Written by: Aaron Rovner, Founder, Saas Hero | Last updated: August 14, 2026
Key Takeaways
- Map every stakeholder’s internal buying jobs before creating collateral so each asset directly supports deal progression.
- Apply a five-question conversion rubric to every asset so content is role-specific, objection-focused, and backed by real evidence.
- Build a persona-by-stage matrix that creates distinct asset versions for each role and stage, instead of generic one-size-fits-all content.
- Score every asset on a 9-point rubric and retire low performers so your library stays high-conversion and easy for reps to use.
- Book a discovery call with SaaS Hero to map collateral gaps, score existing assets, and connect usage data to influenced ARR.
The Six-Step Buyer-Task Framework
- Map Buying Jobs, and identify the specific tasks each stakeholder must complete to advance the deal.
- Define the Five Questions Every Asset Must Answer, and use them as a conversion filter for all content.
- Create Stakeholder-Specific Versions, and build a persona-by-stage matrix for every role in the buying committee.
- Score Each Asset on the 9-Point Conversion Rubric, and evaluate every existing and new asset against it.
- Organize the Library by Moment, and structure assets by buying job and deal moment, not by format.
- Measure Usage-to-Revenue Impact, and connect asset usage to win rates, deal velocity, and influenced pipeline in the CRM.
Step 1: Map Buying Jobs Across the Buying Committee
Objective: Identify every task a buying committee member must complete to move the deal forward internally.
Forrester’s 2024 State of Business Buying Report found that the average B2B purchase now involves 13 stakeholders, with 89% of buying decisions crossing multiple departments. 86% of B2B purchases stall at some point. Buying job mapping counters this stall risk by revealing where deals slow down and why.
Actions to complete this step:
- Interview eight to twelve recent buyers, across both won and lost deals, and ask what internal tasks they had to complete before approval. These interviews create the qualitative foundation for your job inventory.
- Next, pull win/loss notes and opportunity data from the CRM, then tag recurring internal tasks by role such as economic buyer, technical evaluator, end user, champion, and gatekeeper. This step validates and expands what you heard in interviews.
- Then review call recordings for moments where deals stalled, and look for missing jobs that did not surface elsewhere. Identify the specific missing job that caused each stall.
- Finally, synthesize all three data sources into a buying job inventory, a list of ten to twenty discrete tasks, each assigned to a stakeholder role and a deal stage.
Example: A workflow automation SaaS serving mid-market legal firms identifies three champion jobs: “demonstrate ROI to the COO,” “confirm security posture with IT,” and “show adoption path to end users.” Each job requires a distinct asset.
Quality check: Phrase every job from the buyer’s perspective, such as “I need to prove payback period to finance,” instead of the seller’s perspective, such as “send ROI one-pager.”
Common mistake: Teams often map internal CRM stages instead of the buyer’s real tasks. This is one of the most frequently cited buyer journey mapping errors.
Step 2: Build a Five-Question Conversion Rubric for Every Asset
Objective: Establish a conversion rubric that every asset must pass before it enters the library.
Over 60% of sales content created for reps never gets used. Most unused content feels too generic to address specific buyer concerns. The five-question rubric fixes this by forcing creators to define who the asset serves and what problem it solves.
Every asset must answer all five questions:
- Who is this for? Name one specific role, not a vague group like “business buyers.”
- What buying job does it complete? Reference the job inventory from Step 1.
- What objection does it resolve? Name the specific concern, such as “integration complexity” or “unclear payback period.”
- What evidence does it provide? Include a named customer result, a third-party study, or first-party aggregate data.
- What is the one action the reader takes next? Use a single CTA with no competing actions.
Actions to implement the rubric:
- Document the five questions in a shared template that every content creator and agency partner completes before drafting.
- Apply the rubric retroactively to all existing assets during the scoring audit in Step 4.
- Require all five answers in the asset’s metadata record in the CMS or shared drive so they stay visible and enforceable.
