What You'll Learn in This Article
8 key topics covered to help you take action.
Quick Answer
What Counts as a Conversational Keyword
Step 1: Harvest People Also Ask Trees
Step 2: Mine Reddit, Quora and SG-Specific Forums
Step 3: The Search Console Question Filter (Easiest Wins You Already Own)
Step 4: Use AI Engines as Discovery Tools
Step 5: Cluster Into One-Question-One-Answer Pages
The Volume Problem and How to Get Around It
Best Marketing Singapore
First published: 30 June 2026 · Last updated: 30 June 2026
Harvest People Also Ask trees
Every PAA question is a pre-validated query Google has already classified as conversational intent. Expand each PAA, then expand the PAA those reveal. Two levels deep usually surfaces 30 to 80 questions per seed.
Mine Reddit, Quora and SG forums
The exact phrasing people use when they ask humans is the same phrasing they use when they ask AI. HardwareZone, Seedly and r/singapore are gold mines for SG conversational intent.
Search Console question filter
Filter your existing GSC queries by question modifiers (how, what, why, can, should, when, where, which, is, does). The questions you already get impressions for are the easiest wins.
Use AI engines as discovery tools
Ask ChatGPT and Perplexity "what are the top 30 questions a [audience] in Singapore asks about [topic]?" Then test the resulting questions back through the same engines. The answers you do not appear in are your gap list.
Cluster into one-question-one-answer pages
Group near-identical phrasings into a single intent. Each cluster gets one URL with a clean H2 question and a 40 to 60 word answer at the top. This is what AI engines lift.
What Counts as a Conversational Keyword
Three properties make a query conversational rather than classical: **1. It is a full sentence or natural phrase.** "best seo agency singapore for ecommerce" is classic. "what is the best SEO agency in Singapore for a Shopify store doing 50k a month" is conversational. The classic version has bid prices and high competition. The conversational version often has zero recorded volume in Ahrefs and yet attracts the exact same buyer. **2. It contains an explicit question signal or natural-language modifier.** Question words (how, what, why, when, where, which, can, should, is, does), comparison phrases (vs, versus, compared to, better than), and qualifier phrases (in 2026, for SG, that actually works, without spending money). These signals tell AI engines this query needs an answer, not a list of links. **3. It expresses an intent that an AI engine can satisfy in a paragraph.** AI engines do not lift "shopify" or "performance max." They lift "what is shopify good for", "should i use performance max for a 5k monthly budget", "is shopify better than woocommerce for a SG f&b brand". These are the queries you want to own. If a keyword fails any of these three tests, it belongs in your classical SEO research, not your AEO research. Most teams trying to do AEO are still using classical tools and wondering why nothing is showing up in the AI engines. The keywords you are targeting are not the keywords AI engines actually answer.Step 1: Harvest People Also Ask Trees
The single highest-value source for conversational keywords is Google's own People Also Ask box. Every question that appears there has been pre-validated by Google as a real conversational query with enough demand to surface in the SERP. We covered the optimisation side of this in People Also Ask optimization; here we use it as a research tool. The mechanic: Google Singapore your seed term, scroll to the PAA box, and click each question. Every click reveals more PAA questions. Click two levels deep and you typically surface 30 to 80 questions per seed term. Capture them all in a spreadsheet column. Free tools that automate this: AlsoAsked, AnswerThePublic, Keyword Insights' question expansion. They reduce a 30 minute manual process to 30 seconds. For SG-specific results, set the search location explicitly. PAA varies by country and SG-specific PAA trees are different from US ones for the same seed term. A real example we ran for a SG fintech client. Seed term: "personal loan." Classic Ahrefs reports the obvious: "personal loan singapore", "best personal loan". PAA harvest at two levels deep surfaced 73 distinct questions including "is taking a personal loan to invest a bad idea", "can i get a personal loan with a bad credit score in singapore", "how long does it take dbs to approve a personal loan", "what is the difference between a personal loan and a credit line in singapore". Every one of these is rankable in AI engines. Almost none of them appear in the classic Ahrefs report.Step 2: Mine Reddit, Quora and SG-Specific Forums
The second highest source of conversational keywords is the platforms where humans ask other humans. The exact phrasing used in a Reddit thread is overwhelmingly similar to the phrasing the same user would use when asking ChatGPT or Perplexity the same question. Forum data is also in the training set of every major AI model, which is why ChatGPT often produces answers that sound suspiciously like the top Reddit comments. For SG conversational keyword research, the platforms that matter:- r/singapore and r/SingaporeRaw: general SG questions, often surprisingly buyer-intent for consumer categories
- r/singaporefi: finance, investments, insurance, housing
- HardwareZone EDMW: broad consumer SG questions, very SG-specific phrasing
- Seedly community: finance, lifestyle, services
- Quora SG topic: smaller pool but useful for service-category questions
| Tool | Best for | Cost | SG availability |
|---|---|---|---|
| AlsoAsked | PAA tree harvesting | Free tier; paid from USD 15/mo | Yes, set country to SG |
| AnswerThePublic | Question and preposition wheels | Free tier; paid from USD 9/mo | Yes |
| Keyword Insights | Question clustering at scale | USD 58/mo entry | Yes |
| Reddit native search | Live conversational phrasing | Free | Yes |
| HardwareZone search | SG-specific phrasing | Free | Yes (local) |
| Google Search Console | Question queries you already rank for | Free | Yes |
| ChatGPT and Perplexity | Question discovery + gap testing | USD 20/mo each | Yes |
| Ahrefs / Semrush | Volume validation only (with caveats) | USD 99+/mo | Yes |
Step 3: The Search Console Question Filter (Easiest Wins You Already Own)
The questions you already get impressions for in Google Search Console are the cheapest wins in your entire AEO keyword research process. You already rank for them in some position; you just have not optimised for them. Surfacing this list takes ten minutes.
