IMI Pitch Intelligence Framework

This skill teaches the AI to build pitches, proposals, and RFP responses that win business

the IMI way — with proof points, not platitudes; with specificity, not generalities; and

with a clear answer to "why should I choose IMI over anyone else?"

The IMI Pitch Philosophy

Clients don't buy research. They buy confidence in a decision.

Every IMI pitch must answer three questions in this order:

• What is your problem? (Show you understand their specific challenge)
• How will IMI solve it? (Specific methodology, not generic capabilities)
• Why should you trust IMI? (Proof points from similar work)

The cardinal sin: A generic capabilities deck that could be from any research agency.

IMI pitches are bespoke — tailored to the prospect's industry, challenge, and decision.

The Pitch Construction Framework

Stage 1: Prospect Intelligence

Before writing a single slide, gather intelligence:

PROSPECT RESEARCH CHECKLIST:
□ Industry and category — what are the macro trends?
□ Brand position — market leader, challenger, newcomer?
□ Recent news — product launches, campaigns, executive changes, earnings?
□ Public data — brand rankings, NPS benchmarks, market share data?
□ Known challenges — category disruption, competitor threats, consumer shifts?
□ Current research provider — who are we displacing and why might they switch?
□ Decision-maker profile — CMO? Insights Director? What do they value?
□ Budget signals — size of organisation, research maturity level?

Stage 2: Problem Framing

The most powerful pitches START with the prospect's problem, not with IMI's capabilities.

The Problem Frame structure:

## [Prospect] faces a [specific challenge]

[Industry context — 1-2 sentences showing you understand the landscape]

[The specific problem — what keeps the decision-maker up at night]

[What this costs them — quantified if possible, in terms of revenue, growth, or risk]

[The question they need answered — framed as a business decision, not a research question]

Example:

## [QSR Brand] is losing Gen Z consideration in a category they once owned

Quick-service dining among 18-27s is fragmenting — delivery apps and ghost kitchens
have created 300% more options in the last 5 years.

[Brand]'s consideration among Gen Z dropped from 65% to 48% between 2023 and 2025,
while two challenger brands grew from 12% to 31% combined.

At current trajectory, [Brand] risks losing $X million in annual revenue from the
cohort that will define the next decade of category growth.

The question: What do Gen Z consumers actually want from QSR, and how can [Brand]
reclaim relevance without alienating its existing audience?

Stage 3: The IMI Solution

Present a specific methodology, not a menu of capabilities.

Solution structure:

## How IMI Would Solve This

### Phase 1: Discover — [specific deliverable]
[What we'd do, what data we'd use, what the output would be]
Timeline: [X weeks] | Investment: [range]

### Phase 2: Confirm — [specific deliverable]
[What we'd test, how, against what benchmarks]
Timeline: [X weeks] | Investment: [range]

### Phase 3: Optimize — [specific deliverable]
[How we'd track impact and feed learnings back]
Timeline: [ongoing] | Investment: [range]

Key principle: Map every phase to IMI's three pillars. This shows methodology, not

just activity.

Stage 4: Proof Points

The proof point selection framework:

Select case studies based on three criteria (in order of importance):

• Industry match — Same industry as the prospect (strongest signal)
• Problem match — Same type of business challenge (even if different industry)
• Outcome match — Demonstrates the type of result the prospect wants

Proof point structure:

### [Client Industry] — [Headline Result]
**Challenge:** [1 sentence — what the client faced]
**Approach:** [1 sentence — what IMI did]
**Result:** [1 sentence — quantified outcome]
**Relevance to [Prospect]:** [1 sentence — why this matters for them]

Rules:

• Maximum 3 proof points per pitch (more dilutes impact)
• At least one must be from the same industry
• At least one must demonstrate ROI or quantified impact
• Never use a proof point without explaining its relevance to THIS prospect

Stage 5: The "Why IMI" Positioning

IMI's differentiators (deploy selectively based on what the prospect values):

Stage 6: Investment Case

The ROI argument for research investment:

Cost of Wrong Decision = (Revenue at Risk) × (Probability of Wrong Decision Without Research)
Cost of Research = IMI Investment
ROI of Research = (Cost of Wrong Decision Avoided - Cost of Research) / Cost of Research

Example:
  Campaign budget: $5M
  Probability of underperforming campaign without testing: 40% (industry average)
  Cost of underperformance: $2M in wasted spend (40% × $5M)
  Cost of concept testing: $80K
  ROI = ($2M - $80K) / $80K = 24:1

The "insurance" framing: Research is not a cost — it is insurance against making

expensive mistakes. Frame the investment relative to the decision it protects.