Example: A pricing one-pager for a CFO answers: Role = CFO; Job = build budget justification; Objection = unclear total cost of ownership; Evidence = 14-month payback period from a named customer; CTA = download the full ROI model.
Troubleshooting: If a team cannot answer the evidence question, do not publish the asset. Placeholder evidence consistently hurts conversion.
Step 3: Create Stakeholder-Specific Versions by Stage
Objective: Build a persona-by-stage matrix that produces a distinct asset version for each role at each deal stage.
Mid-market DMUs typically involve 6 to 10 stakeholders with 1-to-4-month decision cycles, while enterprise DMUs expand to 7 to 12 participants with 6-to-18-month cycles. One generic version of an asset cannot serve this range of roles and timelines.
Actions to build the matrix:
- List every role identified in Step 1 as matrix rows, including economic buyer, technical evaluator, end user, champion, finance or procurement, and gatekeeper.
- List deal stages as columns, such as problem awareness, solution exploration, requirements building, vendor evaluation, and decision and negotiation.
- For each cell, specify the asset type, the primary buying job it serves, and the five-question answers.
- Prioritize cells where deals most frequently stall, often vendor evaluation and decision stages for economic buyers and technical evaluators.
Role-specific content priorities, drawn from buying committee research:
- Economic Buyer / CFO: ROI calculators with PDF export, payback period summaries, total cost of ownership comparisons.
- Technical Evaluator / IT: Security and compliance packs, integration guides, API references.
- End Users: Product walkthroughs, use-case videos, hands-on trial guides.
- Champion: One-page internal summary, short recorded overview, competitive talking points, quick FAQ for Slack forwarding.
- Finance / Procurement: Pricing transparency one-pagers, contract flexibility details, vendor credibility references.
Tip: Enforce a maximum of three assets per stage-role-vertical-format cell and retire redundant alternatives during quarterly audits. Large libraries rarely increase usage.
Step 4: Score Each Asset on a 9-Point Conversion Rubric
Objective: Assign every asset a numeric score that determines whether it enters the library, requires revision, or is retired.
The 9-point rubric scores each asset across three dimensions, with a maximum of three points per dimension:
- Specificity (0–3): 0 = generic audience, 1 = named role but no stage, 2 = named role and stage, 3 = named role, stage, and specific objection context.
- Evidence Quality (0–3): 0 = no evidence, 1 = generic claim, 2 = third-party study or unnamed customer result, 3 = named customer result with a quantified outcome.
- Job Completion (0–3): 0 = does not complete a buying job, 1 = partially addresses a job, 2 = completes one job with a clear CTA, 3 = completes one job, uses a role-specific CTA, and is forwardable without rep involvement.
Scoring thresholds:
- 7–9: Publish to the active library.
- 4–6: Revise before publishing and assign a specific editor with a two-week deadline.
- 0–3: Retire or rebuild from scratch using the five-question rubric.
Actions to run the scoring process:
- Start by exporting all existing assets from the shared drive or CMS into a scoring spreadsheet so you have a master audit list.
- For each asset, assign two reviewers to score independently, then average the scores. Dual scoring reduces bias and creates more reliable results.
- After scores are finalized, record the final score, revision status, and owner in the asset metadata so the library reflects current quality.
- Set a quarterly re-scoring cadence for all active assets to keep quality aligned with changing buyer needs and positioning.
Example: A generic “product overview” one-pager scores 1, with Specificity at 0, Evidence at 1, and Job Completion at 0, so it is retired. A CFO-specific payback period summary scores 8, with Specificity at 3, Evidence at 3, and Job Completion at 2, and it enters the active library immediately.
Common mistake: Teams sometimes score assets by design quality instead of conversion function. A polished PDF with no named evidence and no specific role scores lower than a plain-text champion FAQ that answers all five questions.
Step 5: Organize the Library by Buying Moment
Objective: Structure the asset library so a rep or champion can retrieve the exact stakeholder-specific asset in under sixty seconds.
Folder taxonomy by moment:
- Moment 1 – Problem Awareness: Blog posts, industry benchmark reports, problem-framing one-pagers by role.
