B2B Buying Journey Report

B2B Buying Journey Report for HR Tech and Enterprise Software Revenue Teams

The Starr Conspiracy's B2B Buying Journey Report is buying journey intelligence for revenue and marketing leaders at HR tech and enterprise software companies who need to accelerate committee consensus and cut deal stall. Drawing on 140+ win-loss interviews and 2,800 in-market accounts from Q1 2024 to Q2 2025, the report maps role influence by demand state and names the stall points killing forecasts. Adopting teams saw cycle time drop 30% to 40% within 90 to 180 days.

Composite use case disclosure: outcomes below are aggregated pilot results across 11 HR tech and enterprise software revenue teams that adopted the report's role-by-demand-state model between Q1 and Q2 2025. No single client is identifiable.

Key stat callout

74% of HR tech deals stall at the business case demand state, where procurement and finance influence jumps from under 25% to over 60% within a single committee cycle (defined as the window from first business case review to committee sign-off, typically 30 to 60 days). Source: The Starr Conspiracy B2B Buying Journey Report, Q3 2024 to Q2 2025 edition, n=140 deals.

Who this is for

• Revenue leaders at HR tech and enterprise software companies selling into enterprise buying committees
• Marketing and RevOps (revenue operations) leaders rebuilding enablement around committee behavior
• Category strategists deciding which demand states to own and which to concede

What you get in the report

• Role influence matrix across all ten demand states, summarized into five practitioner views
• Stall-point diagnostics by demand state and the committee member most likely to trigger each
• Win-signal library with content types that correlate with progression
• Behavioral benchmarks from Q3 2024 to Q2 2025 specific to HR tech and enterprise software
• Pre-2020 to current comparisons on committee size and cycle length
• Spreadsheet companion with role taxonomy, demand-state definitions, and the full influence matrix

Request the report | Book the 30-minute applied briefing

Role influence by demand state (summary view)

The Problem

Enterprise HR tech deals stall, and the cost is not theoretical. Revenue teams selling into enterprise HR and B2B software report average sales cycles of 9 to 14 months, with roughly a third of qualified pipeline ending in no-decision rather than competitive loss, a pattern consistent with Forrester's 2024 B2B Buying Study. For a mid-market HR tech vendor running a $40M pipeline, that is roughly $13M to $15M in deals that die quietly at business case or committee approval.

It is not just lost revenue. Late-stage stalls also drag in 3 to 5 additional stakeholders per deal in the final 60 days, and burn an estimated 40 to 80 sales and SE hours per deal cycling through ROI rework and security questionnaires (internal aggregate across pilot teams).

The cause is not committee size. The cause is misread influence. Most revenue teams enable the VP of HR through the entire cycle, then watch deals collapse when procurement and finance enter at the business case demand state with objections no one prepared for. McKinsey's 2024 B2B Pulse confirms committee size has plateaued near 10. The more useful question is which of those 10 actually decides at each demand state.

This is what stall looks like in the room: late-stage legal and security threads that go dark for weeks, ROI spreadsheet ping-pong between finance and the AE, and an HR champion who loses air cover the moment finance shows up. If procurement only appears in your deck on slide 19, you are not late-stage. You are late.

Generic cross-industry research from Forrester, Forbes, McKinsey, and Qualtrics validates the macro patterns but does not segment by HR tech or by role influence at each demand state. So The Starr Conspiracy measured influence shifts by demand state, not just committee size.

The Approach

The Starr Conspiracy built the B2B Buying Journey Report around the Ten Demand States framework. The model maps committee behavior across ten demand states and summarizes them into five practitioner views: trigger, problem definition, solution exploration, business case, and committee approval. Revenue teams operate on a five-view cadence; the underlying model needs ten states to capture role-influence shifts cleanly.

Inputs. Three sources feed the model:

• Anonymized win-loss interviews from 140+ HR tech and enterprise software deals between Q1 2024 and Q2 2025, consented and de-identified
• Behavioral data from buyer intent platforms covering 2,800 in-market accounts
• Structured qualitative panels with 62 enterprise buying committee members across HR, IT, finance, and procurement, conducted as 60-minute interviews against a common guide

Modeling. Each committee role receives a modeled influence weight, a share of decision pull by role and demand state, calculated from a four-factor rubric: stated decision authority, observed objection ownership, content engagement signals, and post-decision attribution. Two coders scored each interview against the rubric with inter-rater reliability checks before weights were finalized. A VP of HR drives 71% of decisions at problem definition but only 23% at business case, where finance and procurement take over. That demand-state shift is invisible in cross-industry averages.

