Commercial due diligence on User Intuition is an eight-step workflow: Create Study, Customize Plan, Review Goals, Setup Interview, Test Conversation, Launch, Invite Participants, and Review Insights. The product is built so a PE associate, a growth equity principal, an investment banking advisor, or a corporate development lead can launch a customer-interview program in an afternoon, then watch transcripts, satisfaction-rated calls, and synthesized findings show up inside the Intelligence Hub within 48-72 hours. Pricing sits at roughly $20/interview on the Pro plan, and the 4M+ research panel covers 50+ languages, which means a 60-interview market check across NA, EU, and LATAM is a single weekend’s work, not a six-week consulting engagement. This tutorial walks each step with verbatim product labels, the choices that matter for commercial due diligence specifically, and links to the underlying docs.
For the broader methodology, see the methodology guide. For pricing and the comparison against management reference calls and consulting panels, see the User Intuition commercial due diligence platform page. This piece stays in the workflow lane: what to click, where to click it, and why each setting matters when the cohort is the target’s customers, lost prospects, and market alternatives.
What is commercial due diligence, briefly?
Commercial due diligence is the independent validation of a target’s customer relationships, market position, competitive dynamics, and growth thesis before the deal team commits capital. It sits between two failed substitutes: management-curated reference calls, where the seller hand-picks five happy customers (industry research shows satisfaction scores on these calls run 30-40% higher than independent samples), and traditional consulting workstreams, which take 6 to 12 weeks and cost $100K to $500K. Neither produces independent evidence at deal pace.
Done well, commercial due diligence answers four questions before bid. First, what is the retention story across the customer base, not the curated 5%? Second, would customers buy more, pay more, or expand (the growth thesis)? Third, how do customers describe the target versus alternatives in their own words (the moat)? Fourth, where is concentration risk hiding behind the financial data?
The mechanism that makes commercial due diligence work is depth at scale. A 30-minute conversation with a target customer, with 5 to 7 levels of structured probing on switching cost, NPS drivers, and competitive alternatives, surfaces decision drivers that a 2-minute reference call will never reach. Implementation risk perception, champion concentration, contract lock-in, vertical credibility, these patterns sit underneath the data-room narrative and show up only in conversation.
AI-moderated platforms compress the timeline from weeks to 48-72 hours and the cost from $100K+ per workstream to $200 floor pricing. That changes what is possible inside the deal calendar. Instead of one curated workstream, deal teams can run 30 to 100 independent interviews on every serious target, feed every transcript into a searchable Intelligence Hub, and use the same evidence base for IC, 100-day planning, and quarterly value creation tracking.
Why doing this on User Intuition is different
Most commercial due diligence tooling forces a choice between depth and speed. Reference calls are fast and biased. Consulting workstreams are deep and slow. User Intuition delivers both, and the product flow is shaped by that goal.
The AI moderator runs 30-minute laddering conversations with each customer and probes 5 to 7 levels deep on satisfaction drivers, switching risk, and competitive alternatives. Every conversation runs the same methodology, so a 30-interview study and a 200-interview study are directly comparable. No caller bias, because no human caller is in the room. Customers report higher candor with AI moderators than with vendor-affiliated researchers, and the 98% participant satisfaction rate reflects that.
Recruitment is built in and stays independent of the target. The 4M+ research panel covers 50+ languages and lets the deal team filter by industry, company size, decision-maker role, and geography without ever asking the seller for a customer list. Share links route deal team-supplied references in directly. Blind market check across regions scales through the panel without coordination overhead.
Synthesis runs in the same product. Once interviews complete, the Reports tab generates an Executive Summary, Top Insights, Detailed Analysis with verbatim customer quotes, and Recommendations. The Intelligence Hub layers across studies, surfacing compounding insights any single-study report would miss. Pricing at $20/interview makes rigorous commercial due diligence financially viable for every serious target in the pipeline. See the commercial due diligence platform page for the full positioning.
The 8-step walkthrough
The product flow is the same for every study type. The choices below are tuned for commercial due diligence specifically.