- Moment 2 – Solution Exploration: Demo decks, use-case videos, feature comparison sheets by role.
- Moment 3 – Requirements Building: Technical documentation, security packs, integration guides, RFP response templates.
- Moment 4 – Vendor Evaluation: Competitive battle cards, customer case studies by vertical, ROI calculators.
- Moment 5 – Decision and Consensus: Champion decks, business case one-pagers, mutual action plans, pricing one-pagers for finance.
Actions to implement the taxonomy:
- Rebuild the shared drive or CMS folder structure using the five moments as top-level folders.
- Create subfolders by role within each moment folder.
- Apply the four mandatory metadata tags to every asset file name and CMS record.
- Create a one-page “asset retrieval guide” for reps that maps common deal scenarios to the correct folder path.
Example: A rep preparing for a vendor evaluation call with a CFO navigates to Moment 4, then Economic Buyer, then the relevant vertical, and retrieves the ROI calculator and a named case study in under a minute.
Tip: Digital sales rooms act as a shared, centralized hub that holds the narrative, with every asset curated and organized by deal stage and buyer interest, which lets prospects explore on their own time. Teams with the right infrastructure can create a digital sales room per account that mirrors this taxonomy at the deal level.
Step 6: Tie Asset Usage to Revenue Outcomes
Objective: Connect asset usage data to win rates, deal velocity, and influenced pipeline value in the CRM.
Three primary success metrics govern this step:
- Asset usage rate: Percentage of active deals in which a scored asset was sent or accessed.
- Win-rate lift: Difference in close rate between deals where a specific asset was used and deals where it was not.
- Influenced pipeline value: Total ARR of opportunities where a scored asset appeared at any stage.
Actions to collect and report this data:
- Add a custom field to every CRM opportunity record called “Assets Used,” set as multi-select and mapped to the library taxonomy.
- Train reps to log asset usage at the time of sending instead of logging it retroactively.
- Build a Looker Studio or HubSpot dashboard that cross-references asset usage fields with opportunity stage, close date, and closed-won ARR.
- Run a quarterly review that compares win rates on deals with high-scoring assets, in the 7 to 9 range, against deals with unscored or low-scoring assets.
Attribution challenge and mitigation: Multi-touch attribution in B2B is imprecise because buyers spend most of their evaluation time in internal meetings and independent research instead of vendor calls, so much asset consumption happens outside tracked channels. Mitigate this by using influenced pipeline as the primary metric instead of sourced pipeline, and by collecting self-reported asset usage from champions during discovery calls.
Example: After one quarter, the CFO payback period summary with a score of 8 appears in 74% of closed-won deals above $50K ARR and only 31% of closed-lost deals. The team responds by distributing this asset earlier in the vendor evaluation stage for all enterprise opportunities.
Advanced Variations for Mature Teams
Teams with a functioning scored library can extend the system in two directions.
A/B testing asset versions: For high-volume deal stages, create two versions of the same asset that vary the headline, evidence type, or CTA, and then track win-rate lift by version using CRM custom fields. Companies with regularly updated battle cards often win competitive deals at higher rates than companies with outdated or missing battle cards, and the same testing discipline applies to all asset categories.
Quarterly content governance: Integrate the 9-point scoring rubric into a formal quarterly audit. Re-score every asset in the active library, review usage data, and retire or rebuild assets that score below 4. This cadence prevents library decay and keeps the system aligned with shifting competitive positioning.
SaaS Hero also applies this framework to competitor conquesting landing pages and conversion rate optimization programs. These extensions give teams two additional levers when they are ready to apply buyer-task mapping beyond the collateral library into paid media and site experience.
Checklist Recap and Tiered Next Steps
Six-step checklist:
- Buying job inventory completed from buyer interviews and CRM data.
- Five-question rubric documented and embedded in the asset creation workflow.
- Persona-by-stage matrix built with role-specific asset types assigned.
