Teach Pioneer What a Great Lead Looks Like

A criterion is a plain-language description of something you're looking for, like "must handle consumer financial data" or "should have open compliance roles". It is not a database filter. Nothing is being matched against a column somewhere; Pioneer searches by your descriptions and then researches every lead it finds to judge how well that lead actually fits each one.

Criteria are therefore how you teach Pioneer your taste. By the end of this page you'll know how to write descriptions Pioneer can act on, how it judges each one against each individual lead, how the relevance verdict is decided, and how to sharpen your criteria as real results come in.

Start from an example

Say you sell compliance software to fintech companies. A working set of criteria looks like this:

MUST:
- Must be a B2B fintech company (lending, banking, or payments, not a bank itself)
- Must handle consumer financial data
- Must have a live product with real customers

SHOULD:
- Should have raised Series A or later funding
- Should have open compliance or risk roles
- Should be based in the US

Read that list top to bottom and you know exactly what this team wants, and so does Pioneer. The MUSTs are non-negotiable; the SHOULDs describe the best version of a relevant lead. Every rule is something the public web can answer: product pages, funding announcements, job postings. That's the standard the rest of this page teaches.

Criteria work twice: finding and judging

Every criterion does double duty, and this is why they're worth more care than anything else you write:

1. Guiding discovery. Criteria shape which corners of the internet Pioneer explores. "Must have raised Series A funding" sends Pioneer to funding announcements; "should have open compliance roles" sends it to career pages.
2. Qualifying leads. Every lead is researched against every criterion, with evidence gathered and reasoning recorded for each judgment.

One definition of "a good lead," used in both places, so when you improve a criterion, the finding and the judging improve together. Better criteria mean better leads. It's that direct.

Pioneer judges every criterion against every lead

This is the mechanism underneath everything else on this page, and it's the opposite of box-ticking.

For each lead, Pioneer takes your criteria one at a time, reads what its research turned up, and makes a graded judgment: how strongly does this lead match what this criterion is asking for? Direct, unambiguous evidence on the lead's own pages is a strong match. Clearing the bar on one indirect signal is a moderate one. A tangential connection is weak. Alongside that judgment it records a verdict (met, not met, or inconclusive) and the reasoning and evidence behind both, which is what you read on the card.

The strength of match is judged separately from the verdict, and that's what makes it useful: a criterion can pass on thin evidence and still register as a weak match, and a criterion can fail while registering real partial alignment. Nothing here is precomputed. The same criterion produces a different judgment on every lead, because it's judged against that lead's actual evidence.

One consequence worth internalizing: a lead that only weakly matches your criteria loses ground even when it technically passes them. It's also why a vague description is expensive: "should be innovative" gives Pioneer nothing concrete to judge a lead against, so it contributes noise to every lead's position.

MUST and SHOULD are how you say what matters

The two tiers are how you tell Pioneer what's non-negotiable and what's merely preferred. The graded judgment above is how Pioneer applies that to each lead.

MUST criteria

Your deal-breakers, and the relevance gate. A lead needs to meet all of them to be relevant.

Examples:

• "Must be a B2B company (not selling to consumers)"
• "Must have raised venture funding"
• "Must have a presence in North America"

Use MUST only for things that, if missing, mean the lead isn't worth your time at all.

SHOULD criteria

What you value without requiring it. Each SHOULD feeds the ranking through how strongly a lead matches it, but none of them can disqualify a lead.

Examples:

• "Should have a team of at least 10 people"
• "Should have published content about sustainability"
• "Should be using modern cloud infrastructure"

Why the two tiers exist: collapse them and either every preference becomes a veto (you starve the pipeline) or every requirement becomes negotiable (you drown in noise). Keeping the contract and the taste separate is what makes both useful.

Relevance is a rule, not a vibe

Relevance is mechanical: a lead is relevant if every MUST criterion is met, mostly relevant if it meets most of what matters, and partially relevant otherwise. The tier is calculated from the criteria results alone: no AI override, no fuzzy weighting of your deal-breakers. You wrote the standard; the standard decides. A system that quietly overrode your stated deal-breakers would teach you that the controls are decorative, so it never does.