Step 1: Create Study
Open the New Study screen and you will see six pre-built templates: Win/Loss Analysis, Churn Analysis, NPS and CSAT, Customer Onboarding, Brand Health, and Custom Design. For commercial due diligence, the choice depends on the deal thesis. Pick Win/Loss Analysis for competitive customer research (“Why did customers choose the target over alternatives?”). Pick NPS and CSAT for renewal and retention thesis validation (“Is reported satisfaction durable?”). Pick Custom Design when the deal team has a thesis question that does not map to a standard template. The selected card highlights with a dark background. Click Save & Continue.
Commercial due diligence often blends 2 to 3 study types across the same panel. For a typical platform deal, the team runs a Win/Loss-style study on lost prospects, an NPS-style study on the existing base, and a Custom study on a specific hypothesis (pricing power, expansion willingness). See Choose Your Study Type for the full comparison.
Step 2: Customize Plan
The Customize Plan screen opens a chat with Charles, our AI researcher. Type your context into the chat box and Charles drafts the full research plan: Objective, Background, North-Star Learning Goal, Key Sub-Questions, Conversation Flow, and Interviewer Guidelines, all in a panel on the right.
For commercial due diligence, give Charles four things up front. First, the target: “We are evaluating [target company] for acquisition.” Second, the segments: “We need current customers, lost prospects in the last 12 months, and customers using a primary alternative.” Third, the thesis: “We are testing retention durability, growth willingness (expand or pay more), and the competitive moat.” Fourth, the IC timing: “Findings need to be IC-ready within 7 days.” Charles returns a research plan that asks about NPS drivers, switching cost, competitive alternatives, expansion willingness, and champion concentration.
Commercial due diligence-specific tip: tell Charles what the deal team is most worried about. He uses your hypotheses to design probes that test or break them, keeping interviews out of ground that is already in the data room. Read the Customize Plan docs for the full context, scope, and objective questions Charles will ask.
Step 3: Review Goals
The Review Goals screen opens the research plan in a rich text editor. Study Name sits at the top (Charles suggests one like “Project [codename] Customer Diligence, Q2”; rename to fit the deal team’s convention). Below that, every section, Objective through Interviewer Guidelines, is editable. Changes save automatically.
This is the step where deal teams add IC-memo alignment. The default plan covers satisfaction and switching, but for IC defensibility you want explicit coverage of the four canonical thesis areas: NPS-style satisfaction, switching cost and renewal intent, share-of-wallet and expansion willingness, and competitive alternatives. Add a sub-question like “If the price increased 15% at renewal, what would you do?” That pressure-tests pricing power in a way no data-room artifact can.
Commercial due diligence-specific tip: keep Key Sub-Questions to 4 to 6 themes with 2 to 4 questions each. Twelve questions or fewer keeps completion above 70% on customer cohorts inside a 14-day DDQ window. Findings that do not map back to the thesis generate noise. The Review Study docs have the full editing toolbar reference. Click Save & Continue when ready.
Step 4: Setup Interview
The Setup Interview screen handles the participant-facing experience. Two voice cards: Elliot (Male, American) and Clara (Female, American). Click the play button on each card to preview. Pick the one whose tone fits the customer audience; click the card to select. Below the voice cards, the Default Mode toggles control format: Chat, Audio, or Video. Audio is the default for commercial due diligence because voice transcripts capture tone and hesitation around switching and renewal that chat will not.
Below the format toggles is the screener questions section. Add the highest-leverage screener: “Have you used [target company] in the last 6 months?” or “Were you involved in the [target company] purchase or renewal decision?” Anyone who answers no drops out before consuming a credit. Language and country targeting happens later in the Invite Participants step, not here.
Commercial due diligence-specific tip: pick Elliot or Clara based on the customer demographic, not the deal team’s preference. The match between moderator voice and participant audience measurably improves rapport and depth. Read the Setup Interviewer docs for the full mode-selection guide.