- All existing assets scored on the 9-point rubric, with low scorers retired or queued for revision.
- Library reorganized by moment with four mandatory metadata tags applied.
- CRM custom fields live, with a Looker Studio or HubSpot dashboard tracking usage-to-revenue metrics.
Tiered next steps by team maturity:
- Early stage (no formal collateral system): Start with Steps 1 and 2. Build the buying job inventory and five-question rubric before creating new assets, and hold off on production until the matrix in Step 3 is drafted.
- Mid-maturity (existing library, low usage): Run the Step 4 scoring audit immediately. Retire low-scoring assets before reorganizing the library. Usage rates often improve within one quarter once clutter is removed.
- Advanced (library exists, usage tracked but not tied to revenue): Prioritize Step 6. Add CRM custom fields and build the influenced pipeline dashboard. The scoring rubric and moment taxonomy already exist, and revenue attribution becomes the missing link.
Frequently Asked Questions
How long does it take to build a buyer-task-driven collateral system from scratch?
Most Series B to C B2B SaaS teams complete the full six-step system in four to six weeks. Steps 1 and 2, which cover buying job mapping and rubric definition, take one to two weeks and require access to call recordings, CRM data, and eight to twelve buyer interviews. Steps 3 and 4, which cover the persona-by-stage matrix and scoring audit, take one to two weeks depending on the size of the existing library. Steps 5 and 6, which cover library reorganization and CRM instrumentation, take about one week each. Teams with larger libraries or more complex buying committees with ten or more stakeholders should plan for the full six weeks, then begin the quarterly governance cadence after the initial build.
Which cross-functional roles need to be involved?
At minimum, three functions must participate. Marketing owns asset creation, rubric enforcement, and library governance. Sales contributes buyer interview data, validates the buying job inventory, and logs asset usage in the CRM. RevOps builds and maintains the CRM custom fields, the attribution dashboard, and the quarterly reporting cadence. Teams with a dedicated sales enablement function typically assign that role to own the moment taxonomy and rep training on asset retrieval. Finance or a CFO stakeholder should review the influenced pipeline dashboard design to confirm that metrics align with board-level reporting requirements.
How does this system adapt for smaller teams with limited content resources?
Smaller teams should focus on depth over breadth. Instead of building assets for every cell in the persona-by-stage matrix, identify the two or three buying jobs where deals most frequently stall, often the champion’s internal selling job and the economic buyer’s financial justification job, and build scored assets for those jobs first. A single high-scoring champion deck and a CFO-specific ROI one-pager usually produce more measurable win-rate lift than a broad library of low-scoring generic assets. The five-question rubric and 9-point scoring system stay the same regardless of team size, and only the number of populated cells in the matrix changes.
What are the most common risks and how are they mitigated?
Three risks appear most often. First, rep adoption failure occurs when reps revert to existing assets because the new library feels harder to navigate than the old one. Mitigate this by building the asset retrieval guide in Step 5 and training reps with deal-scenario walkthroughs instead of generic library tours. Second, evidence gaps appear when teams cannot answer the evidence question in the five-question rubric because customer results have not been documented. Mitigate this by running a parallel customer success interview program to collect named outcomes before the library build begins. Third, attribution gaps arise when asset usage is logged inconsistently in the CRM, which produces unreliable win-rate data. Mitigate this by making the “Assets Used” CRM field a required field for opportunity stage advancement instead of an optional log.
How often should the system be updated after the initial build?
The buying job inventory and persona-by-stage matrix should be reviewed quarterly, in sync with the content governance audit. Battle cards and competitive assets require a thirty-day review cycle because competitive positioning shifts faster than other content categories. The 9-point scoring rubric itself should be reviewed annually or when a significant product change, pricing change, or ICP shift occurs. The CRM dashboard and attribution model should be validated each quarter against closed-won data to confirm that the influenced pipeline metric still reflects asset impact accurately. Teams that skip quarterly reviews usually see library decay within two quarters, with low-scoring assets re-entering the active library and usage rates declining.