The Challenge

The client had invested heavily in customer research over time, including segmentation, personas, and qualitative insight. However, these assets were static, quickly outdated, and difficult to use outside specialist research teams.

Key challenges included:

• Personas existed as documents, not decision tools

• Teams struggled to “bring customers to life” in day-to-day work

• Research insights were locked in reports rather than embedded in planning

• Running new research was slow and costly

• Growing interest in AI, but concerns around accuracy, governance, and misuse

The organisation wanted a way to make customer understanding accessible, interactive, and safe — without replacing real research or creating new risk.

The Goal

The objective was to design and build a set of interactive AI personas that would:

• Behave like real customers in interviews or workshops

• Reflect existing research and validated insight

• Be safe, bounded, and appropriate for business use

• Support exploration, hypothesis testing, and decision-making

• Complement — not replace — traditional research

Critically, these personas needed to sound human and imperfect, not like experts or chatbots.

Our Approach

We approached this as a design and governance challenge, not just a technical one.

1. Persona Grounding & Scope Definition

Each AI persona was grounded in:

• Existing segmentation and qualitative research

• Clear demographic, behavioural, and emotional profiles

• Explicit articulation of motivations, barriers, and trade-offs

Just as importantly, we defined what the personas should not do, including:

• No expert knowledge

• No calculations or strategic advice

• No topics outside lifestyle, shopping, and personal preference

This ensured personas stayed realistic and safe.

2. Prompt Architecture & Behaviour Design

For each persona, we designed a structured, data and insight driven, instruction framework covering:

• Core identity and emotional drivers

• Tone of voice and language style

• Shopping behaviours and brand perceptions

• Contextual boundaries (what they can and can’t respond to)

• Acceptable uncertainty with truly human, personal dislikes, contradiction and language.

This was critical to avoiding “AI sounding AI”, bring insights to life in a human way.

3. Variability & Scenario Testing

To increase usefulness, personas were designed with:

• Gender and demographic toggles

• Adjustable life-stage and context parameters

• Consistent emotional drivers across variations

This allowed teams to explore:

• How different customer types might react

• Trade-offs between price, style, and performance

• Early reactions to concepts, propositions, or positioning

4. Guardrails, Ethics & Governance

Strong guardrails were built in by design:

• No personal or identifiable data

• No learning or memory beyond the session

• No use outside defined research-style interactions

• Clear positioning as synthetic, not real customers 

This made the personas suitable for broad internal use without creating compliance or reputational risk.

The Solution

The engagement delivered a suite of interactive AI personas, including:

• Multiple distinct customer archetypes with clear emotional drivers

• Chat-based interaction that mimics interviews or workshops

• Structured prompt frameworks that can be reused or adapted

• Personas that can be explored live in meetings, planning sessions, or concept reviews

Rather than static documents, the personas became living insight tools that teams could engage with directly.

Results & Impact

The interactive personas delivered immediate and practical value:

• Faster access to customer perspective during planning

• Reduced reliance on lengthy research cycles for early-stage questions

• Improved cross-functional alignment around “who the customer is”

• More engaging and customer-led workshops and discussions

• Increased confidence in using AI in a responsible, bounded way

Most importantly, teams shifted from talking about customers to interacting with them.

Key Takeaway

AI personas are not about replacing research — they are about making insight usable.

When carefully designed, governed, and grounded in real research, interactive AI personas can dramatically improve how organisations keep the customer at the centre of decisions.