Choose Keywords That Find Buyers

The same workspace, the same ICP, and the same scoring can produce anywhere from 0% to 47% high-fit leads. The difference is the source. This guide explains what separates a source that finds buyers from one that wastes credits. Everything in it comes from measured fit rates on real Signado sources, not theory. Sample sizes vary and are noted where they are small.

What makes a good keyword

A keyword tells Signado which LinkedIn posts to look at. The people who wrote those posts, or commented on them, become your potential leads. So the real question behind every keyword is: who talks about this on LinkedIn? Not who you want to find. Who actually writes and comments on posts containing these words.

Start with a concrete phrase your buyer would write when the problem is happening. That usually gives you a better crowd than a broad label. When there is no dependable pain phrase, a specific category, purchased service, product, or material can still open a useful pool. Keep the words tied to what you sell, and include the platform, channel, or product domain when a broad phrase would spill into unrelated markets.

Avoid generic outcomes such as need more customers, broad labels such as lead generation, and job titles used only to name the audience. Those phrases feel natural because they describe your market internally, but they rarely identify one useful LinkedIn conversation.

Measured on real sources in engager mode:

Keyword	What kind of phrase it is	High-fit rate
cold email is dead	Something a buyer would say	14.6%
lead generation	A broad product category	9%
n8n	A tool name	2%
hiring manager	A job title	0 of 5

Not every conversational phrase is a winner (reply rate dropped ran at 8.2%), but the shape sets your ceiling: every top source we measured was a phrase a buyer would say. Specific category phrases remain a fallback when the profile does not support four natural pain phrases.

Some rewrites, from label to buyer phrase:

• outbound sales (category) becomes cold email is dead (an opinion buyers debate)
• real estate broker (job title) becomes listings sitting too long (a pain that broker posts about)
• employee onboarding (category) becomes new hires quitting in 90 days (a complaint that buyer writes)

The next two sections explain why the two label types fail, because each fails for a different reason.

Why job titles find job seekers, not buyers

Ask yourself who writes or comments on a LinkedIn post containing the words "hiring manager". Almost never a hiring manager. A person who holds a job does not post about their own job title. The people who do talk about a job title are the people circling it: candidates who want that job, career coaches selling advice to those candidates, resume writers, and recruiters trying to fill the role.

We measured this directly. A source for hiring manager in engager mode returned five leads. None scored high fit. The crowd was job seekers and a resume coach, and the preview had shown exactly that before the source was ever activated.

The fix is to stop targeting who your buyer is and start targeting what your buyer says. If your buyer holds the hiring manager title, they rarely post "hiring manager", but they may post about the problems of the job: candidates ghosting after the offer, time to hire keeps slipping. Those phrases find the person holding the title because those are the words the title-holder actually writes.

There is one narrow exception. If you sell the work performed by a role, the role can be part of a genuine purchase request. A company selling outsourced SDR delivery can reasonably look for posts asking for an outsourced SDR partner. That is a request for the service, not an attempt to target everyone whose title contains SDR.

Why broad product categories often find competitors

The second trap is subtler. Suppose you sell lead generation services, so you add lead generation as a keyword. It describes your market, but the pool also contains many people who sell lead generation: agencies, tool vendors, consultants, and growth creators. A broad category can collect competitors and peers alongside buyers.

The mechanism is a vocabulary split. Buyers often describe problems in problem words, while sellers often describe the same market in category words. That is why a natural pain phrase is the first choice when one exists.

You can see this in the data. In our scored leads, roughly 15% of everyone discovered were capped as likely competitors by the ICP scorer. Signado's scoring catches them, so they will not clutter your high-fit view. But scoring happens after discovery, and discovery costs 5 credits per lead. The scorer protects your attention; it cannot refund the credits. It is cheaper never to invite competitors in the first place.

This is not a universal category ban. If there is no natural, offer-specific pain phrase, use a category that is specific enough to keep the search in the right world. LinkedIn lead generation is more useful for a LinkedIn-only offer than bare lead generation. apparel fulfillment services carries the product domain that bare fulfillment services would lose. Post relevance and ICP scoring still decide which posts and people survive.

Post authors vs post engagers: which mode to use

Every keyword source runs in one of three modes, and the mode decides who becomes a lead when Signado finds a matching post:

• Post authors collects the person who wrote each matching post.
• Commenters collects the people who commented on each matching post.
• Both collects the author and commenters from the same matching-post pool.

