research-to-action-bridge

# Research-to-Action Bridge

This skill transforms market research insights into concrete, actionable recommendations that product, marketing, and strategy teams can execute immediately.

## Purpose

The traditional gap between "what we learned" and "what we do" costs companies months of delay and diluted insights. According to Foundation Capital's research thesis, the future of market research involves always-on research agents that serve as "feedback engines" for domain agents across the organization.

This skill bridges that gap by:

- Converting research findings into prioritized action items
- Generating ready-to-use briefs for product, marketing, and strategy teams
- Recommending specific next steps with clear ownership
- Creating feedback loops that trigger new research when needed
- Ensuring insights don't die in slide decks

## When to Use This Skill

Use this skill when:

- Research analysis is complete and needs to drive decisions
- Stakeholders need clear "so what" from research findings
- Product teams need feature prioritization from user insights
- Marketing teams need campaign briefs from customer research
- Positioning or messaging needs refinement based on feedback
- Pricing strategy needs adjustment from willingness-to-pay data
- Go-to-market planning requires customer segment insights

## Action Generation Framework

### The Insight-to-Action Pipeline

```
RESEARCH INSIGHT
     ↓
STRATEGIC IMPLICATION
(What does this mean for the business?)
     ↓
ACTION DOMAIN
(Who needs to act on this?)
     ↓
SPECIFIC RECOMMENDATION
(What exactly should they do?)
     ↓
SUCCESS METRIC
(How will we know it worked?)
     ↓
FEEDBACK TRIGGER
(When should we re-research?)
```

### Action Domains

Research insights typically drive action in these domains:

```
PRODUCT ACTIONS:
- Feature prioritization
- UX/UI improvements
- Roadmap adjustments
- Technical requirements
- Integration priorities

MARKETING ACTIONS:
- Messaging and positioning
- Campaign concepts
- Channel strategy
- Content themes
- Brand voice refinement

SALES ACTIONS:
- Value proposition updates
- Objection handling guides
- Segment targeting
- Pricing presentation
- Competitive positioning

STRATEGY ACTIONS:
- Market entry decisions
- Segment prioritization
- Partnership opportunities
- Investment allocation
- Risk mitigation

CUSTOMER SUCCESS ACTIONS:
- Onboarding improvements
- Support documentation
- Churn prevention triggers
- Expansion opportunities
- Advocacy programs
```

## Output Templates

### 1. Product Roadmap Input

When research reveals product opportunities or issues:

```
PRODUCT ROADMAP RECOMMENDATION

INSIGHT SUMMARY:
[1-2 sentence finding from research]

SUPPORTING DATA:
- [Key metric or quote]
- [Key metric or quote]

RECOMMENDED ACTION:
[Specific product change or feature]

PRIORITY RATIONALE:
Impact: [High/Medium/Low] - [Why]
Urgency: [High/Medium/Low] - [Why]
Effort Estimate: [High/Medium/Low] - [Rough assessment]

SUGGESTED ACCEPTANCE CRITERIA:
- [What would success look like]
- [Measurable outcome]

USER STORIES:
As a [persona], I want [capability] so that [benefit].

RISKS IF NOT ADDRESSED:
- [What happens if we don't act]

VALIDATION APPROACH:
[How to verify this works - may trigger new research]
```

**Example:**

```
PRODUCT ROADMAP RECOMMENDATION

INSIGHT SUMMARY:
72% of personas cited "report builder complexity" as primary
frustration during Days 7-30 of onboarding, correlating with
the observed NPS dip at Day 30.

SUPPORTING DATA:
- "I watched two tutorial videos and still couldn't figure out
  how to add a comparison column." - Jennifer, Marketing Director
- 8 of 20 personas (40%) mentioned report builder specifically
- Day 30 NPS dropped to +5 from Day 1's +30

RECOMMENDED ACTION:
Implement guided report builder wizard with templates for
common use cases (monthly performance, campaign comparison,
executive summary).

PRIORITY RATIONALE:
Impact: HIGH - Directly addresses primary pain point
Urgency: HIGH - Causing measurable satisfaction drop
Effort Estimate: MEDIUM - Template system + wizard UI

SUGGESTED ACCEPTANCE CRITERIA:
- First-time users can create comparison report in <5 minutes
- Template usage reduces support tickets by 30%
- Day 30 NPS improves to +20 or higher

USER STORIES:
As a Marketing Director with limited time, I want pre-built
report templates so that I can generate board-ready reports
without learning complex builder features.

RISKS IF NOT ADDRESSED:
- Continued NPS dip at Day 30
- Workaround behavior (export to Excel) reduces product value
- Negative word-of-mouth focused on "steep learning curve"

VALIDATION APPROACH:
Run longitudinal check-in study with new cohort post-launch
to verify Day 30 NPS improvement.
```