In GSC, go to Performance, then Queries. Filter Query > Custom (regex) > use this regex pattern:
`^(how|what|why|when|where|which|can|should|is|are|do|does|will)`
This surfaces every query you receive impressions for that begins with a question word. For most established SG sites this returns several hundred queries. Sort by impressions descending. The queries with high impressions but low CTR or low average position are your priority list, because conversational intent suggests AEO content can lift both.
Bonus filter: also pull queries containing comparison signals (vs, versus, compared, better than, difference between). These are conversational by intent even if they do not start with a question word.
What you do with the list: each high-impression question that you do not have a dedicated answer for becomes a candidate for either a new H2 on an existing page (faster) or a new dedicated FAQ-style article (deeper). The decision is based on whether the question is a sub-topic of an existing piece or a topic in its own right.
Step 4: Use AI Engines as Discovery Tools
This is the step most SG SEO professionals are not yet running and the one that produces the most contrarian wins. AI engines themselves are excellent at generating conversational keyword lists because they are trained on the exact corpus of natural-language queries you are trying to surface.
Two prompts that work consistently well in ChatGPT and Perplexity:
Prompt 1 (discovery): "List the 30 most common questions a [specific audience] in Singapore asks about [topic]. Order by frequency. Use the natural phrasing the audience uses, not corporate phrasing."
Prompt 2 (gap): Take 10 to 20 of those questions and run each one as a query in ChatGPT and Perplexity. Note which ones return your brand or your URL in the answer. Note which ones do not. The "do not" list is your gap list. These are queries where buyer-intent searches happen and your brand has no chance of being cited.
Worked example, same fintech client. Prompt 1 surfaced 30 questions. Running each through Perplexity, the brand was cited in 4 of 30 answers. The 26 questions where the brand was missing became the prioritised content brief: each got either a new dedicated answer or an addition to an existing page. Within 90 days, branded citations on Perplexity rose from 4 to 18 of the 30 queries.
For a deeper take on which AI engines matter most for SG audiences, see our piece on voice search optimization Singapore which covers the same conversational query phenomenon from the voice angle. Same queries, different input modality.
Step 5: Cluster Into One-Question-One-Answer Pages
Raw question lists are not yet a content plan. The conversion from list to plan is clustering: grouping near-identical phrasings into a single intent that gets a single page or single H2.
The clustering rule: two questions belong to the same cluster if a single high-quality answer satisfies both. "How does PDPA apply to email marketing in Singapore" and "is PDPA consent required for marketing emails" are the same cluster. "What is PDPA in Singapore" is a different cluster (definition, not application).
Free clustering tools: Keyword Insights' clustering feature, Cluster.ai, or just a spreadsheet plus ChatGPT (paste the list, ask it to group by semantic intent). For lists under 200 questions, the manual or LLM-assisted approach is fine. For larger lists, dedicated clustering tools save hours.
Output structure per cluster:
- One canonical question as the H2 (use the most natural phrasing from your research)
- One 40 to 60 word answer immediately below the H2 (this is what AI engines lift)
- Supporting paragraphs that expand the answer with context, examples and nuance
- Internal link to one related deeper article in the same topical cluster
This is the structure AI engines reward. Skipping the 40 to 60 word answer immediately under the question is the single most common AEO content mistake we see in SG marketing teams.
