Conversation Task: Writing Effective Conversation Objectives

At a Glance

• What it is: The Conversation Objective is an essential property of the Conversation Task type that defines the goal, flow, and tone for the AI moderator that will engage with participants.
• Why it matters: Clear objectives produce more focused, predictable conversations that generate more actionable insights.
• How to write it: Combine a clear goal (e.g., “Uncover unmet needs…”) with actionable guidance (steps, probes, techniques) and relevant context (who, what, why).

Overview

The new Recollective Conversation Task works best when it includes a clear, well-defined Conversation Objective. This objective explains what the AI moderator should accomplish and how it should engage with participants. It outlines what you want to learn, how the discussion should unfold, and the tone or style the AI should use. Think of it as a distilled version of a research brief—concise, purposeful, and focused. The more specific your objective, the smoother, more insightful, and more consistent the conversations will be.

There’s no single “right” way to write an objective. Some work best framed as a goal (for example, “I want to uncover…”), while others are more effective as direct instructions (for example, “Ask the participant to…”). In practice, the strongest objectives often blend both—combining clarity of purpose with guidance on how to achieve it.

Broad objectives can result in extended, uneven discussions, whereas tightly defined ones conclude more efficiently and with greater clarity. If ever your objective feels too ambitious, consider splitting it into multiple Conversation Tasks.

Iterating and Refining Objectives

Writing a strong Conversation Objective is as much an iterative process as it is a creative one. The best way to evaluate whether your objective works is to experience it from the participant’s perspective.

If you already have an objective in mind, simply add it to a Conversation Task and select Save and Preview to experience it firsthand. Use this as a pilot run—observe how the AI moderator engages, where the dialogue feels focused, and where it may drift. Then refine your objective to sharpen its purpose and improve the flow. You can repeat this process as often as needed to get it just right.

If you’re unsure how to refine it—or if you want to explore a broader area—then go ahead and start with a broad conversation objective. Let the first round of conversations reveal what themes, emotions, or insights emerge naturally. You can then design subsequent Conversation Tasks that dig deeper into those specific areas.

This iterative approach mirrors how qualitative research evolves in practice: start with exploration, then progressively narrow in on what matters most. Each round of refinement helps you craft objectives that are clearer, more targeted, and more aligned with your study’s goals.

Over time, you’ll likely find it helpful to build a library of template objectives—ones that you can quickly adapt for new studies or different research goals. Start saving the objectives that work well, refine them based on what you learn, and reuse them as starting points for future conversations. This not only streamlines your process but also strengthens your overall research framework, making each new study more focused and efficient.

Sample Conversation Objective

The following example illustrates how a well-crafted Conversation Objective can combine structure, focus, and intent to guide meaningful dialogue. It demonstrates how to balance emotional exploration with practical evaluation, moving participants from their current attitudes toward their reactions to a new concept.

This sample also shows how providing context—such as product details, sensory cues, and descriptive framing—enables the AI moderator to elicit deeper, more grounded insights. Through this use of context, the conversation becomes more vivid and emotionally resonant, leading to richer, more authentic feedback.

Our goal is to understand how consumers perceive and respond to the transition from plastic to fully compostable takeout food containers, focusing on their practical considerations, expectations, and decision-making criteria when evaluating sustainable packaging options.

The discussion should begin by exploring participants’ current views on sustainability in food packaging. We specifically want to know if it influences their dining or takeout decisions, and if so, in what ways. If participants indicate that sustainability matters to them, ask them to describe the most important qualities they believe eco-friendly containers should have.

Once participants have fully shared their expectations, introduce EcoPak’s new concept: containers made from plant-based materials that fully decompose in municipal compost within 60 days. Emphasize that these containers feature a distinctive texture and color that set them apart from plastic. Gather participants’ first impressions, then explore the trade-offs they would be willing to accept in terms of cost and durability. If their important qualities mentioned earlier differ from the concept, probe into each difference to understand the reasons behind it.

For reference, EcoPak’s plant-based containers have a naturally smooth yet matte texture, made from cornstarch and bamboo fibers that hold a subtle organic grain. This material composition gives them a warmer, more natural feel compared to the slick, synthetic surface of traditional plastic. They do not include clear lids or metal handles.

This prompt makes use of various dimensions and moderation techniques which we discuss in greater detail below:

• Structure: Semi-structured
• Focus: Depth
• Intent: Exploratory
• Elicitation: Direct + reflective
• Timeframe: Present to future
• Context: Rich stimulus

Key Dimensions

When crafting a conversation objective, it’s useful to consider the various dimensions that can influence how discussions can unfold.

These dimensions act like dials that adjust different qualities of the exchange—such as structure, focus, and tone. You don’t need to use every dial each time, but being aware of them helps you design interactions that are more intentional and meaningful.

Structure

Start by deciding how tightly the AI moderator should follow a path. Use a structured approach for consistency and use a flexible one to let stories flow naturally.