Step 5: Test Conversation
The Test Conversation screen prompts you with “Ready to test your study?” Click Start Test Conversation and you experience the full participant flow: greeting, study introduction, research questions, AI probing, wrap-up. Test conversations do not count against usage limits. After the test, a feedback screen asks “How was the conversation?” with Good or Needs Work options.
For commercial due diligence, run two test conversations before launch. The first as a happy long-tenured customer: listen for whether the AI probes the durability of that satisfaction (it should not accept “the product works great” as a final answer). The second as a customer evaluating an alternative: listen for whether the AI probes past “we are looking around” into specific alternatives and switching cost math. Deal-pace work means no second chance after IC.
Commercial due diligence-specific tip: if the AI accepts a surface answer, go back to Step 3 and tighten the Interviewer Guidelines with explicit instructions like “Probe at least three levels deep when participants describe satisfaction or competitive alternatives.” The Test Conversation docs cover what to look for during testing.
Step 6: Launch
The Launch screen shows three summary cards (Study Type, Interviewer, Interview Type), the Study Name, and the Research Plan Preview. The final review checklist sits in three accordions: Research Plan, Interviewer Settings, Study Configuration. When everything looks right, click Save and Launch (the rocket-icon button). Your study goes live immediately. You are redirected to the Study Dashboard.
The detail deal teams miss: launching does not automatically send invitations. The study is live and ready to receive participants, but recruitment happens in the next step. This is intentional: most teams want to set up the config first, review with the partner or MD, then trigger recruitment on a specific day inside the DDQ window.
Commercial due diligence-specific tip: launch on Day 3 or 4 of a 14-day DDQ window. That leaves 7 to 10 days for completion and 2 to 3 days for synthesis before IC memo lock. For 6 to 8 week DDQ windows, launch a wave-one broad market check on Day 3, then a wave-two thesis-specific cohort after IC pre-read. The Launch docs cover what can and cannot be changed post-launch.
Step 7: Invite Participants
This step opens after launch. From the Study Dashboard, the Invites tab plus the Actions dropdown gives four invitation methods.
Research Panel opens recruitment from the 4M+ panel across 50+ languages, with country and language selection here. This is the workhorse for commercial due diligence: filter by industry, company size, and decision-maker role to build a blind market check sample independent of the target’s data room. For multi-region acquisitions (NA + EU + LATAM), set country here and run parallel cohorts in one study. Invite Your Customers lets the deal team upload a customer list (target-provided under exclusivity or deal team-built) via CSV or the Contacts tab. Share Link generates a unique URL the deal team pastes into a personalized email to a known reference. Embed Widget is rarely used in CDD; reserve it for portfolio company post-close monitoring. See the recruiting overview, the research panel docs, and the share link docs.
Commercial due diligence-specific tip: combine methods. Research panel for blind market check (the segment the target cannot influence), share link for known references (where the deal team needs specific account voices). A 60-interview study split 40 panel-recruited and 20 deal team-supplied is the most defensible IC sample shape.
Step 8: Review Insights
Once interviews complete (first ones inside hours, full cohorts within 48-72 hours), three tabs hold the output. The Calls tab lists every interview with email, status, date, duration, quality rating (High, Medium, Poor), and end reason. Click any row to expand the transcript with audio playback. The Reports tab holds the AI-synthesized analysis: Executive Summary, Total Participants, Top Insights at a Glance, Detailed Analysis with verbatim quotes, and Recommendations. Click Generate Report once you have 2+ completed interviews; click Regenerate Report as more land.
The third surface is the Intelligence Hub in the left navigation. Each Hub session is a workspace where you sync studies, upload supplementary files (data-room artifacts, financial DD outputs, market reports), and ask natural-language questions across everything in the room. For commercial due diligence, this is where IC-defensible synthesis lives.
Commercial due diligence-specific tip: create a single Intelligence Hub session per deal called “Project [codename] CDD” at launch, sync every wave into it, and add the IC memo and financial DD documents as supplementary sources. Then ask questions like “Where do customer-reported NPS drivers contradict management’s stated value proposition?” Most consulting-led CDD reports lose 30% of insight value because synthesis happens in spreadsheets nobody opens after IC. The Hub keeps the evidence base indexed through IC, 100-day planning, and quarterly value creation tracking. The Intelligence Hub docs and Reports docs cover the full output surface.