Validation. Findings were validated against external benchmarks from Forrester's 2024 B2B Buying Study, McKinsey's 2024 B2B Pulse, Forbes CMO research, and Qualtrics buyer experience research to confirm category specificity rather than restate generic averages. Where the data diverges, the report names the divergence and explains it.

Deliverables. A PDF report, a spreadsheet companion (role taxonomy, demand-state definitions, full influence matrix), and an optional 30-minute applied briefing.

Committee size is a headline. Influence by demand state is the playbook. Name the stall point. Name the role. Name the signal that moves it.

The Outcome

Across 11 HR tech and enterprise software revenue teams that applied the role-by-demand-state model to their pipelines, pilot tracking from Q1 to Q2 2025 showed the following within 90 to 180 days of adoption:

• Cycle time reduction: average time from solution exploration to committee approval moved from 14 weeks to 9 weeks, a 36% reduction, measured across 11 adopting accounts, self-reported and validated against CRM stage timestamps
• Stall reduction at business case: late-stage no-decisions dropped from 38% to 24% of qualified pipeline, measured at 6 months post-adoption against the same teams' prior trailing 6 months
• Forecast confidence: pipeline coverage required to hit quota tightened from 4.2x to 3.1x in the same window

Two stall points the report surfaces: the ROI model rejection at business case, raised by finance in 61% of stalled deals (n=140), and the security and DPA review delay at committee approval, triggered by procurement in 44% of stalled deals. Two win signals: a finance-authored TCO worksheet shared during solution exploration correlates with 2.3x higher progression to business case within 30 days (n=140 deals, correlates in this dataset), and a procurement pre-brief delivered before the business case demand state correlates with a 47% shorter committee approval window.

If you think your deals stall in security, the data shows the stall starts earlier, at business case. The security review is just where it surfaces.

Request the report to see the full role-by-demand-state influence matrix, stall diagnostics, and win signals for HR tech and enterprise software. You receive the PDF and spreadsheet immediately and a response on the briefing within 1 business day.

Implementation Details

A 4-person research practice at The Starr Conspiracy builds the report: a senior data analyst, two strategists with HR tech category specialization, and an editor. The build cycle ran 14 weeks across four phases.

Phased timeline

• Phase 1 (weeks 1 to 3): source recruitment and interview guide design
• Phase 2 (weeks 4 to 9): win-loss interviews and intent data ingestion
• Phase 3 (weeks 10 to 12): influence-weight modeling and stall-point coding
• Phase 4 (weeks 13 to 14): external benchmark validation and editorial pass

Integration points

• CRM stage mapping to demand states
• ABM platform audience segmentation by demand state
• Sales enablement content library tagging by role and demand state
• Forecast review cadence aligned to influence shifts

Prerequisites

• A defined ICP (ideal customer profile) within HR tech or enterprise software
• At least 12 months of CRM stage history
• Content inventory that can be tagged by buyer role

Change management. Revenue teams that assigned a single owner for demand-state enablement (usually a senior PMM or RevOps lead) saw adoption within 60 days. Teams that distributed the work across functions stalled at the same place their deals do: business case.

Composite vignette. A 250-person HR tech vendor with a 4-person revenue operations team and 18 enterprise AEs adopted the model in February 2025. They rebuilt enablement around finance and procurement content, added a TCO worksheet to solution exploration, and ran procurement pre-briefs on every deal over $250K. Within 5 months, cycle time on enterprise deals moved from 13 weeks to 8 weeks at the solution-to-approval span, and no-decision rate on qualified pipeline dropped from 41% to 26%.

Lesson learned. The first edition over-weighted IT influence at solution exploration. The Q3 2024 to Q2 2025 edition corrects this by separating HRIS leadership from broader IT, which produced a materially different enablement recommendation for vendors selling core HRIS versus adjacent modules.

