Research proposals win or lose on credibility and clarity. This template is designed for agencies pitching AI-moderated research to clients who may be unfamiliar with the methodology.
The most common failure mode in AI-moderated research proposals is over-explaining the technology. Clients don’t care how the AI works — they care what they will know afterward and how fast. Lead with the business problem, anchor to outcomes, and introduce the methodology only to the extent it justifies the speed and depth claims. This template is structured in that order.
Section 1: Executive Summary
Frame the business problem, not the research methodology. This is the section clients read in the first 90 seconds. If it describes research methodology instead of business stakes, you’ve already lost momentum.
The executive summary should answer three questions: What decision is the client trying to make? What do they currently not know that’s blocking that decision? What will this research deliver, and when?
Example language:
“[Client] needs to understand why brand consideration is declining in the 25-34 demographic before Q3 campaign planning. We propose a 100-interview brand perception study targeting lapsed and current customers, delivering actionable strategic recommendations within 5 business days.”
A strong executive summary is 100-150 words. It names the business problem, not the research category. It includes the output format and the timeline. It does not include methodology language — that belongs in Section 2.
What to avoid: “This proposal outlines a qualitative research program designed to explore consumer perceptions across key audience segments…” This is methodology-first framing. Start with the client’s problem, not your solution.
Section 2: Methodology Overview
Describe the methodology in client-friendly language. Two paragraphs: one on what the interviews are like for participants, one on why this produces better findings than alternatives.
Recommended language:
“Our research methodology uses structured depth interviews with adaptive probing. Each participant engages in a 30+ minute conversation where follow-up questions are calibrated to their specific responses, reaching 5-7 levels of motivational depth. This produces the same quality of insight as expert human moderation while enabling 100+ simultaneous conversations for statistically meaningful patterns.”
Key points to include in the methodology section:
- Interview depth (30+ minutes, not a 5-minute survey)
- Laddering methodology (5-7 levels, with example progression)
- Sample size advantage (100+ interviews vs. typical 15-25 in traditional qual)
- 98% participant satisfaction rate
- Non-leading question design
- 24/7 participant availability (removes scheduling constraints on fieldwork speed)
What clients worry about: The most common objection in methodology review is “will an AI miss nuance that a human moderator would catch?” Address it directly: the AI moderator runs 5-7 levels of probing depth on every response, which is more consistent laddering than most human moderators achieve under time pressure. The 98% participant satisfaction rate reflects interview quality, not novelty.
Length guidance: One to two paragraphs. Over-explaining the methodology signals that the agency is uncertain about it. If you need three paragraphs to make the methodology sound credible, the problem is the framing, not the length.
Section 3: Study Design
The study design section is where proposals win or lose on specificity. Vague objectives (“understand consumer perceptions of the brand”) make the proposal feel generic. Precise objectives (“identify which brand attributes drive consideration among 25-34 lapsed users versus current users”) make it feel tailored.
Customize per engagement, documenting:
- Research objectives: 3-5 specific questions the study answers, written as outcomes (“By the end of this study, we will know [X]”)
- Target audience: Demographics, behavioral criteria, and screening requirements. Include the screening question for the most important qualifier.
- Sample size with rationale: “100 interviews provides thematic saturation across four audience segments (25 per segment) and supports comparative analysis between them.” Size to the question, not to a default.
- Discussion guide overview: Core topics and phase structure, not the full guide. Clients do not need to see every probe.
- Analysis framework: How findings will be structured — by theme, by segment, by question type — so clients know what the deliverable will look like before they approve the study.
For the full discussion guide format reference, the agency concept testing discussion guide template provides the five-phase structure used in most concept validation studies. For competitive research, the agency competitive analysis discussion guide covers the three primary formats.