### 2. Marketing Campaign Brief

When research reveals messaging, positioning, or campaign opportunities:

```
MARKETING CAMPAIGN BRIEF

CAMPAIGN OBJECTIVE:
[What marketing outcome we're targeting]

RESEARCH FOUNDATION:
[Key insights driving this brief]

TARGET AUDIENCE:
Primary: [Segment with key characteristics]
Secondary: [Segment with key characteristics]

KEY MESSAGE:
[Core message that resonated in research]

PROOF POINTS:
- [Supporting claim 1]
- [Supporting claim 2]
- [Supporting claim 3]

MESSAGING DO'S:
- [Language/framing that worked]
- [Emotional triggers that resonated]

MESSAGING DON'TS:
- [Language/framing that failed]
- [Triggers to avoid]

RECOMMENDED CHANNELS:
[Based on persona media consumption data]

TONE AND VOICE:
[Based on communication style preferences]

CREATIVE CONSIDERATIONS:
[Visual or format preferences from research]

SUCCESS METRICS:
- [KPI 1]
- [KPI 2]

A/B TEST RECOMMENDATIONS:
[Variations to test based on segment differences]
```

**Example:**

```
MARKETING CAMPAIGN BRIEF

CAMPAIGN OBJECTIVE:
Launch campaign for eco-friendly cleaning product targeting
Gen Z consumers, optimizing for brand awareness and trial.

RESEARCH FOUNDATION:
- Tagline B ("The Last Cleaning Product You'll Feel Guilty About")
  rated 7/10 by target persona, significantly outperforming
  generic sustainability messaging
- 36% cited environmental concerns as purchase barrier
- Personas responded negatively to "greenwashing" signals

TARGET AUDIENCE:
Primary: Eco-conscious Gen Z (ages 18-26), urban, values
authenticity and transparency, skeptical of corporate
sustainability claims, influenced by peer recommendations
and TikTok content creators.

Secondary: Millennial parents concerned about chemical
exposure and environmental legacy for children.

KEY MESSAGE:
"Honest sustainability you can actually verify"
(Combines guilt acknowledgment with transparency commitment)

PROOF POINTS:
- Specific certifications (name them)
- Supply chain transparency (show the journey)
- Packaging breakdown (what happens after disposal)

MESSAGING DO'S:
- Acknowledge the guilt/frustration with current options
- Provide specific, verifiable claims
- Show real-world impact metrics
- Use casual, peer-to-peer tone
- Feature authentic user content

MESSAGING DON'TS:
- Generic "clean planet" language (rated 4/10)
- Puns or "clever" wordplay (perceived as trying too hard)
- Vague sustainability claims without specifics
- Polished corporate aesthetic (triggers skepticism)

RECOMMENDED CHANNELS:
- TikTok (primary reach + authenticity signals)
- Instagram (visual storytelling for supply chain)
- Influencer seeding (micro-influencers preferred over celebrities)

TONE AND VOICE:
Casual, honest, self-aware. Can acknowledge imperfection.
"We're not perfect, but here's exactly what we're doing."

CREATIVE CONSIDERATIONS:
- Unpolished, documentary-style content preferred
- Show the "receipts" (certifications, supply chain footage)
- Feature real team members, not actors
- Vertical video format for social

SUCCESS METRICS:
- Aided brand awareness in target demo: +15%
- Social engagement rate: >5%
- Trial conversion from campaign landing page: >3%

A/B TEST RECOMMENDATIONS:
- Test guilt-forward vs. empowerment messaging
- Test certifications prominent vs. story-first approach
- Test user-generated vs. brand-produced content
```