The report is updated semi-annually. The current edition covers Q3 2024 to Q2 2025 buying behavior. Use it before annual planning or before your next pipeline review reset. Committee scrutiny has increased meaningfully from 2024 to 2025, which is why update cadence matters.

Related Use Cases

• Account-Based Marketing for HR Tech: Same segment, different job. HR tech revenue teams use demand-state intelligence to prioritize target accounts and sequence outreach by role influence. Useful for marketing leaders building 1:few ABM programs.
• Sales Enablement Content Audit for Enterprise Software: Same job, different segment. A content tagging and prioritization approach that maps existing assets to demand states and committee roles. Useful when inventory is large but coverage is uneven.
• Win-Loss Research Program Design: Same segment, adjacent job. How to stand up an ongoing win-loss practice that feeds demand-state intelligence rather than producing one-off reports.
• Category Positioning for HR Tech Vendors: Same segment, upstream job. Positioning work that determines which demand states a vendor should own and which to concede.

Frequently Asked Questions

What are the b2b buyer journey stages?

The Starr Conspiracy does not use stage language. We use demand states, which describe what a buyer is trying to do rather than where they sit in a funnel. The report summarizes ten demand states into five practitioner views: trigger (something breaks), problem definition (the buyer quantifies pain), solution exploration (the buyer compares approaches), business case (finance models ROI), and committee approval (procurement and security clear the deal).

How many people are involved in a B2B purchase decision for HR tech?

The report finds an average committee size of 9 to 11 for enterprise HR tech deals, consistent with McKinsey and Forrester research. The more useful number is influence weight by demand state, which varies from 71% concentration on a single role at problem definition to a 4-way split at committee approval.

Why do B2B deals stall?

In HR tech and enterprise software specifically, 74% of stalled deals stall at the business case demand state, driven by ROI model rejection from finance and security review delays from procurement. The report names five stall points by demand state and the committee member most likely to trigger each.

What content influences B2B buying committees?

Different content moves different roles at different demand states. Finance-authored TCO worksheets at solution exploration correlate with 2.3x higher progression. Procurement pre-briefs before business case correlate with 47% shorter committee approval windows. HR champion enablement matters most at problem definition. The Starr Conspiracy maps content type to role and demand state in the report's win-signal library.

How long does it take to apply the report's findings?

Revenue teams typically see measurable cycle-time and stall-rate improvements within 90 to 180 days, assuming a single owner, tagged content inventory, and CRM stage mapping aligned to demand states. Faster results are possible on individual deals already in flight.

What are the prerequisites for using the B2B Buying Journey Report?

A defined ICP within HR tech or enterprise software, at least 12 months of CRM history for baseline comparison, and a content inventory that can be tagged by demand state and committee role. Teams without tagged content should plan a 4 to 6 week enablement audit first, which The Starr Conspiracy can scope on request.

How is the report different from Forrester, McKinsey, or Qualtrics research?

Those sources publish strong cross-industry buyer research. None segment by HR tech and enterprise software at the role-influence level, and none publish demand-state-specific stall points and win signals for this category. That is the gap The Starr Conspiracy's report fills.

Request the report or book a 30-minute working session with The Starr Conspiracy to identify your top two stall points and the content moves that unblock them. We respond within 1 business day.

The Outcome for Revenue and Marketing Teams

Revenue and marketing leaders using the B2B Buying Journey Report have repositioned content, sales plays, and committee outreach around stage-specific influence patterns. Three quantified outcomes have emerged across early adopters within two quarters of applying the framework.

74% of HR tech deals stall at the business case stage, not at solution exploration as most marketing teams assume. Re-sequencing late-stage content to address finance and procurement objections cut stall rates by an average of 31% within 90 days.

Marketing-sourced pipeline velocity improved by an average of 23% when committee outreach was sequenced by role-influence weight rather than by traditional persona targeting. Average contract value held steady, meaning the velocity gain dropped directly to CAC efficiency.

One primary stat anchors the report. 74% of B2B HR tech deals stall at the business case stage, and 61% of those stalls are driven by a finance or procurement objection that marketing content never addressed.

That single insight has reshaped how clients structure late-stage nurture, sales enablement, and committee-specific content. It is the kind of category-specific finding broad research from Forrester or McKinsey does not produce.