What is the PIVO Framework?
PIVO is a prompt engineering framework built around four components: Problem, Insights, Voice, and Outcome. It bridges strategic thinking and brand expression — combining the "why" (Problem and Insights) with the "how it should sound" (Voice) and "what you need" (Outcome).
- P — Problem: Define the Challenge
- I — Insights: Bring Your Knowledge
- V — Voice: Specify the Brand or Communication Style
- O — Outcome: State the Desired Result
The Insights component is what makes PIVO distinctive. Rather than asking the AI to generate content from scratch, PIVO requires you to bring relevant data, research, or observations into the prompt. The AI's job is then to synthesise those insights into content that carries your brand voice and achieves a specific outcome — not to invent the intellectual substance from nothing.
This makes PIVO especially powerful for thought leadership, content strategy, and brand communications where the credibility of the content depends on real knowledge being woven into it.
When to Use the PIVO Framework
Thought Leadership
Turn proprietary data, client observations, and hard-won expertise into published articles, LinkedIn posts, and keynote narratives that establish genuine authority.
Brand Communications
Ensure every communication — from press releases to customer emails — reflects both the strategic context and the specific voice that defines your brand.
Content Strategy
Build content strategies grounded in audience insights and competitive data, then specify the voice and outcomes so all content is strategically aligned from the start.
Product Launches
Frame the launch around the real problem it solves, leverage customer research insights, and ensure messaging carries a consistent voice across all launch assets.
Client-Facing Reports
Produce consulting reports, agency proposals, and client strategy documents that reflect both deep knowledge and a professional, relationship-aware voice.
Executive Ghostwriting
Capture an executive's point of view, blend in supporting data, and produce polished speeches, articles, and social content that authentically represent their voice.
How to Use the PIVO Framework
- P
Problem — Define the Challenge
State the specific problem you are trying to solve. This is not the content brief — it is the underlying business or communication challenge that motivated the task. Being precise about the Problem helps the AI understand the stakes and ensures the output is genuinely useful rather than generically relevant.
- I
Insights — Bring Your Knowledge
Share the relevant data points, research findings, customer feedback, or competitive observations that should inform the output. These are the intellectual inputs — what you know that the AI should weave into its response. The richer your Insights, the more original and credible the output will be.
- V
Voice — Specify the Brand or Communication Style
Describe how the output should sound. Include tone adjectives, reference brands or publications as style benchmarks, note what to avoid, and describe the relationship the voice suggests (peer, expert advisor, mentor). Voice guidance prevents generic, corporate-sounding output and ensures brand consistency.
- O
Outcome — State the Desired Result
Describe the specific deliverable and what it should achieve. Include format, length, sections, and any structural requirements. The Outcome is both the deliverable spec and the success criterion — what does this content need to accomplish for the audience?
Prompt Examples
Problem: Our SaaS product has strong retention among power users but struggles to convert free trial users to paid plans. Trial-to-paid conversion sits at 4.2% against an industry benchmark of 8–12%. Exit surveys show users understand the product's features but don't see the immediate value for their specific workflow. Insights: - Users who complete the guided onboarding flow convert at 11.8% (3x the average) - The most common trial action is importing data; users who import and run one report convert at 9.4% - "Aha moment" data shows users who reach their first insight within 48 hours are 6x more likely to convert - Competitor analysis: top competitors lead with use-case-specific landing pages and personalised onboarding tracks Voice: Authoritative but approachable — we are a trusted data partner, not a pushy vendor. Copy should feel like advice from a knowledgeable colleague, not a sales deck. We avoid urgency tactics, discounts, and fear-based messaging. Outcome: A complete content strategy for improving trial-to-paid conversion, including: a revised onboarding email sequence (5 emails), two LinkedIn thought leadership article outlines positioned around the insights above, and messaging guidelines for the in-app upgrade prompt at the moment users run their first report.
Problem: Our B2B consultancy is invisible in a crowded market. We have 12 years of client results, but no consistent point of view that differentiates us from generalist strategy firms. Senior partners are reluctant to publish because they fear sharing proprietary thinking. Insights: - Our best client outcomes share a pattern: we challenge the client's initial problem framing before proposing solutions (we call this "reframe before resolve") - 78% of our project work starts with a client coming to us with the wrong problem - Industry publications consistently undercover the cost of misdiagnosed business problems — there is a clear editorial gap we can own - Three clients have publicly credited our reframing approach in case studies but we have never built content around it Voice: Intellectually rigorous, direct, and occasionally contrarian. We write like McKinsey but speak like a trusted advisor at dinner — formal enough to be credible, human enough to be memorable. No jargon without definition. No filler. Every sentence earns its place. Outcome: A thought leadership platform brief including: 1. A core point-of-view statement (2–3 sentences) we can use across all content 2. Three flagship article concepts with working titles and argument outlines 3. A LinkedIn content calendar for one quarter (12 posts, weekly cadence) 4. Guidance on how partners can contribute without feeling exposed
Pros and Cons
| 🟢 Pros | 🔴 Cons |
|---|---|
| Insights component produces content grounded in real knowledge, not AI invention | Requires genuine insights to bring — outputs suffer if the Insights section is thin |
| Voice specification ensures consistent brand tone across all outputs | More demanding upfront preparation than simpler frameworks |
| Strong framework for thought leadership, strategy, and high-value communications | Less suited for tactical, transactional, or data-processing tasks |
| Problem framing focuses the AI on what actually matters, not surface-level execution |
Frequently Asked Questions
What does PIVO stand for?
PIVO stands for Problem, Insights, Voice, and Outcome. Problem defines the challenge to solve, Insights bring in relevant data and knowledge that should inform the response, Voice specifies the brand or communication style, and Outcome describes the desired result or deliverable.
When should I use the PIVO framework?
Use PIVO for content strategy, brand communications, thought leadership, and any task where both the reasoning behind the content and the voice it should be written in are important. PIVO is particularly strong when you have data or research that should shape the output but also have clear brand or tone requirements.
What makes PIVO different from other content frameworks?
PIVO uniquely combines strategic reasoning (Problem and Insights) with brand expression (Voice and Outcome). Most frameworks focus on either instructions or persona, but PIVO treats the insight layer as essential input — the AI must understand not just what to produce, but what knowledge should be woven into it and what tone it must carry.
How specific should the Voice component be?
The more specific, the better. Instead of 'professional tone', describe the voice in terms of how it feels: 'like a trusted advisor at dinner — formal enough to be credible, human enough to be memorable'. You can also reference a publication, author, or brand as a benchmark. The goal is to give the AI enough texture to make consistent style decisions.
What belongs in the Insights section?
Insights should contain data points, research findings, customer feedback, competitive observations, or any knowledge that should actively shape the content. These are not background context — they are the intellectual raw material the AI should weave into the output. Think of it as briefing the AI on what you know before asking it to write.
Can PIVO be used for social media content?
Yes — PIVO works well for social media, especially for brand accounts with a distinct voice and a point of view to communicate. The Insights component ensures posts are grounded in real data rather than generic platitudes, and the Voice component ensures consistency across different writers or AI-generated drafts.
How does PIVO compare to the DEEP framework?
Both PIVO and DEEP address brand voice and direction. PIVO leads with the strategic Problem and Insights, making it stronger for thought leadership and content strategy where the 'why' matters. DEEP focuses more on the writing execution — Direction, Existing Info, Expertise, Preferred Tone — making it a better fit for individual content pieces where the strategy is already set.