### 3. Sales Enablement Update

When research reveals objection patterns or value perception issues:

```
SALES ENABLEMENT UPDATE

INSIGHT SOURCE:
[Research study and date]

OBJECTION PATTERN IDENTIFIED:
[What prospects are saying/asking]

PREVALENCE:
[How common - % of personas who raised this]

ROOT CAUSE ANALYSIS:
[Why this objection exists]

RECOMMENDED RESPONSE:
[How to address it]

SUPPORTING PROOF:
[Evidence to share with prospects]

TALK TRACK:
"[Specific language to use]"

MATERIALS NEEDED:
[Collateral to create or update]

COMPETITIVE CONTEXT:
[How competitors handle this - if relevant]

ESCALATION TRIGGER:
[When to involve solutions engineer/executive]
```

**Example:**

```
SALES ENABLEMENT UPDATE

INSIGHT SOURCE:
B2B Analytics Platform Pricing Study, Jan 2026
(5-persona cohort representing mid-market buyers)

OBJECTION PATTERN IDENTIFIED:
"What happens to our data if we cancel?"

PREVALENCE:
Raised by "Budget Guardian" persona type - estimated 25-30%
of CFO/finance-led evaluations will ask this.

ROOT CAUSE ANALYSIS:
Finance personas have been burned by vendors who make data
extraction difficult or charge exit fees. They're protecting
against lock-in before committing budget.

RECOMMENDED RESPONSE:
Lead with data portability commitment BEFORE they ask.
Frame as "you own your data, always" positioning.

SUPPORTING PROOF:
- Export functionality demo (show 1-click full export)
- Data portability SLA in contract
- Customer reference who has exported successfully
- Competitive comparison on data portability

TALK TRACK:
"Before we go further, I want to address something that often
comes up with finance teams - data ownership. Your data is
yours, period. You can export everything - all historical data,
all reports, all configurations - with one click, anytime,
at no additional charge. We actually put that in writing in
our contract. Would it be helpful if I showed you exactly
how that works?"

MATERIALS NEEDED:
- One-pager: "Your Data, Your Control" for finance stakeholders
- Demo script: Data export walkthrough
- Contract excerpt highlighting portability clause

COMPETITIVE CONTEXT:
[Competitor X] charges exit fee and limits export to 90 days
of data. [Competitor Y] requires professional services
engagement for full export. Position our approach as
industry-leading transparency.

ESCALATION TRIGGER:
If prospect pushes on data deletion timelines or compliance
requirements (GDPR, CCPA), involve Solutions Engineer
for technical deep-dive.
```

### 4. Pricing Strategy Recommendation

When research reveals willingness-to-pay or value perception insights:

```
PRICING STRATEGY RECOMMENDATION

RESEARCH BASIS:
[Study details and methodology]

CURRENT PRICING:
[Existing price points]

FINDINGS SUMMARY:

Willingness to Pay by Segment:
| Segment | Ceiling | Sweet Spot | Floor |
|---------|---------|------------|-------|
| [Seg A] | $XX     | $XX        | $XX   |
| [Seg B] | $XX     | $XX        | $XX   |

Value Driver Analysis:
[What features/benefits drive willingness to pay]

Price Sensitivity Factors:
[What makes segments more/less price sensitive]

RECOMMENDATION:
[Specific pricing change or structure]

RATIONALE:
[Why this pricing will work]

SEGMENT STRATEGY:
[How to approach different segments]

RISK ASSESSMENT:
[Potential downsides and mitigations]

IMPLEMENTATION APPROACH:
[How to roll this out]

MONITORING PLAN:
[How to track if it's working]
```

