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Jobs to be done for paid search

Jobs to be done (JTBD) is a product strategy framework that treats customers as people hiring products to do specific jobs in their lives or work. The framework cuts through demographic and feature thinking and gets to what customers actually want.

It's also a remarkably useful lens for Google Ads.

The basics, briefly​

Customers don't buy products because they're products. They buy products because they have a job to do, and your product is one way to do it.

Classic example: someone buying a quarter inch drill bit doesn't want a drill bit. They want a quarter inch hole. The drill bit is the means; the hole is the job.

For B2B SaaS, the jobs are usually about work, time, or anxiety:

  • "I want my engineering team to ship faster without bureaucracy." (job)
  • "I want to know our pipeline is healthy without spending an hour every Monday compiling data." (job)
  • "I want to onboard new sales hires in 2 weeks instead of 8." (job)

Jobs are concrete things people are trying to accomplish. They're not features ("workflow automation") and not generic benefits ("improve productivity"). They're specific outcomes someone is hiring for.

Why this matters for Google Ads​

Two reasons:

1. Customers search for jobs, not categories​

Look at high intent search queries:

  • "How to track engineering work without Jira"
  • "Way to send sales emails without writing them all from scratch"
  • "Tool to onboard new reps faster"

These are job formulations. The searcher knows what they want to accomplish. They don't necessarily know what category of tool solves it.

Generic category queries ("project management software", "sales engagement platform") show lower intent because the searcher is exploring the category before committing to a specific job framing.

2. Job specific ad copy outperforms generic copy​

Compare two ads for a CRM:

Generic:

"The world's most powerful CRM. Try free today."

Job specific:

"Stop losing deals because your CRM is a chore. 5 minute updates."

The first is forgettable. The second names a specific job (keep deals moving) and a specific obstacle (CRM as a chore). Searchers who feel that pain notice immediately.

Job specific copy wins click through rate and, more importantly, conversion rate. The clicks come from people whose pain you've named. They're already half sold.

How to find your customer's jobs​

Three sources, in order of reliability:

1. Customer interviews​

The single best source. Ask new customers:

  • "When you decided to look for a tool like ours, what was happening in your work?"
  • "What were you trying to do that wasn't getting done?"
  • "What did you try before us, and why didn't it work?"

The answers are often surprising. "I needed to get my CEO off my back about pipeline visibility" is a more specific job than "improve sales productivity", and it's the actual reason a deal closed.

Patterns across interviews surface the dominant jobs.

2. Sales call transcripts​

If your sales team records calls, the discovery questions they ask and the answers they get reveal jobs. "What's prompting the search now?" elicits job statements.

Look for verbs and outcomes. "I want to..." or "We need to..." statements are jobs.

3. Win/loss reviews​

When you win a deal, why? When you lose, why? The answers usually map to jobs.

Wins often correlate with jobs your product does well. Losses often correlate with jobs your product doesn't do, jobs the customer prioritized that you didn't address.

How to use jobs in keyword research​

Jobs translate to keywords. Each job suggests a few specific search phrases:

Job: "Ship software faster without bureaucracy."

Possible queries:

  • "Project management for software teams"
  • "Lightweight project management"
  • "Alternative to jira engineering teams"
  • "Fast project tracking"
  • "Project tool without overhead"

Each of these is a customer expressing the job in a different way. Cluster them.

Job: "Get new sales reps productive in 2 weeks."

Possible queries:

  • "Sales onboarding tool"
  • "Sales rep ramp time"
  • "Sales training software"
  • "Onboard sales reps faster"

Different language, same underlying job.

When you build a campaign per job (rather than per category or per feature), the keywords cluster naturally. The cluster's intent is the job. The ad copy can name the job. The conversion rate goes up.

How to use jobs in ad copy​

Job in headline, evidence in description.

Headline: "Ship software faster than Jira allows" (names a job, names a known constraint).

Description: "Linear replaces Jira for engineering teams. Triage in seconds. Built for shipping." (evidence: speed, audience, outcome).

Compare to:

Headline: "Powerful project management" (no job).

Description: "Industry leading software for modern teams." (no evidence).

The first version converts. The second doesn't.

The pattern: name the job in the headline, prove it in the description.

The hardest part: figuring out the job​

The framework is conceptually clear. The hard part is knowing which jobs your product actually does best for which customers.

Most B2B SaaS products do several jobs for several customer types. Picking the wrong primary job wastes your campaign.

A few diagnostics:

  • Which customers are happiest? Look at NPS, retention, expansion. Their jobs are the ones your product nails.
  • Which use cases get expanded? Customers expanding usage are doing jobs they value highly.
  • What do success stories say? Customer case studies usually surface the dominant job clearly.

If you're unclear, run small campaigns for each of three or four candidate jobs and see which converts best. The market votes with conversion rates.

Where Hero Marketer fits​

The product analysis Hero Marketer runs during onboarding extracts jobs from your product description. The richer your description, the better the analysis at surfacing them. The campaign wizard then uses those jobs to weight keyword clustering and ad copy generation.

You can also tell Hero AI which jobs you care about, and it'll prioritize those when answering questions about campaign performance.

For more on the analysis: What product analysis does.

Going further​