Buying signals: what they are, examples from job postings, and how to collect them

Most writing about buying signals lists things a prospect says on a call. Those are real, but by the time a prospect is on a call the signal has done its job. The buying signals worth automating are the ones that appear before anyone talks to you, and the most reliable of those is a job posting. This guide defines the term, walks through examples that are each a measurable posting pattern, and shows how to collect them with an API instead of a browser tab.

What are buying signals?

Buying signals are observable actions that show a company or a person is moving toward a purchase. They range from a prospect asking about pricing to a company posting jobs for a team that will need your product. The strongest signals are budgeted decisions made in public, and a job posting is exactly that: headcount approved, money allocated, and the need published by the company itself.

The word covers three layers that fire at different times. Conversational signals happen inside a sales cycle: a question about implementation, a request for a security questionnaire, a second stakeholder joining the call. Behavioural signals happen just before it: repeat visits to a pricing page, a demo request, a free-tier signup. Structural signals happen before the company knows it is a prospect: a funding round, a new executive, a new team being hired. Job postings sit in the third layer, which is why they lead the other two.

What is a buying signal in sales?

In sales, a buying signal is any evidence that an account has budget, a problem your product solves, and a reason to act now. Reps use conversational signals to decide when to close. Sales development and revenue operations teams use structural signals to decide who to contact in the first place, because those signals exist for every company, not only the ones already in a conversation.

Hiring is the structural signal with the best ratio of specificity to availability. A posting names the function, the seniority, the location, often the tools, and sometimes the salary. It is published by the company on its own careers page or through its applicant tracking system, so there is no inference step. The glossary entry on hiring-signal intent covers how this compares with content and review intent; the short version is that hiring precedes both, because the team that will read your content has to be hired first.

Buying signals examples

Every example below is a pattern you can query, and each carries the share of companies showing it across the ten boards JobsPipe collects. The share matters because a signal is only as strong as it is rare: a pattern that four in ten hiring companies show is a filter, not a trigger.

• A first sales posting at an established company. Among companies that were already hiring more than 30 days ago, 10.3% posted their first sales role in the last 30 days. A first sales hire means a company is moving from founder-led selling to a team, and the team will need a CRM, sequencing, data and dialing before it is productive.
• A first engineering posting. 10.6% of established companies posted their first engineering role in the last 30 days. Where the company is not a software business, this is usually an internal build decision and a good signal for infrastructure, tooling and security vendors.
• A first marketing posting. 6.6% of established companies posted a first marketing role in the last 30 days. It is the rarest of the three first-hire signals, and a strong one for marketing automation, analytics and agency sellers.
• A lead or executive opening. 17.6% of hiring companies have at least one open role at lead or executive seniority. New leaders re-evaluate the stack they inherit, so the opening is an earlier signal than the appointment announcement that follows it.
• An engineering burst. Only 2.2% of hiring companies have three or more engineering roles open at once. The rarity is the point: a company in this slice has funded a build and is about to spend on everything a bigger engineering team consumes.
• Hiring across three or more functions. 10.3% of hiring companies have open roles in at least three functions. Broad hiring usually follows a funding event or a launch and is a reasonable proxy for both when neither was announced.
• Ten or more open roles. 13.4% of hiring companies have ten or more roles open, and those companies account for 77.7% of active postings. Volume is a real signal for sellers of high-volume tooling, but note the concentration: most postings come from this minority of large hirers, so raw posting counts overweight them.
• A single opening at a small company. 41.5% of hiring companies have exactly one role open. On its own that is a weak signal, but combined with a small headcount it becomes a strong one, because one hire at a thirty-person company is a larger relative change than a hundred at a thirty-thousand-person one.
• Tooling named in the posting. 25.0% of sales postings name CRM as a skill and 15.9% name lead generation. When a posting names a competitor product, the account is running it today, which is a displacement signal rather than a greenfield one.

How to interpret buying signals

Four rules keep a signal programme honest. First, rarity is strength. Read every signal against its base rate above; a pattern shown by 41.5% of hiring companies cannot carry a play on its own. Second, lead time is long. A posting maps to a purchase one to two quarters out, so a hiring signal belongs in account tiering and nurture, not in a same-day cadence. Third, signals compound. A lead-level opening at a company that is also in the engineering-burst slice is a different account from one that shows either alone. Fourth, signals decay. A posting closes, and a closed posting means the hire is made and the buying window for team tooling is opening, or the plan was dropped. The status, closed_at and closed_reason fields carry that state.

One trap is treating volume as intent. Because 77.7% of postings come from the 13.4% of companies with ten or more roles, a feed sorted by posting count is a list of large employers. Normalise by headcount: the company_object.employee_count field lets you divide open roles by size, which is what turns a raw count into a growth signal.

How to collect buying signals from job postings

Two requests cover most programmes. The first finds the pattern once; the second polls for new matches without re-reading the corpus. Both use real filter names on POST /v1/jobs/search, and the hiring signals API page has the full set.

Find the first-sales-hire pattern at small companies. The size filter uses exact headcount where known, so companies with no size data are excluded by default.

curl -X POST https://api.jobspipe.dev/v1/jobs/search \
  -H "Authorization: Bearer $JOBSPIPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "job_title_or": ["sales development representative", "business development representative", "account executive"],
    "job_seniority_or": ["entry", "mid"],
    "max_employee_count": 200,
    "posted_at_max_age_days": 14,
    "limit": 50
  }'

Poll for anything new since the last run. discovered_at_gte tracks when JobsPipe first saw a posting, not when the company dated it, so a scheduled job that stores its last timestamp sees each posting exactly once.

curl -X POST https://api.jobspipe.dev/v1/jobs/search \
  -H "Authorization: Bearer $JOBSPIPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "company_name_or": ["Ramp", "Mercury", "Linear"],
    "discovered_at_gte": "2026-09-08 00:00:00",
    "limit": 100
  }'

Each result carries job_title, company, company_domain, seniority, job_function, date_posted, discovered_at and technology_slugs, which is enough to route the account into a CRM with the reason attached. If you would rather not run the poll yourself, Signals saves the same filters and delivers new matches by email, Slack or signed webhook, and Workflows builds the filter from a sentence. The free tier covers 1,000 jobs a month, which is enough to watch a few hundred named accounts daily.