Low yield
4,202unique screening starts required at the mean
- Expected usable
- 142.8
- Limiting audience
- All usable interviews
Expected shortfall
Research planning tools
B2B recruitment planner
Can your recruitment plan reach the people you need?
Estimate the screening effort behind a usable sample. Check the unique supply, find the audience quota that limits recruitment, and see how changing assumptions affects the plan.
Start with your target and a defined source.
Use screening starts for a short calculation, or model the stages from a contact list. The planner supports one deduplicated source pool and up to six mutually exclusive quota cells. It calculates scenarios locally; no contact list is uploaded.
All starting values are illustrative, including the unique-pool confirmation. Replace them with your own assumptions. Switching starting point loads example pool and qualification values; check them before using the result.
Base scenario: Targets met in expectation only. Mean-based effort: 2,778 unique screening starts.
Recruitment scenario · editable assumptions
Targets met in expectation only
2,778unique screening starts at the mean-based requirement
Enough effort for every cell’s expected yield to reach its target. This is not a guarantee or the expected time to finish recruitment. “No result within limit” means zero yield or more than 10 million starts/records.
216expected usable before quota closure
3,000unique screening starts available
222 starts/records above the mean-based requirement.
Limiting audience: All usable interviews
At least 200 distinct organizations are needed. The pool must already have one candidate per distinct unit.
Where the available pool is reduced
Expected counts before quota closure; bar lengths use the starting pool. Losses at each stage have different meanings.
Qualified people300
2,700 lost at this stage
Completed interviews240
60 lost at this stage
Usable interviews before quota closure216
24 lost at this stage
Chance of filling the plan
Not modeled. Open the optional probability controls to review the assumptions.
Recruitment yield does not establish representativeness, statistical adequacy, current supplier capacity, or field duration. No universal B2B conversion rates are assumed.
Your assumptions and calculations
B2B recruitment plan https://russellresearch.com/tools/b2b-recruitment-planner/ Source: Illustrative recruitment source Unit: person; target: 200; mode: simple; available unique screening starts: 3000 Unique pool confirmed: true; multiple people per organization: false Minimum distinct organizations: 200 (arithmetic lower bound, not a forecast) Rates: low / base / high percentages; conditional on the previous stage. Joint eligibility: 8 / 10 / 12; User assumption Survey completed: 70 / 80 / 90; User assumption Quality accepted: 85 / 90 / 95; User assumption Simple mode treats all screening starts as eligibility-determined; eligibility is joint organization/person qualification. Full mode separates them. Quota structure: none. Shares are joint shares of all qualified people; common completion and quality rates across cells. low: Expected shortfall; expected usable before quota closure 142.8; mean-based effort 4,202 unique screening starts; limiting cell All usable interviews All usable interviews: expected 142.8; target 200; shortfall 57.2; fill not modeled base: Targets met in expectation only; expected usable before quota closure 216; mean-based effort 2,778 unique screening starts; limiting cell All usable interviews All usable interviews: expected 216; target 200; shortfall 0; fill not modeled high: Targets met in expectation only; expected usable before quota closure 307.8; mean-based effort 1,950 unique screening starts; limiting cell All usable interviews All usable interviews: expected 307.8; target 200; shortfall 0; fill not modeled Base funnel (before quota closure): Qualified people: 300; lost at stage: 2,700 Completed interviews: 240; lost at stage: 60 Usable interviews before quota closure: 216; lost at stage: 24 Screening starts at mean-based effort: 2,778 Independent, identical fixed-probability trials confirmed: false. Probability enabled: false. Fill probability withheld: independence unconfirmed or people clustered within organizations. Sensitivity: vary one rate across its range, hold other rates at base and quota shares fixed. Joint eligibility: effort 2,315 (high rate) to 3,473 (low rate) Survey completed: effort 2,470 (high rate) to 3,175 (low rate) Quality accepted: effort 2,632 (high rate) to 2,942 (low rate) Model: one finite unique pool, one attempt per unit, fixed rates, static exclusive quotas. Binomial cell tails; union lower bound, minimum marginal upper bound. Quota events are not assumed independent. Required probability effort uses equal cell failure-risk allocation. Scenario ranges are assumptions, not confidence intervals. Mean-based effort is not expected stopping time or a guarantee of quota completion. Funnel yields precede quota closure; organization ceilings do not establish attainable allocation. No source-overlap estimation, multiple-source optimization, overlapping margins, historical uncertainty fitting, dynamic routing, session attendance, costs, or field-duration forecast. No sample-adequacy, representativeness, live inventory, or legal-permission assessment.