### 5. Go-to-Market Segment Prioritization

When research reveals segment attractiveness insights:

```
GTM SEGMENT PRIORITIZATION

SEGMENTS EVALUATED:
[List segments studied]

EVALUATION CRITERIA:
- Purchase intent strength
- Barrier/objection density
- Price sensitivity
- Decision complexity
- Competitive intensity

SEGMENT SCORECARD:

| Segment | Intent | Barriers | Price Sens. | Complexity | Priority |
|---------|--------|----------|-------------|------------|----------|
| [Seg A] | XX%    | Low/Med/High | L/M/H | L/M/H | 1/2/3 |

PRIORITY 1: [Segment Name]
Why: [Rationale from research]
Go-to-Market Approach:
- Primary message: [What resonates]
- Primary channel: [Where to reach them]
- Key proof points: [What convinces them]
- Likely objections: [What to prepare for]
- Timeline to decision: [Typical cycle]

PRIORITY 2: [Segment Name]
[Same structure]

DEPRIORITIZED: [Segment Name]
Why: [Research-based rationale for not pursuing now]
Revisit Trigger: [What would change this]
```

### 6. Feedback Loop Trigger

When research identifies need for ongoing monitoring:

```
FEEDBACK LOOP SPECIFICATION

TRIGGER CONDITION:
[What event or change should trigger new research]

RESEARCH TYPE:
[What kind of research to conduct]

PERSONAS TO INCLUDE:
[Which personas/segments to study]

KEY QUESTIONS:
[What we need to learn]

SUCCESS INDICATOR:
[What would indicate positive outcome]

WARNING INDICATOR:
[What would indicate problem]

FREQUENCY:
[How often to check - if recurring]

AUTOMATION POTENTIAL:
[Can this be continuously monitored?]
```

**Example:**

```
FEEDBACK LOOP SPECIFICATION

TRIGGER CONDITION:
New report builder wizard ships to production

RESEARCH TYPE:
Longitudinal check-in study (Day 1, Day 7, Day 30)

PERSONAS TO INCLUDE:
New users matching "Marketing Director" and "Business Analyst"
profiles from original study

KEY QUESTIONS:
1. Can users create first report in <5 minutes?
2. Do users discover and use templates?
3. Does Day 30 NPS exceed +20?
4. What new friction points emerge?

SUCCESS INDICATOR:
- Time-to-first-report <5 min (vs. current ~15 min)
- Day 30 NPS ≥ +20 (vs. current +5)
- Support ticket volume for report builder ↓ 30%

WARNING INDICATOR:
- Time-to-first-report unchanged
- New confusion points in wizard flow
- Day 30 NPS does not improve

FREQUENCY:
Monthly for first 3 months post-launch, then quarterly

AUTOMATION POTENTIAL:
High - can monitor time-to-first-report via product analytics
Medium - NPS requires check-in surveys
Low - qualitative friction discovery requires interviews
```

## Integration Patterns

### Always-On Research Network Model

Based on Foundation Capital's vision, research-to-action operates as part of a continuous system:

```
CONTINUOUS INSIGHT-ACTION LOOP:

┌─────────────────────────────────────────────────────────┐
│                                                         │
│  ┌─────────────┐    ┌─────────────┐    ┌─────────────┐ │
│  │  Research   │───→│   Analyze   │───→│   Action    │ │
│  │   Agents    │    │   Agents    │    │   Agents    │ │
│  └─────────────┘    └─────────────┘    └─────────────┘ │
│        ↑                                      │         │
│        │                                      │         │
│        │         ┌─────────────┐             │         │
│        └─────────│  Feedback   │←────────────┘         │
│                  │   Triggers  │                       │
│                  └─────────────┘                       │
│                                                         │
└─────────────────────────────────────────────────────────┘
```

**Research Agents:** Create personas, conduct interviews, gather data
**Analyze Agents:** Extract patterns, quantify findings, generate reports
**Action Agents:** Convert insights to briefs, recommendations, decisions
**Feedback Triggers:** Monitor outcomes, detect signals, initiate new research