Section 4: Timeline
The timeline section is where AI-moderated research creates the most dramatic proposal differentiation. Traditional qualitative research — recruit 15-20 participants, schedule 60-minute human-moderated sessions, transcribe, analyze — takes 4-8 weeks. This timeline takes 5 business days.
| Day | Activity |
|---|---|
| Day 1 | Study design finalized, discussion guide approved, recruitment begins |
| Day 2-3 | Interviews conducted (100+ simultaneous) |
| Day 4 | Analysis and synthesis |
| Day 5 | Client deliverable and debrief |
How to present this: Clients who have worked with traditional qualitative research will not believe this timeline on first read. Anchor it to the mechanics: “Participant recruitment draws from a 4M+ panel that is pre-screened and available 24/7. Rather than scheduling sequential 60-minute sessions across 3-4 weeks, 100 participants complete their interviews simultaneously within a 24-hour field window. Analysis begins the moment fieldwork closes.” That explanation converts skepticism faster than just asserting the timeline.
Milestone ownership: Specify which milestones require client input (Day 1: approve discussion guide, approve screener) and which the agency owns independently (Day 2-4). This prevents the 5-day timeline from expanding because of approval delays.
What Should Every Research Proposal Include?
Beyond the six sections above, proposals that consistently win include three additional elements that most agencies leave out.
A risk table. A two-row table: “What could slow this down?” and “How we mitigate it.” Common entries: recruitment incidence rate below 20% (mitigation: build 15% buffer into participant invite volume), client approval delays (mitigation: 24-hour approval SLA per milestone). Clients read this section as evidence of operational maturity.
A sample finding. One anonymized finding from a previous similar study — paraphrased to protect client confidentiality — showing what the output looks like. This resolves the “what will I actually get?” question faster than any description can.
A retainer bridge. One paragraph at the end noting that this project can serve as a baseline for ongoing tracking, and that clients running quarterly or monthly studies through a retainer program typically reduce per-study cost by 20-30% through volume. This plants the retainer conversation before the project is even approved. Full retainer tier structures are covered in the agency research retainer pricing models guide.
Section 5: Pricing
Present 2-3 options (good/better/best). Never present a single price point — it removes the client’s ability to right-size the investment to their current need and reduces your ability to understand where they see value.
- Essential: 50 interviews, insight brief, $3,000-$5,000
- Standard: 100 interviews, strategic deck, segment analysis, $7,000-$12,000
- Comprehensive: 150+ interviews, multi-segment, competitive benchmarking, $12,000-$20,000
Anchoring the pricing: Per-interview cost ($25/audio on the User Intuition platform) is a compelling proof point for clients accustomed to traditional qual pricing, where effective per-interview cost often runs $300-$800 including moderator time, facility rental, and transcription. Present the per-interview economics explicitly if the client is quantitatively oriented. For clients focused on outcomes, present total investment relative to the business decision the research informs — a $12,000 study that informs a $2M campaign budget is a 0.6% research tax.
Section 6: Intelligence Hub Value
Close with the compounding value proposition. The Intelligence Hub is the mechanism by which a single project proposal becomes the foundation of an ongoing relationship.
Recommended language: “All findings are indexed in a searchable Intelligence Hub. Future studies build on this baseline, reducing exploratory time on follow-up research by 30-40% and enabling longitudinal tracking across quarters. Rather than starting each new study from zero, your team can query findings from this study as context for future projects — the research investment compounds rather than depreciating.”
This section should be short — three to four sentences. It is a seed for the retainer conversation, not a full proposal on its own. The goal is to end the proposal with the client thinking about future studies, not just evaluating the current one.
How Do You Win the Proposal Review?
Agency proposals for AI-moderated research win most often when they demonstrate three things simultaneously: operational credibility (you know how to run this study), speed advantage (you can deliver faster than alternatives), and strategic value (findings will inform a specific decision, not just answer a research question).
The most effective proposals run 8-12 pages. Longer proposals shift the client’s attention from evaluation to review burden. Structure them so the executive summary, methodology overview, and timeline are visible in the first four pages — if a CMO only reads four pages, those are the pages that determine whether they approve or decline. The study design, pricing, and Intelligence Hub sections reward clients who want depth, but should not be required reading for approval.
For the full consumer research for agencies guide and the how to build research retainer services playbook, see the companion resources.