The two modes produce very different crowds, and the reason is self-selection. Writing a LinkedIn post about a problem is a strong signal: the author chose the topic, thought about it, and put their name on an opinion. People who do that are almost always living the problem professionally: operators, founders, consultants, practitioners. Commenting is a much weaker signal. A comment thread on a popular post gathers buyers, but also peers, job seekers, students, and people who simply enjoy arguing. The author self-selected; the commenters just showed up.

The measured difference is large. In one workspace, cold email in author mode ran at 47% high fit (13 of 17 scored leads) and outbound at 28%. Engager sources on strong phrases ran between 8% and 15%. Author mode consistently produces fewer leads per post (one author versus potentially many commenters), but a far higher share of them fit.

How to choose:

• Choose Post authors when your buyers write posts about the problem. This is true for founders, consultants, and operators in professions that post publicly. You get fewer, better leads, and your outreach can reference something they wrote themselves.
• Choose Commenters when you want volume, or when your buyers comment rather than publish. Some buyers never write posts but do comment on them. Commenter mode also hands you the comment text, which gives outreach a natural opening.
• Choose Both when both signals matter. One source searches the keyword once and can surface both the author and commenters from those posts. It uses one saved source and one active Daily slot while Daily is on.

The full mechanics of the two modes are in Post Authors vs Post Engagers.

How to choose a creator or competitor profile

A creator or competitor source watches a LinkedIn profile and surfaces the people commenting on that profile's posts. One question decides whether it works: is this profile's audience made of your buyers?

The measured spread is wide. Creator sources ran at 15 to 22% high fit when the profile's audience matched the workspace's ICP, and about 3% when it did not. Same feature, five times the yield, and the only variable is whose audience it is.

The common mistake is picking profiles you follow: the big names in your own industry. But a peer's audience is more peers. If you sell to SaaS founders, another agency owner's followers are mostly other agencies. The profile you want is the one your buyers read: the growth voice founders follow, the industry figure your customers quote. Ask where your existing customers spend their LinkedIn attention, and put your source there.

Check a source with a preview before spending credits

A preview costs 1 credit and shows you the real crowd before discovery starts: matching posts, plus the actual authors or commenters the selected mode would surface, with their names and headlines. For commenter previews, Signado adds a one-line first-look description of the sampled commenters' visible roles or professional domains. It does not judge their fit against your ICP. Keywords search all of LinkedIn, so the crowd is broad. Creator and competitor sources pull from a specific audience your buyers already follow. Active discovery costs 5 credits per lead, so the preview is the cheap moment to inspect a source before committing more credits.

Read a preview with one question: would you want a meeting with these specific people? Not "is the topic relevant" but "are these humans my buyers".

Two patterns from our data are worth repeating:

• The worst source we measured (166 leads, 1.2% high fit) was never previewed. One credit would have shown the mismatch before 160+ leads were paid for.
• Believe what the preview shows you. In one measured case, the preview for a keyword meant to find hiring managers surfaced a resume writer as a top potential lead. The source was activated anyway and delivered zero high-fit leads. The preview was right, and it usually is: it is drawn from the same crowd discovery will pull from.

Read the fit stats and replace weak sources

Once 10 of a source's leads have been scored, its card on the Discovery Sources page shows what share of them are a Strong fit or Worth a look. This turns keyword choice from a one-time guess into a feedback loop: activate, read the numbers, keep what works, rewrite what does not.

For calibration, from our measured data:

• About 24% reached Strong fit in a mature Signado workspace: 166 of 676 attributed scored leads. We round that rate down for the benchmark shown in the app.

A source stuck under 5% after 20 or more scored leads is telling you something: the crowd it attracts is not your crowd. Pause it, rewrite the phrase, or spend the slot on a different source. This matters more than it looks, because every active source takes an equal share of your daily budget. A weak source does not just underperform; it starves your good sources of budget.

Checklist before you activate

1. Is there a natural phrase your buyer would post when the problem bites?
2. Is it a job title? It will find job seekers, not the people holding the title.
3. If it is a category, does it name the exact channel, service, product, or material instead of a broad market?
4. Do your buyers write posts about this problem? If yes, try author mode.
5. For a profile source: do your buyers follow it, or do you?
6. Preview it. Would you take a meeting with the people it shows?
7. After 10 scored leads, check the fit rate on the source card. Replace what stays low.