The Volume Problem and How to Get Around It
A real frustration with conversational keyword research: Ahrefs and Semrush consistently report zero search volume for the exact long-tail conversational queries that drive AI engine traffic. This is not the tool being wrong. It is that classic keyword tools sample volume from Google search logs, which historically underweighted long-tail queries to begin with, and ChatGPT, Perplexity and Claude queries do not appear in Google logs at all.
Three ways around this:
1. Group conversational keywords into thematic clusters and check the cluster volume, not the individual query volume. A cluster of 15 zero-volume conversational queries on "PDPA email marketing rules" might collectively drive 500+ monthly impressions in GSC once you publish.
2. Use GSC impression data as your real-volume proxy. Once you publish, GSC will report actual impression volume for queries Ahrefs claims are zero-volume. This is the only ground truth.
3. Discount Ahrefs zero-volume readings for any query containing question words or natural-language phrasing. They are systematically underreported. A question keyword reading "0 volume" in Ahrefs typically has 20 to 200 actual monthly searches.
For broader keyword strategy that combines volume validation with AEO research, our AI keyword research Singapore guide covers the full process end to end.
Common Mistakes SG Marketing Teams Make
Mistake 1: Skipping PAA harvesting because the volumes look small. PAA is not a volume signal, it is an intent signal. Volume is reported elsewhere. Treat PAA as your master question list.
Mistake 2: Not setting search location to Singapore. PAA, AlsoAsked and AnswerThePublic all default to US. SG conversational queries are different from US ones. Set the location every time.
Mistake 3: Ignoring forum sources. Reddit and HardwareZone produce the most natural SG-specific phrasing. Ahrefs cannot. Forums must be in the research workflow.
Mistake 4: Treating zero-volume readings as zero demand. Most conversational queries are systematically underreported. GSC post-publish data is your ground truth, not Ahrefs pre-publish guesses.
Mistake 5: Writing one giant article that tries to answer 30 questions. Worse SEO and worse AEO. Cluster properly: one question one answer one URL, with linked siblings.
Mistake 6: Not having a 40 to 60 word answer paragraph directly under each H2 question. This is the structure AI engines lift. Without it, you can have the right keyword and the right answer and still not get cited.
Mistake 7: Skipping the AI engine discovery prompt. The most contrarian queries come out of asking ChatGPT and Perplexity directly what people ask them. Free, fast, and most teams are not doing it.
Frequently Asked Questions
What is a conversational keyword in AEO?
A conversational keyword is a natural-language query, usually a full sentence or question, that people type into AI engines like ChatGPT, Perplexity and Google's AI Overviews. It differs from a classical SEO keyword in three ways: it is sentence-shaped rather than two or three words, it usually contains a question word or natural-language modifier, and it expresses an intent that an AI engine can answer in a paragraph rather than a list of links.
How do I find conversational keywords for my Singapore business?
Use a five-source method: harvest People Also Ask trees from Google SG SERPs, mine Reddit, HardwareZone and Seedly for SG-specific phrasing, filter your existing Search Console queries by question words, run discovery prompts in ChatGPT and Perplexity asking what audiences ask about your topic, then test the resulting list back through the same engines to find your gap. This combination surfaces 10x more rankable queries than classic Ahrefs or Semrush alone.
Why do conversational keywords show zero search volume in Ahrefs?
Two reasons. First, classic keyword tools sample volume from Google's search logs, which historically underweight long-tail queries. Second, conversational queries inside ChatGPT, Perplexity and Claude do not appear in Google logs at all. Ahrefs zero-volume readings on question-shaped queries are systematically wrong; the real volume only shows up after you publish, in Google Search Console impression data.
Should I write one big article or many small articles for conversational keywords?
Many small articles, clustered by intent. The rule: two questions belong on the same page only if a single high-quality answer satisfies both. Trying to answer 30 different questions in one giant article hurts both SEO (intent dilution) and AEO (AI engines cannot lift a clean 40 to 60 word answer because the page does not have one per question). Cluster properly, then write one piece per cluster.
How long should the answer paragraph under each question be?
Aim for 40 to 60 words. This is the length most AI engines lift cleanly when they cite a source in a generative answer. Shorter than 30 words usually lacks enough context to satisfy the query. Longer than 80 words gets truncated when the engine quotes you, which often loses the punchline. The 40 to 60 word range is the sweet spot for being both citable and complete.
Can I use ChatGPT to find keywords I should target?
Yes, this is one of the most underused techniques in 2026 SG SEO. Two prompts work well: a discovery prompt ("list 30 questions a [audience] in Singapore asks about [topic]") and a gap test (run those questions back through ChatGPT and Perplexity, note which return your brand and which do not). The "does not return your brand" list is your prioritised content gap. We routinely surface 50+ rankable conversational queries this way per client, in under an hour.