Structured Example:

Guide participants step by step through the customer journey for [product]—covering discovery, evaluation, purchase, onboarding, and ongoing use—in order to capture expectations, decision factors, and barriers at each stage.

Flexible Example:

Invite participants to freely describe their natural journey of discovering, deciding on, and using [product], allowing them to shape the flow while surfacing priorities, concerns, and key decision points in their own words.

Focus

Choose whether to explore many topics or dig deeply into one. Broader focus surfaces variety; deeper focus reveals detail and emotion.

Breadth Example:

Map all the different ways participants currently [achieve goal/do activity], covering [area 1], [area 2], [area 3], and any other methods they mention.

Depth Example:

Dig deeply into one specific instance of [activity/behaviour]. Capture every detail of what happened, who was involved, how decisions were made, and how they felt.

Intent

Set whether the goal is to capture what exists or discover what could be. Descriptive style uncovers facts; exploratory reveals opportunities.

Descriptive Example:

Document exactly how participants approached [task/product] the last time they used it — what steps they took, what worked well, and what challenges arose.

Exploratory Example:

Explore participants’ unmet needs and frustrations around [category]. Encourage them to suggest ideas, features, or solutions they wish existed.

Elicitation Style

Select how questions should be asked. Direct style get clear answers; indirect ones uncover feelings and symbolism.

Direct Example:

Ask what made participants choose [brand/product] over others. I’d like each person to rank their factors in order of importance.

Indirect Example:

Ask participants if [brand/product] were a type of animal, which one would it be and why? Use their answer to probe the qualities they associate with the brand.

Timeframe

Guide participants to look back or imagine forward. Use past or present for real experiences; future for aspirations or projections.

Past/Present Example:

Ask participants to recall their most recent [activity/experience] and describe it in detail from beginning to end.

Future Example:

Ask participants to imagine their ideal [future scenario/product/service] in [time horizon], and describe how it would work, how it would feel, and why it would be better than today.

Context & Stimulus

Decide how much information participants need for the conversation. Minimal background information for simpler inquiries; rich context or stimulus for more nuanced scenarios.

Minimal Example:

Ask participants open questions about how they generally approach [topic/decision], without providing examples or background — rely on their own framing.

Rich Example:

Have participants review the [ad/prototype/concept statement] provided above for [product/service]. Ask for their immediate reactions, likes/dislikes, and suggestions for improvement. It is important to note the [background and context].

Setting Tone & Role

By default, conversations are conducted in a friendly, professional manner—similar to how a skilled researcher would engage participants. You can actually override this default by specifying a desired tone or behavioral style. For example, you might ask the moderator to adopt a challenging, playful, reassuring, or even sarcastic tone.

In addition to setting tone, you can assign the moderator a distinct role that determines how it approaches conversation and inquiry. For instance, you might instruct it to “act as” a product manager, medical professional, UX researcher, technologist, or financial advisor.

If you’d like to go a step further, you can describe the participants’ background and relationship to the topic to give the moderator extra context. For example, noting that participants are customers, parents, patients, scientists, educators, or academics can help it adapt its tone and approach more effectively.

Here are some examples:

Tone

Build a rapport with participants as you explore their experiences with [medical condition]. Use a warm conversational tone, validate their feelings, and encourage openness by showing empathy.

Moderator Role

Act as a Product Manager and interview participants to understand which [product] features they find most valuable and what pain points they experience when using the product and others in the same category.

Participant Background

The participants are existing customers that have significant experience with a previous version of the product that lacked [specific features].

The participants are patients battling [specific disease] and are part of a clinical trial that will last for 5 years. The trial began last year.

The participants are nurses specialized in [area of practice] and have a solid understanding of relevant terminology.

Combination

Act as a digital wellbeing coach with attitude. Use a playful and somewhat sarcastic tone to engage parents about their teenagers’ habits with their smartphones. Keep the conversation fun and light.

Act as a trend-savvy bestie. Keep things light, clever, and a bit reflective — help the Gen Z participants spill the truth on what’s trending or totally tired.

Controlling Duration

Conversation duration cannot be reliably limited by time or turns. Some participants reply quickly, while others take time to reflect, type slowly, or pause between answers. The system adapts automatically to ensure the conversation unfolds at a natural pace.

Ultimately, how long a conversation lasts depends on your objective and how you guide the moderator. Broad or multi-part goals tend to take longer, while focused ones wrap up more quickly.

The AI moderator is designed to stay on task — pursuing the stated objective efficiently and ending the conversation once it determines that goal has been met. It may also close early if the participant isn’t a good fit or shows frustration and asks to stop.

You can shape the overall duration by refining your objective:

• Limit scope: ask for “a few words,” “two reasons,” “one short example.”
• Adjust depth: specify which topics to probe deeply, lightly, or skip.
• General guidance: ask for a “very short conversation” or “detailed exchange.”

