You just shipped a feature, and now you need a blog post that explains it to customers before the same questions land in your inbox. Most tutorials tell you to open a keyword tool first. For a small product, that advice rarely fits.
I build software for business growth, and I watch where people struggle. They chase search volume when they should research a blog topic for a software product by starting with what they already know. This guide shows you a site-first method that keeps every product claim accurate.
How do I research a blog topic for a small software product? Start from what your site already explains. Turn one customer question into one topic, gather dated outside context, log every claim in a ledger, and check that ledger before you draft a single paragraph.
Below, I cover what topic research involves, why keyword volume shouldn't be your first filter, the five steps, and the final check. Most drafts break at one specific point, and it isn't picking the topic. I'll show you where it is.
What does researching a blog topic for a software product involve?
Researching a blog topic for a software product is the process of collecting verifiable facts about one customer question. You draw first from your own pages and second from dated outside sources, so you can trace and check every product claim in the post.
The output is a verified outline, not a keyword list. Your own site is the source of truth for product claims.
Three terms to know
- Research step: one discrete task, such as reading a feature page or noting a customer question, that produces a fact you can use.
- Primary source: the original place a fact comes from. For product claims, that is your own page or doc, not someone else's summary of it.
- Claim ledger: a simple log listing each claim, its source, and the date you checked it.
Think of the claim ledger like a receipt drawer at tax time. If you can't produce the receipt, you don't file the expense.
What you need before you start
- Your feature pages
- Your product docs
- Your FAQ page
- Real customer questions from email, chat, or calls
- A claim log, such as a spreadsheet or a doc
With these in hand, the end result is clear. You get an outline in which every product claim traces back to your own site. That same research-first approach is what BloGoose applies when it produces researched articles.
Why keyword volume shouldn't be your first filter
Keyword volume is a poor first filter for a small product because the questions your customers ask are specific. Those questions often show little or no search volume. Filter by volume first, and you discard the exact topics your buyers care about.
Most tutorial videos on this subject are walkthroughs of keyword tools. They assume a tool is required and build the whole workflow around its metrics. That approach has real strengths: it maps demand across broad markets and shows you what competitors rank for.
| Factor | Tool-first | Site-first |
|---|---|---|
| Starting point | Search volume and difficulty scores | Your feature pages, docs, FAQs, and customer questions |
| Product accuracy | Not built in; depends on the writer | Every claim traces to your own site |
| Fit for niche products | Weak, because specific queries often show little volume | Strong, because topics come from real customer questions |
| Verification step | Usually absent from the workflow | A claim ledger checked before drafting |
| Best for | Broad publishers covering large markets | Small software products and founder-led teams |
Do I need Semrush to research a blog topic? No, not for a small software product. You can research a topic without keyword tools by working from evidence you already own. Read your feature pages, docs, and FAQ page, then list the questions customers actually send you. Pick one question and treat it as the topic. Gather dated outside context to frame it, and log every claim with its source. A paid tool adds value later, when you want to compare demand across topics. It cannot tell you whether your post describes your product correctly.
Here is how the site-first method works in practice.
How to research a blog topic for a software product in 5 steps
Research a blog topic by starting with what your site already explains. Then narrow it to one customer question, add dated outside sources, log every claim, and approve an outline before anyone drafts.
This is the Site-First Research Loop, and it takes about 60 to 90 minutes per article. Before you start, open your product pages, your changelog or release notes, a spreadsheet (Google Sheets or Excel works), and a browser.
- Open your own site first (15 minutes). Read the product page, feature docs, and pricing page for the feature you want to cover. Paste every factual sentence into column A of your spreadsheet. You should end with a short list of what your product actually does, in your own words.
- Turn one customer question into one topic (10 minutes). Pick a single question from support emails, demo calls, or sales chats, and write it as the working title. One reader task maps to one article, so save any second question for its own post. You should have one question and one sentence that describes the reader's task.
- Gather outside context from dated primary sources (30 minutes). Search for official documentation, standards, and original research, and note each publication date. Then open the top-ranking articles for your question and list what they already cover, so you can see the gap.
- Pro tip: keep each source's own year in the cell beside the claim, and never update it to the current year. A 2023 figure stays a 2023 figure.
- If you want help: BloGoose's research step reads your site and gathers context on the topic. It then pauses so you can review the sources and facts before drafting continues. You still decide on the facts, the words, and what gets published.
- Log every claim as you go (ongoing). Add one row per fact: the claim, its source URL, and the source's year. You should see no claim in your notes without a matching row.
- Approve the outline before drafting (15 minutes). Write H2s that answer the customer question, and attach the logged claims under each heading. You should end with an outline in which every heading points to at least one logged claim.
Worked example: one feature, one question, one article
Say you just shipped scheduled CSV exports. Step 1 pulls the feature description from your release note. Step 2 picks one question: "Can I send a weekly report to my accountant automatically?"
Steps 3 to 5 add dated context on export formats and produce an outline built around that single task. The feature becomes one focused article.
If you write a feature article like this every month, browse Verthilix's task-focused product pages. You can also look at the Growth Duo, which pairs researched articles and short videos in one subscription.
How to check every source and fact before drafting continues
Check sources by sorting every claim into a Claim Ledger with four tiers: your site, primary source, secondary blog, or unsupported. Keep site claims, cite primary sources, replace secondary blogs with primary sources, and cut anything unsupported.
You need: the claim spreadsheet from step 4 and your approved outline. The check takes about 20 to 30 minutes.
- Add two columns, Tier and Action (2 minutes). You should see them beside each claim row.
- Open every source URL and assign a tier (15 minutes). You should see exactly one tier per row.
- Apply the matching action (10 minutes). The research has worked when every claim in the outline carries a tier and an action.
| Tier | Example | Action |
|---|---|---|
| Your site | Product page, docs, release notes | Keep |
| Primary source | Official docs, original research | Cite with its own year |
| Secondary blog | Another site summarizing a study | Replace with the primary source |
| Unsupported | No traceable origin | Cut |
Verify these four things: claims, numbers, dates, and product specifics.
How do you verify sources gathered by AI?
Verify AI-gathered sources the same way you verify your own research. Open each link yourself and confirm the page exists. Then check that the page actually states the claim attributed to it, and record the publication year it shows. Trace every statistic back to the organization that produced it, not to a blog that repeated it. Compare each product claim against your own pages, because a research tool can misread a feature. Then give the claim a ledger tier. A source counts as verified only when you have read it, dated it, and matched it to a specific sentence in your outline.
Troubleshooting
- The source has no date: look for a primary source that is dated. If none exists, cut the claim.
- The link is dead: search for the original publisher's page. If you can't find it, mark the claim unsupported.
- A statistic has no origin: cut it.
- A product claim conflicts with your site: your site wins. Use your own wording.
Reuse your verified research beyond the article
Your Claim Ledger is more than article prep. It is a fact base you can reuse in every format, so your blog post, video, and sales page all say the same thing.
Take the scheduled CSV export example. Use the same ledger rows to script a 30-second clip, following this guide to make a short product video for one new feature. That gives you one feature, one researched article, and one short clip, all built from one ledger. No video can contradict the post, because both use the same verified claims.
Your next step is to see the Growth Duo, which combines researched articles and short videos in one subscription. For more site-first workflows, read the Verthilix Journal. Research each feature once, verify it once, and let it carry your message wherever customers find you.