RFP Response Strategy

RFP Scoring Framework

When responding to an RFP, score each requirement and prioritise:

RFP Response Structure

## [RFP Title] — IMI's Response

### Understanding of the Brief
[Restate the client's challenge in your words — show you GET IT]

### Our Approach
[Specific methodology — Phase 1/2/3 mapped to Discover/Confirm/Optimize]

### Why IMI
[3 differentiators, each with evidence, tailored to this RFP]

### Relevant Experience
[3 proof points, selected by industry + problem + outcome match]

### Team
[Named individuals with relevant experience]

### Investment & Timeline
[Phased pricing with clear deliverables per phase]

### Guarantee
[IMI's refund guarantee — if we don't meet the agreed objective, full refund]

Cross-Sell Proposal Framework

For existing clients — expanding the relationship:

CROSS-SELL TRIGGER IDENTIFICATION:
1. Client mentions a challenge outside current scope → open door
2. Data from current project reveals an adjacent opportunity → proof-based cross-sell
3. Seasonal/calendar trigger → category event coming up
4. Competitive threat → "your competitor just did X, here's how to respond"
5. Team expansion at client → new stakeholder, new needs

The proof-based cross-sell is the strongest. When current research reveals that the client

has an adjacent problem, the cross-sell writes itself:

## Opportunity: [Adjacent Capability]

### What Your Current Research Revealed
[Specific finding from their existing IMI work that points to an adjacent need]

### The Implication
[What this means for their business if unaddressed]

### What We'd Recommend
[Specific IMI capability to address it, with timeline and investment range]

### The Value
[Expected ROI or risk mitigated]

Industry-Specific Value Propositions

CPG / FMCG

• Emphasis: Category management, shelf strategy, promotion optimisation
• Key Pulse™ angle: Consumer passion points driving category choice
• Proof point priority: ROI metrics, promotional effectiveness

Financial Services

• Emphasis: Trust, regulation compliance, digital transformation
• Key Pulse™ angle: Values-based segmentation, financial wellbeing attitudes
• Proof point priority: Trust-building case studies

Sports & Entertainment

• Emphasis: Sponsorship strategy, fan engagement, experiential ROI
• Key Pulse™ angle: Passion point alignment, audience fit
• Proof point priority: Sponsorship valuation, WOM multiplier results

Life Sciences / Healthcare

• Emphasis: Patient journey, HCP engagement, regulatory-compliant messaging
• Key Pulse™ angle: Health attitudes, wellness passion points
• Proof point priority: Behaviour change outcomes

Lottery & Gaming

• Emphasis: Player segmentation, responsible gaming, Newcomers
• Key Pulse™ angle: Entertainment passion points, occasion-based play
• Proof point priority: Newcomer acquisition, player retention

Output Templates

Template: Pitch Deck Outline

## Pitch: [Prospect Name]

### Slide 1: Title
[Prospect name] × IMI — [one-line value proposition]

### Slide 2: The Challenge
[Prospect's specific problem, quantified]

### Slide 3: What's At Stake
[Cost of inaction — revenue risk, competitive threat]

### Slide 4: Our Approach
[Phase 1: Discover | Phase 2: Confirm | Phase 3: Optimize]

### Slide 5: Proof Point 1
[Same-industry case study with result]

### Slide 6: Proof Point 2
[Same-problem case study with result]

### Slide 7: Why IMI
[3 differentiators tailored to this prospect]

### Slide 8: Investment & Timeline
[Phased pricing, clear deliverables]

### Slide 9: The IMI Guarantee
[Refund guarantee — confidence in our work]

### Slide 10: Next Steps
[Specific proposed action]

Common Pitfalls

• Leading with IMI's history. "Founded in 1971, IMI has served 200+ clients..." is

background, not a pitch. Lead with the prospect's problem.

• Generic capabilities presentation. If you could swap the prospect's name for any

other company and the pitch still works, it's not specific enough.

• Too many proof points. Three strong, relevant proof points beat ten generic ones.

• Forgetting the ROI case. Every pitch must answer "what will this cost me and what

will I get back?" If you can't frame the investment case, the pitch will stall at procurement.

• Not tailoring "Why IMI" to the prospect. The refund guarantee matters to risk-averse

clients. Pulse™ data matters to insight-hungry clients. Normative benchmarks matter to

companies that need category context. Pick the right differentiators.

Cross-Skill References

• For Pulse™ data as proof points → imi-pulse-intelligence
• For brand strategy frameworks in pitches → imi-brand-strategy
• For campaign evaluation capabilities → imi-campaign-evaluation
• For sponsorship capabilities → imi-sponsorship-intelligence
• For deliverable standards in proposals → imi-client-deliverable

*Built for IMI International's Local AI — grounded in IMI's commercial methodology and

50+ years of winning trust from 200+ client partners across 45 countries.*

*Purpose: Insight. Method: Rigour. Outcome: Profit.*

AXE MCP Server Integration

Every skill in the AXE Skills Hub runs with access to the AXE MCP Server — giving it the full fleet intelligence toolkit automatically. No setup required; tools are available in any AXE-powered session.

Core Tools Available

Quick Start

# In any AXE session, tools are pre-loaded. Example chaining:

# 1. Search for context
results = qdrant_search("user query here", collection="axe_persistent_memory")

# 2. Fetch live data if needed
content = web_fetch("https://docs.example.com/api")

# 3. Write result to memory for next session
write_memory("shared/last_result.md", output)

# 4. Log quality output to Edge training pipeline
hydra_add(prompt=user_query, response=output, score=0.9, source="skill-name")

Edge Training Integration

High-quality skill outputs are automatically eligible for Edge model training via hydra_add. When a response scores ≥0.85 in evals, pipe it to the Hydra pipeline to compound Edge's knowledge. This is how skills make Edge smarter over time.

# After generating a high-quality response:
hydra_add(
    prompt=user_input,
    response=final_output,
    score=0.9,          # eval score
    source="skill-name" # tracks provenance
)