How much does the plan depend on the rates?
Low combines every low conversion rate; high combines every high rate. Quota shares stay fixed. These are assumption scenarios, with no assigned likelihood.
Base yield
2,778unique screening starts required at the mean
- Expected usable
- 216
- Limiting audience
- All usable interviews
Targets met in expectation only
High yield
1,950unique screening starts required at the mean
- Expected usable
- 307.8
- Limiting audience
- All usable interviews
Targets met in expectation only
Which assumption changes the required effort most?
Each row changes one rate across its entered range, with every other rate at base and quota shares fixed. Sorted by the increase in required effort. Equal or zero ranges can tie.
| Assumption | At its high rate | At its low rate |
|---|---|---|
| Joint eligibility | 2,315 | 3,473 |
| Survey completed | 2,470 | 3,175 |
| Quality accepted | 2,632 | 2,942 |
From an estimate to fieldwork
Check the audience behind each percentage.
A list of professionals, a list of companies, and a panel of qualified decision-makers describe different supply. Confirm the unit, screening criteria, source overlap, and validation process before committing to a target.
Discuss B2B recruitmentRead our B2B research guidanceWhat counts as one interview?
Decide whether you need individual professional opinions or evidence about companies or locations. Company and location modes require one representative record per distinct unit. Multiple people within a company do not create multiple companies.
If individual research permits several people per organization, the planner checks a hard capacity ceiling and reports a minimum organization count. It cannot determine their distribution across organizations or apply an independent-trial probability model. AAPOR establishment guidance.
Why separate unfinished screeners from ineligibility?
Someone who leaves before the screener establishes eligibility has an unknown status. Contact-list mode shows that loss separately. The short mode assumes every start reaches an eligibility decision; switch modes if that assumption is unsuitable. Collection-stage definitions.
Can I multiply industry and job-role percentages?
Only when the second percentage is conditional on the first group, or when an independence assumption is justified. Knowing that 40% of a source works at large companies and 30% holds a target role does not establish a 12% joint incidence. Their overlap could range from 0% to 30%.
Enter measured or defensible joint cells. Quota shares here are shares of qualified people, not shares of the whole contact list. Overlapping margins need a joint audience table and are outside this release.
Why might the overall yield look sufficient while a quota is short?
Extra people in a common audience cannot fill a rare audience. The mean-based requirement is the largest cell target divided by that cell’s usable yield per record or start. The displayed funnel precedes quota closure; it does not predict accepted totals after cells close.
What does the fill probability assume?
One finite pool of unique units, one attempt per unit, independent outcomes across units, and common fixed conversion probabilities. Individual cell counts then have binomial distributions. This is a model of uncertain recruitment outcomes, not sampling without replacement from a known number of qualified people. Rates estimated from limited past data carry additional uncertainty that the model does not fit.
For multiple cells, the planner shows a union-bound lower limit and the smallest individual probability as an upper limit. It never multiplies quota probabilities. Sufficient effort divides allowable failure risk equally among cells; it can exceed the effort an exact joint calculation would require. Binomial reference.
Does this establish a representative or adequately sized sample?
No. Quotas and high yield do not establish a known probability of selection or remove coverage and nonresponse bias. The research design must separately support the analysis. AAPOR outcome-rate guidance.
For supported independent percentages and means, use the detectable-difference calculator. For conjoint work, use the conjoint sample-size estimator. Qualitative session attendance, costs, field time, and live supplier inventory require separate planning.
Methods and sources
Explicit denominators and visible assumptions.
Usable yield is the product of conditional conversion rates. Cell yield also includes its joint share of qualified people. Low/base/high scenarios are assumption sensitivity, not confidence intervals. Evidence labels describe the input’s stated origin and do not certify accuracy.
Sources reviewed September 29, 2026. Professional guidance informs stage definitions; the scenario and quota-risk conventions are the planner’s own disclosed methodology.
- AAPOR: Standard Definitions for Establishment Surveys (2025)
Defines organizational units and separates collection stages, unknown eligibility, and usable data.
- AAPOR: Standard Definitions
Explains outcome rates and why a response rate alone does not establish absence of nonresponse bias.
- ESOMAR/GRBN: Guideline on Online Sample Quality
Guidance on online participant validation, duplicate prevention, screening, and source transparency. This does not supply project-specific rates.
- NIST: Binomial Distribution
Reference for the fixed-probability binomial calculation. Joint quota bounds and equal risk allocation are this planner’s disclosed conventions.