### Domain Agent Handoffs

Research actions feed specific domain agents:

```
PRODUCT DOMAIN:
Research Output → Product Roadmap Input
Owner: Product Manager / Product Agent
Artifact: Feature specification, user story, prioritization

MARKETING DOMAIN:
Research Output → Campaign Brief
Owner: Marketing Manager / Marketing Agent
Artifact: Creative brief, channel plan, message matrix

SALES DOMAIN:
Research Output → Enablement Update
Owner: Sales Enablement / Sales Agent
Artifact: Battlecard, objection guide, talk track

CUSTOMER SUCCESS DOMAIN:
Research Output → Experience Improvement
Owner: CS Manager / Success Agent
Artifact: Playbook update, intervention trigger, content gap
```

## Quality Standards

### Action Readiness Checklist

Before delivering recommendations, verify:

```
SPECIFICITY CHECK:
□ Action is concrete (not "improve messaging")
□ Owner is identified (not "the team")
□ Timeline is suggested (not "soon")
□ Success metric is defined (not "better")

EVIDENCE CHECK:
□ Research data supports recommendation
□ Confidence level is stated
□ Sample size is acknowledged
□ Limitations are noted

FEASIBILITY CHECK:
□ Action is within owner's control
□ Resources required are realistic
□ Dependencies are identified
□ Risks are assessed

FEEDBACK CHECK:
□ Validation approach is defined
□ Trigger for re-research is specified
□ Monitoring plan exists
```

### Confidence Tagging

Tag all recommendations with confidence level:

```
HIGH CONFIDENCE (Act Now):
- Strong consensus in research (>80%)
- Large sample size (20+ personas)
- Consistent with known market behavior
- Low risk if wrong

MEDIUM CONFIDENCE (Act with Monitoring):
- Moderate consensus (60-80%)
- Adequate sample (10-20 personas)
- Novel but plausible finding
- Moderate risk if wrong

LOW CONFIDENCE (Validate First):
- Split or polarized findings
- Small sample (<10 personas)
- Contradicts assumptions
- High risk if wrong
```

## Examples

### Example: Full Insight-to-Action Flow

**Research Finding:**
From 25-persona meal kit concept test, couples segment showed
56% top-2-box purchase intent (vs. 38% for singles and families),
driven primarily by "date night at home" use case.

**Strategic Implication:**
Couples represent highest-opportunity segment for initial
market entry, with differentiated motivation that can drive
distinct positioning.

**Actions Generated:**

**1. Product Action:**
```
Create "Date Night Box" SKU with:
- Two-portion sizing
- Elevated ingredient quality
- Wine pairing suggestions
- Ambient playlist QR code
- Premium packaging for gift potential

Priority: HIGH
Owner: Product Manager, New SKUs
Timeline: Q2 launch
Success Metric: 40% of couple-segment trials choose Date Night SKU
```

**2. Marketing Action:**
```
CAMPAIGN BRIEF: "Date Night, Delivered"

Target: Couples 28-45, dual-income, urban/suburban
Message: "Restaurant quality. Couch comfort."
Channels: Instagram, Pinterest (meal inspiration context)
Tone: Romantic but not cheesy; elevated but accessible

Priority: HIGH
Owner: Brand Marketing Lead
Timeline: Launch with SKU
Success Metric: 3% CTR, 25% landing page conversion
```

**3. Sales/Partnership Action:**
```
Pursue partnership with wine subscription services:
- Cross-promotion opportunity
- Shared customer segment
- Natural bundle potential

Priority: MEDIUM
Owner: BD Lead
Timeline: Exploratory Q1, execute Q2
Success Metric: Partnership signed with >100K subscriber base
```

**4. Feedback Loop:**
```
Trigger: Date Night Box ships
Research: 60-day check-in with early adopters
Questions:
- Did product meet "date night" expectation?
- Would they give as gift? Have they?
- What occasion triggered purchase?
- Repeat purchase intent?

Warning Signal: <30% repeat purchase intent
Success Signal: Organic gift-giving behavior
```

---

This skill closes the loop in the synthetic research workflow, ensuring insights don't die in reports but drive concrete action across the organization.