Each criterion gets one of three verdicts, with the reasoning and evidence behind it:

Inconclusive is an honest "don't know": Pioneer couldn't find enough public evidence either way, and says so rather than guessing.

SHOULD criteria never make or break relevance. They act on the ranking instead. A lead's position in the Leads column comes from adding up how strongly it matched each of your criteria, with a met MUST weighing substantially more than a SHOULD, enough that relevant leads always sit above leads that failed a deal-breaker, while within each group the strongest evidence rises first. Because every strength is judged per lead, the ordering adapts to what Pioneer actually found rather than to a formula you have to learn. Criteria Pioneer couldn't evaluate at all contribute nothing either way, so a lead is never punished for a failure on Pioneer's side.

So when a lead you like isn't relevant, there's exactly one place to look: which MUST failed, and whether you actually believe that rule. And when a relevant lead sits lower than you expected, the answer is in the strengths, not the verdicts: it passed everything, but weakly. How to read both on a real lead: Read a Lead's Research.

Write rules the web can answer

Pioneer evaluates criteria through web research, so a good criterion is one the public web can verify.

Be specific, not vague

• "Should be a good company" → "Should have been in operation for at least 2 years"
• "Must be in tech" → "Must be a software company (not hardware or services)"

Vague criteria fail twice: they can't guide the search, and they can't be evaluated with evidence.

Base criteria on discoverable information

Usually discoverable:

• Company size (LinkedIn, Crunchbase)
• Industry/vertical (website, press coverage)
• Funding status (Crunchbase, press releases)
• Geographic presence (website, job postings)
• Technology stack (job postings, case studies)

Often not public:

• Exact revenue numbers (unless disclosed)
• Internal processes
• Specific budget allocations

A criterion the web can't answer comes back Inconclusive on every lead, which tells you nothing. Rewrite it around a public signal: instead of "must have budget for tooling," try "should be actively hiring engineers" (a company that's hiring is spending).

Test one thing per criterion

Instead of "Must be a Series A+ company in fintech with at least 50 employees", write three rules:

• "Must have raised Series A or later funding"
• "Must be in the fintech industry"
• "Should have at least 50 employees"

Separate rules get separate verdicts, so when a lead falls short, you can see exactly where, and fix exactly that.

Start with 3–5

Too few criteria and results run broad, leaving you to filter by hand. Too many and results narrow toward zero, missing strong matches. Start with 3–5 and let real results tell you which way to adjust.

Sharpen criteria as results arrive

Your first criteria won't be perfect, and they don't need to be. Pioneer helps you refine them right on the board, in the Preferences column:

• Recommended actions: Pioneer analyzes your pipeline and suggests up to three concrete improvements to your criteria or properties. Click one to review the exact change before it's applied, or hit the refresh icon for a new set.
• Steering: type what you want in plain language ("more hardware companies", "exclude agencies") into the box at the bottom of the Preferences column. Pioneer turns it into a criteria change for you to review.
• Direct editing: click the pencil at the top of the Preferences column and edit the rules yourself.

When your criteria change, Pioneer re-checks your existing leads against the updated rules and uses them for everything it discovers next. Refinement applies to the whole pipeline, not just future leads. The full playbook, with a worked example: Refine Your Pipeline.

Two worked setups

Finding enterprise customers

MUST:
- Must be a B2B company selling to enterprises (not SMB or consumer)
- Must have raised at least Series A funding
- Must have a presence in the United States

SHOULD:
- Should have 100+ employees
- Should have published case studies on their website
- Should have a dedicated sales team

Finding investors

MUST:
- Must be an active investor (made investments in the last 2 years)
- Must invest in seed or Series A stage
- Must invest in B2B software

SHOULD:
- Should have invested in companies similar to ours
- Should be based in the Bay Area or NYC
- Should have a clear focus area that includes our space

More setups across six use cases: Example Pipelines.

Next steps

• How Pioneer Finds Leads: what your criteria actually steer
• Refine Your Pipeline: the loop that makes criteria great
• Create Your First Pipeline: put criteria into practice

Need help?

If you have questions, reach out to us at support@pioneerclimate.com