Adapting This Template for Different Study Types
The six-section template above is designed for general-purpose research proposals. Three study types require specific adaptations.
Concept testing proposals: The methodology section should explain that the discussion guide moves through five phases — warm-up, unstructured reaction, relevance and need-state, credibility and barriers, comparative evaluation — and that the phased structure preserves the signal value of first impressions before guided probing begins. The full guide template is in the agency concept testing discussion guide template. In pricing, concept testing proposals often benefit from presenting a “concept battery” option — testing 2-3 concepts simultaneously using the same participant sample — which halves the per-concept cost.
Competitive analysis proposals: Frame the executive summary around a specific competitive threat or positioning question, not a generic “understand competitive landscape” objective. Clients approve competitive research faster when it is tied to an imminent business decision — a repositioning, a campaign launch, a new product entering the category. The methodology section for competitive proposals should specify which of the three formats is being deployed (decision journey reconstruction, switching analysis, or competitive perception mapping) and why that format fits the question. Full format descriptions are in the agency competitive analysis discussion guide.
Multi-market proposals: If the study spans multiple geographies, the timeline section expands to address market-specific recruitment and whether fieldwork runs in parallel or sequentially. On the User Intuition platform, parallel fieldwork across multiple markets is standard — 50 interviews in the US, 50 in Germany, and 50 in Brazil can field simultaneously with a single 24-hour window. The 50+ language support removes the typical multi-market timeline drag. Present this as a cost and speed advantage over traditional multi-market alternatives, which typically sequence markets and produce results 6-10 weeks apart.
What User Intuition gives the proposal to stand on
A proposal is only as credible as the delivery capability behind it, and the methodology and timeline sections of this template make specific promises — parallel multi-market fieldwork, a fixed turnaround window, a sample size large enough to segment. User Intuition is what lets an agency write those promises without hedging. It runs the interviews, recruits participants, and returns synthesized findings, so the timeline section can commit to 24 hours rather than the 6-10 week range a traditional multi-market study would force.
The proposal-specific advantage is that the platform’s economics make the three-option pricing structure defensible. Because the fieldwork cost is a known, flat per-interview figure, an agency can present a value, a recommended, and a scoped-down option that genuinely differ in research design rather than in margin gymnastics — and the multi-market clients this template addresses can be quoted parallel fieldwork across geographies and languages as a standard inclusion, not a custom surcharge. That turns the methodology section from a description of intent into a description of a capability the agency can demonstrate on request.
The strongest proposals invite that demonstration. Agencies can point a prospective client to how recurring studies accumulate into a customer intelligence hub, or offer a demo of a live study as part of the proposal review so the methodology section is something the buyer has watched run.
Proposal Quality Checklist
Before sending any AI-moderated research proposal, verify:
| Element | Check |
|---|---|
| Executive summary leads with business problem | Yes / No |
| Methodology section is under two paragraphs | Yes / No |
| Research objectives are written as outcomes (“we will know X”) | Yes / No |
| Timeline specifies client approval milestones | Yes / No |
| Three pricing options presented | Yes / No |
| Intelligence Hub paragraph closes the proposal | Yes / No |
| Per-interview cost or total investment is anchored to decision value | Yes / No |
| Sample size includes rationale (not just a number) | Yes / No |
Proposals that pass all eight checks consistently perform better in client review — not because of any one element, but because together they signal operational rigor. Clients evaluating multiple agency proposals can usually identify which ones were built from a template with genuine substance and which were assembled under time pressure. The goal of this template is to make the substantive version the default, not the exception.
An agency research proposal for AI-moderated studies is not a methodology document. It is a business case with a research solution attached. The most effective proposals are ones where a CMO who has never heard of AI moderation can read the first four pages and understand exactly what decision they are funding, what they will know afterward, and when it will be ready. The remaining pages — study design detail, full pricing breakdown, Intelligence Hub explanation — are for the research buyer who wants to validate the methodology before approving. Both readers need to be served by the same document, which is why the six-section structure sequences information from business stakes to operational detail, not the other way around.