Ultimately, clear objectives and thoughtful guidance determine how a conversation unfolds. Responding realistically during testing helps you fine-tune pacing and ensure the exchange ends efficiently.

Creative Techniques

Your Conversation Objectives don’t define a goal—they can also shape how the AI moderator behaves. With the right guidance, you can direct it to apply techniques that experienced moderators use to uncover deeper, more nuanced insights. The techniques below illustrate only a few of the many ways you can bring variety and depth to your objectives.

Pacing & Timing

Try these techniques to manage rhythm and flow, ensuring the moderator doesn’t push too soon or stop too early.

• Conditional Probe: Don’t introduce [topic]; if the participant raises it, then go deep (triggers, feelings, consequences, what would change it).
• Threshold Trigger: When emotions spike, pause and unpack why.
• Deferred Probe: Quietly track mentions of [theme]; only explore if it recurs.
• Escalation Ladder: Build comfort first; ask more personal questions gradually.

Control Focus & Effort

Use these techniques to balance efficiency and richness, avoiding aimless chatter while uncovering depth where it matters.

• Limit → Expand: Start tight (one word/top 3), then unpack the story.
• Priority Filter: Force a choice and explore why it wins.
• Comparative Push: Ask “Compared to what?” to sharpen insight.
• Contrast Amplifier: Capture both “best” and “worst” to reveal differences.

Self‑Reflection

Explore techniques to create perspective and encourage introspection.

• Role Switch: Turn critique into constructive design: “If you had control, what would you fix first?”
• Perspective Flip: Ask what a skeptic would say, then reconcile views.
• Doubt Trigger: When hesitation appears, explore its roots and what resolves it.
• Evidence Gate: Anchor every claim in a concrete example.
• Delayed Reflection: Compare first and final impressions to reveal shifts.

Conversation Starters

Good objectives will focus the AI moderator on uncovering perceptions, motivations, needs, decisions, and influences—the drivers behind how people think and behave. Below are some ideas to get you started on how you can create engaging conversations that boost the quality of your findings.

Perceptions & Impressions

Explore how people see or describe a product or brand.

• First Impressions: “I want to uncover the three words people use to describe the [brand] and what those words reveal about trust and usability.”
• Explain to a Friend: “I want to hear how participants describe [the product] to a friend to reveal authentic language and tone.”

Motives & Mindsets

Understand why people act as they do.

• Motivation and Barriers: “I want to explore what motivates people to try [product] and what prevents repeat purchases.”
• Moments of Doubt: “I want to identify what triggers hesitation before subscribing and what reassures people to continue.”

Needs & Opportunities

Spot gaps and possibilities.

• Unmet Needs: “I want to uncover frustrations people face when [taking an action] to find where [brand] could add value.”
• Future Vision: “I want to explore how people imagine a [future state] and what today’s experience lacks.”

Decision-Making

Reveal what shapes choices.

• Trade-Offs: “I want to understand how people weigh price versus quality in [category] and what tips the decision.”
• Competitor Switch: “I want to know what prompts customers to leave one brand of [category] and what might bring them back.”

Social & External Influences

Examine how others shape opinions.

• Trusted Sources: “I want to learn which information sources—friends, reviews, or experts—people trust most when shopping for [product].”
• Social Influence: “I want to explore how others’ opinions affect decisions about trying new [services].”

Journeys & Triggers

Map the path to action.

• Journey Mapping: “I want to trace the journey from discovery to loyalty, capturing emotional highs and lows.”
• Switching Triggers: “I want to understand what prompts people to change [product or service] and what could prevent churn.”

Providing Context

Conversation Objectives should also equip AI moderators with the background information they need to perform effectively. Supplying context means including key details about the product, service, or research focus to ensure moderators can frame questions appropriately, avoid misunderstandings, and probe more meaningfully.

Think of context as the “briefing packet” you would give a human moderator: by embedding this information directly in your objective, you are helping the AI moderator drive more accurate, relevant, and insightful conversations.

We only suggest you include context that is directly relevant to the discussion. This can include:

• Who: Participant demographics, roles, motivations, or familiarity with the topic.
• What: Product, service, or concept, including key features and prototype stage.
• Why: Research intent, hypotheses, and success factors.
• Sensitivities: Topics to approach gently or avoid.
• Positioning: How something fits within the broader category or landscape.
• Mindset: What participants already know, expect, or feel about the topic.
• Prior findings: Existing insights to ensure the AI moderator doesn’t repeat questions.
• Cultural nuances: Habits, customs or sensitivities that may influence the discussion.

You can also include responses from earlier tasks directly in the conversation objective. These dynamically inserted values can drive the conversation or be included as supporting information.

In Summary

A well-crafted Conversation Objective is the foundation for rich, purposeful dialogue. It tells the AI moderator what to explore, how to probe, and when to pivot—ensuring each conversation unfolds with clarity and intent. The result? Exchanges that feel natural yet insightful, yielding findings that are consistent, actionable, and deeply aligned with your research goals.