Mini case study
A growth equity firm ran the workflow on a target SaaS business inside a 4-week DDQ window. The deal team set up the study in a single afternoon: NPS and CSAT template at Step 1, target company and four-segment recruitment plan briefed to Charles at Step 2, learning goals tightened at Step 3 to map to the four IC thesis areas (retention durability, growth willingness, competitive moat, concentration risk), Audio mode and the 6-month usage screener at Step 4, two test conversations at Step 5, launched Day 3 at Step 6.
Recruitment used the research panel filtered by industry and company size for a blind market check sample of 60 customers, with no involvement from the target’s management. All 60 interviews completed within 72 hours.
The Reports tab and Intelligence Hub surfaced a finding that contradicted the deal-room narrative. Reported NPS in the data room was 65. Independent NPS from the panel sample was 41. The dominant theme, present in 38 of 60 transcripts, was implementation friction in the past 18 months: customers loved the product but resented onboarding and felt the relationship had degraded since acquisition by current ownership. The deal team renegotiated the bid by 12% and built a 100-day customer success investment plan into the value creation thesis. The deal closed at the lower price.
“Management-curated reference calls told us a retention story. AI-moderated interviews with 60 customers, chosen independently from the data room list, told us a different one, churn risk concentrated in the top deciles of revenue. That evidence is what investment committees actually want, delivered before the next Monday meeting.”
Joel M., CEO, Abacus Wealth Partners
What gets the best results from commercial due diligence on User Intuition?
Tips for getting the most out of the workflow, gathered from the patterns that consistently produce IC-defensible findings.
Keep the research plan tight. Aim for 4 to 6 main themes with 2 to 4 sub-questions each at Step 3. Plans with 8+ themes produce interviews longer than 25 minutes and completion rates drop, brutal inside a 14-day DDQ window. Twelve questions or fewer keeps completion above 70% on independent customer cohorts.
Run two test conversations every time. One as a happy customer, one as a customer evaluating an alternative. The highest-leverage 20 minutes the deal team can spend before launch is catching tone misalignment or shallow probing while it is still cheap to fix.
Pick voice over chat. Voice transcripts surface tone, hesitation, and emotional emphasis around switching and renewal that chat compresses out. Reserve chat for international cohorts where typing fits language fluency better.
Recruit independently of the target wherever possible. The 4M+ panel filtered by industry and company size builds a sample the seller cannot curate. Pair it with deal team-supplied known references for completeness. Avoid pure management-supplied reference lists, the satisfaction lift on those calls runs 30-40% above truth.
Run waves, not one-shots. A wave-one read in the first week of DDQ informs IC pre-read; a wave-two cohort study after IC pre-read tests the specific hypotheses that survive. Two 30-interview waves outperform a single 60-interview shot for almost every commercial due diligence use case at $20/interview.
Sync the Intelligence Hub before IC and again at post-close. Every completed wave should land in the same project session inside the Intelligence Hub. Cross-wave pattern recognition is the highest-leverage output User Intuition produces, and it only works if every study lands in the same room. The same evidence base supports IC, 100-day planning, and quarterly value creation tracking. See the cost breakdown for commercial due diligence and the methodology for compressing the timeline for the budgeting and pacing case behind the wave structure.
Route findings inside 5 days. Commercial due diligence findings degrade fast because deal calendars degrade fast. As soon as the report and the Intelligence Hub are populated, route specific findings to specific owners (deal team, MD, IC member) with a defined SLA. This is the same logic that makes AI-driven commercial due diligence work as a continuous program across portfolio monitoring, not just a one-shot pre-close engagement. The studies that move the bid are the ones whose findings reach a decision-maker the same week.
FAQ
The frontmatter FAQ block above answers the most common questions. The full canonical answers also surface inline in the workflow above.