Company Context: How to Make Your AI Interviewer a Domain Expert

Company Context: How to Make Your AI Interviewer a Domain Expert

The short answer: Company context is how you teach Koji about your specific business, product, industry, and customers. When configured well, Koji's AI interviewer asks sharper, more relevant follow-up questions — turning a generic AI interview into one that feels specifically designed for your research.

The difference between a good AI interview and a great one often comes down to context. An AI that understands your product category, your customers' typical workflows, and the language your industry uses will naturally ask better follow-up questions than one operating with no background knowledge.

This guide explains what company context is, what to include, how to add it, and how it changes the quality of your interviews.

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What Is Company Context?

Company context is a freeform field in your Koji account settings that lets you provide background information about your organization. Think of it as a briefing document for the AI interviewer — the kind of context you would give a human researcher before their first day on the job.

Unlike the research brief, which is study-specific, company context applies across all your studies. It is set once and automatically used in every interview you run.

What company context includes

Good company context typically covers:

• What your company does: a clear description of your product or service
• Who your customers are: the primary personas, industries, or roles you serve
• Key terminology: product names, internal jargon, industry-specific vocabulary
• Business model: how you sell, what problems you solve, what market you are in
• Current focus areas: what the company is actively working on or trying to understand
• Competitors and alternatives: what customers compare you to

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Why Company Context Improves Interview Quality

Without context, Koji's AI makes interview decisions with only general knowledge of your topic area. With context, it has a specific mental model of your world.

Here is a concrete example. Suppose your company makes B2B expense management software. Without company context, the AI might ask a generic follow-up like "what tools do you use for that?" With company context, it can ask more targeted questions like "you mentioned approval workflows — does your team use automated routing or manual delegation?" because it knows what features your product has and what problems your customers typically face.

Company context enables:

• Sharper follow-up questions — the AI probes on things that are actually relevant to your business
• Correct terminology — participants are not confused when your industry uses specific vocabulary
• Better topic coverage — the AI recognizes when participants mention your product category and knows how to explore deeper
• More natural conversations — the interview feels less robotic and more like talking to someone who understands the space

Research quality scores — measured by relevance, depth, and coverage — consistently improve when company context is configured well.

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How to Add Company Context

Company context is configured at the account level:

1. Go to Settings in your Koji dashboard
2. Select Company Context from the settings menu
3. Write your context in the text field provided
4. Save your changes

Changes take effect immediately and apply to all new interviews. Existing conversations are not retroactively updated, but you can update your context at any time as your business or research focus evolves.

Writing effective company context: a template

Here is a template for crafting useful company context:

[Company name] is a [brief product description]. We help [target customer] [achieve what outcome] by [how the product works].

Our main customer segments are: [segment 1], [segment 2], [segment 3].

Key terminology our customers use: [term 1], [term 2], [term 3].

Our main competitors and alternatives include: [competitor 1], [competitor 2].

Current research focus: [what you are trying to learn right now].

What makes us different from alternatives: [key differentiators].

Keep context concise and factual. 150–400 words is typically the right length. Longer context is not always better — focus on what is most likely to make follow-up questions sharper.

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Examples by Industry

SaaS company (project management tool)

Acme is a project management tool for software engineering teams. We help teams track sprints, manage backlogs, and ship features faster.

Our customers are typically engineering managers, product managers, and software developers at companies with 50–500 engineers.

Key terminology: sprints, backlogs, epics, stories, velocity, ceremonies, standups, retros.

Main competitors: Jira, Linear, Shortcut, GitHub Projects.

Our key differentiator: designed specifically for engineering-heavy teams who want speed over customization.

E-commerce (DTC brand)

[Brand] sells premium sustainable activewear direct to consumers in Europe. We focus on performance gear for recreational athletes — runners, cyclists, and gym-goers aged 25–40.

Our customers are health-conscious buyers who prioritize quality and sustainability over price. They often compare us to Lululemon, Patagonia, and Arc'teryx.

Key purchase drivers: material quality, fit, environmental impact, brand values.

Current focus: understanding post-purchase satisfaction and repeat purchase behavior.

Healthcare startup (patient communication platform)

[Company] helps outpatient clinics improve patient communication and reduce no-shows through automated messaging and appointment management.

Our users are clinic administrators and practice managers at small-to-mid-size medical practices. Patients interact with consumer-facing tools but are not our primary buyers.

Key terms: EHR integration, scheduling workflow, patient portal, HIPAA compliance, front desk staff.

Current research: how practices handle appointment reminders and what breaks down in existing workflows.

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Company Context vs. Context Documents

Koji offers two ways to provide background information: company context and context documents.

Company context (Settings → Company Context) is a persistent, always-on background for your entire account. It is applied globally to all interviews.

Context documents are study-specific files you upload to individual studies — product specs, feature documentation, competitive analyses, previous research findings. They provide depth on the specific topic you are researching.

Use both together for best results: company context handles the "who we are and who our customers are" layer, while context documents handle the "what we are specifically researching right now" layer.

For example, a product team might have company context describing their SaaS product and customer base, then upload a specific feature spec as a context document when researching that feature's adoption.

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Company Context for Agency and Multi-Client Research

If you use Koji across multiple clients or product lines, you have options:

• Rotating context: update company context before each client's research project. Simple but requires discipline to keep current.
• Separate accounts per client: enterprise-tier accounts can discuss multi-account setups with the Koji team.

For agencies, be explicit about client context: include the client company name, industry, and research goals so Koji's AI is appropriately specialized even when conducting research on behalf of a client.

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Measuring the Impact of Company Context

After adding company context, run a few interviews and review quality scores. Interviews with well-configured company context typically score higher on:

• Relevance (1–5): whether the conversation stayed focused on what matters for your research
• Depth (1–5): whether the AI probed on the right things
• Coverage (1–5): whether key questions and topics were addressed

If you are seeing low quality scores even with good context, check your research brief — especially the methodology, key questions, and topics to explore. Company context helps the AI ask better follow-ups, but the research brief drives the overall interview structure.

See the Understanding Quality Scores guide for how to interpret scores and identify what to improve.

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Tips for Maintaining Your Company Context

• Review quarterly: update context when your product, target market, or research focus changes
• Add new terminology: as your product adds features with specific names, add those terms
• Refine after early studies: if you notice the AI asking off-target follow-ups, revise your context to address the gap
• Keep it factual: avoid marketing language and superlatives — concrete, specific descriptions produce better follow-up questions than vague claims

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Related Resources

• Understanding the Research Brief — the study-specific configuration that works alongside company context
• Uploading Context Documents — add study-specific depth beyond account-level context
• Structured Questions Guide — combine contextual AI probing with quantitative question types
• Setting Up Voice Interviews — configure the full interview experience
• Understanding Quality Scores — measure the impact of your context on interview quality
• Working with the AI Consultant — get help designing your full research setup