difficulty terms that match buyer intent, even at lower volume. The top organic result earns roughly 27 to 28% of clicks per Backlinko and Advanced Web Ranking, so reachable rankings beat impressive volume you can never capture.

What tools do I need to follow this example? A keyword tool such as Google Keyword Planner or Ahrefs for volume and difficulty, plus Google autocomplete, "People also ask," and "related searches" for real phrasing. The SERP itself is your best free intent check.

How do I tell keyword intent? Read the phrase and the live results. Words like "buy," "delivery," and "subscription" signal transactional intent; "best" and "vs" signal commercial; "how," "what," and "why" signal informational. If the page-one results are mostly guides, the intent is informational even when the wording looks commercial.

Can I reuse this keyword research example for any niche? Yes. Swap the cold-brew seeds for your own products, then run the same six steps. The table columns (keyword, intent, volume band, difficulty, target page) work for any business, local or global.

What is the difference between keyword difficulty and traffic potential? Difficulty estimates how hard a keyword is to rank for, based on how strong the current top-10 pages are. Traffic potential estimates how much traffic you would actually get, because the page would also rank for many related terms. Ahrefs notes the average top page ranks for roughly a thousand keywords, so traffic potential often beats raw volume as a guide.

Do I need a paid tool to do keyword research? No. You can complete every step of this example with free tools: Google autocomplete, "People also ask," "related searches," and Google Search Console for terms you already rank for. A paid tool such as Ahrefs or Semrush mainly speeds up volume, difficulty, and competitor-gap work at scale.

Are LSI keywords real, and should I add them? No. Google's John Mueller has stated there is "no such thing as LSI keywords." Instead of sprinkling synonyms, cover the whole cluster in natural language. Related terms then appear on their own, which is exactly what search engines and AI answer engines reward.

What to do next

Pick five seed keywords for your own business and run the six steps above today. Build the table, tag intent, cluster, and rank your rows by business value. Then write your first quick-win page. If you want a second set of eyes on your keywords, pages, and rankings, request a free local SEO audit and we will show you exactly which clusters to ship first.