Every CX team needs a research playbook, a repeatable set of research frameworks that can be deployed quickly when scores drop, customers churn, or executives ask why. Without a playbook, each research initiative starts from scratch: debating methodology, designing questions, securing budget, and negotiating timelines. By the time the study launches, the window for timely action has often closed.
This playbook provides four research plays that CX teams can execute using AI-moderated interviews at User Intuition. Each play addresses a specific CX intelligence need, includes implementation templates, and produces structured outputs that drive action. At $20 per interview with results in 48-72 hours, these plays can be executed individually or combined into a continuous intelligence program.
What Is the Detractor Deep-Dive Play and When Should You Run It?
The Detractor Deep-Dive is the foundational CX research play. It converts NPS, CSAT, or CES detractors from data points into diagnostic intelligence by interviewing them within 7 days of their low score, while the experience that drove the rating is still fresh and specific.
When to run it. Trigger a Detractor Deep-Dive whenever NPS drops by 5 or more points in any segment, when a specific product or service generates a spike in low scores, when launching in a new market and baseline detractor reasons are unknown, or on a regular monthly cadence to maintain continuous understanding of dissatisfaction drivers.
Study design template. Target audience: customers who gave NPS scores of 0-6, CSAT scores of 1-2, or CES scores of 5-7 within the past 7 days. Sample size: 30-75 interviews. If you have multiple customer segments, aim for 10-15 per segment minimum. Recruitment method: upload your detractor list from your CRM or NPS platform directly to User Intuition. The platform handles invitation and scheduling.
Core research objectives. Identify the specific experiences and touchpoints driving low scores. Understand the expectation gap, that is, what customers expected versus what they received. Map the emotional journey from initial satisfaction to current dissatisfaction. Surface the competitive comparison frame customers use to evaluate you. Identify specific, actionable recovery pathways that would improve the customer’s perception.
Analysis framework. Structure your findings using the Root Cause Cluster method. Group interview findings into 3-7 root cause themes. For each theme, document: the specific failure or friction point, the customer expectation that was violated, the source of that expectation (marketing, competitors, previous experience), the emotional impact on the customer, and the customer-suggested remedy. Rank themes by frequency (how many detractors cite this cause) and severity (how strongly it affects satisfaction). This dual ranking prevents teams from optimizing for frequent-but-minor issues while ignoring rare-but-severe ones.
Output deliverable. A one-page Detractor Intelligence Brief containing: the top 3 root causes with frequency and severity scores, 2-3 customer verbatims per root cause (quoted directly from interviews), a prioritized action list ranked by expected impact and implementation effort, and a comparison to previous Detractor Deep-Dive findings to track whether previous interventions are working.
Implementation timeline. Day 1: Upload detractor list and launch study. Days 2-4: Interviews complete and analysis delivered. Day 5: CX team reviews findings and drafts Detractor Intelligence Brief. Day 6-7: Brief presented to stakeholders with action recommendations. Total elapsed time: one week from detractor identification to actionable intelligence. Compare this to the traditional timeline of 8-12 weeks and the advantage of AI-moderated research becomes visceral.
How Does the Churn Autopsy Play Work?
The Churn Autopsy play investigates why customers leave by interviewing recently churned customers within 14 days of cancellation. This play is distinct from the Detractor Deep-Dive because it focuses on customers who have already made the decision to leave, requiring a different conversational approach and producing different analytical outputs.
When to run it. Every month, or continuously if churn volume supports it. The Churn Autopsy should be an always-on program rather than a periodic study. Every churned customer represents intelligence about preventable loss. At $20 per interview, the cost of not interviewing them is almost always higher than the cost of understanding them.
Study design template. Target audience: customers who cancelled, downgraded, or did not renew within the past 14 days. Exclude customers who left for reasons unrelated to experience (company closures, mergers, role changes) by screening during interview setup. Sample size: aim to interview 50-100% of churned customers each month. If churn volume is very high, sample representatively across segments. Recruitment method: automated trigger from your CRM or subscription management system. When a customer churns, an interview invitation deploys automatically.
Core research objectives. Reconstruct the full decision timeline from initial dissatisfaction to final departure. Identify the trigger event that converted dissatisfaction into action. Understand what alternatives the customer evaluated and chose. Determine which specific interventions (if any) could have prevented the churn. Assess whether the customer would consider returning and under what conditions.
Analysis framework. Use the Churn Decision Chain method. For each churned customer, map the sequence: Background Dissatisfaction (chronic issues) leads to Trigger Event (the moment they decided to act) leads to Alternative Evaluation (what they compared you against) leads to Decision Factor (what tipped the choice) leads to Exit Execution (the cancellation process itself). Aggregate across all interviews to identify the most common background dissatisfactions, the most frequent trigger events, the most popular alternatives, and the most decisive factors. This chain-level analysis reveals multiple intervention points rather than a single “reason for churn.”
Output deliverable. A monthly Churn Intelligence Report containing: the top 5 churn decision chains by frequency, the estimated revenue impact of each chain (frequency multiplied by average customer value), a list of preventable versus non-preventable churn with percentage breakdown, specific intervention recommendations for each preventable churn chain, and trending data showing whether churn causes are shifting over time.
The Churn Autopsy is where CX research demonstrates its clearest financial ROI. If a monthly report identifies that 35% of churn is driven by a single addressable friction point, and the fix reduces churn by even one percentage point, the retained revenue typically exceeds the annual research cost by 50-200x. CX teams report that User Intuition’s structured analysis and evidence-traced findings make it straightforward to build the business case for fixing the issues research identifies.
What Does the Journey Probe Play Investigate?
The Journey Probe is a focused, tactical research play that investigates a single touchpoint or experience moment in the customer lifecycle. It is the scalpel to the Detractor Deep-Dive’s broader diagnostic, producing highly specific findings that the team owning that touchpoint can act on immediately.
When to run it. When quantitative data reveals friction at a specific touchpoint (high drop-off, low satisfaction scores, elevated support tickets). When a touchpoint is being redesigned and you need customer input before investing in development. When a Detractor Deep-Dive or Churn Autopsy reveals a touchpoint as a root cause and you need deeper understanding. When launching a new touchpoint (feature, process, channel) and want rapid feedback.
Study design template. Target audience: customers who recently experienced the specific touchpoint you are investigating. “Recently” means within the past 14 days for most touchpoints; for infrequent touchpoints like annual renewal, extend to 30 days. Sample size: 25-50 interviews. Touchpoint research reaches analytical saturation faster than broader studies because the scope is narrow. Recruitment: filter your customer base by the relevant behavioral event (completed onboarding, contacted support, renewed subscription) and invite from that filtered list.
Core research objectives. Map the customer’s actual experience of the touchpoint step by step, including steps before and after what you internally define as the touchpoint boundary. Identify specific friction points, confusion moments, and workarounds. Understand the customer’s expectations for this touchpoint and where those expectations come from. Capture the emotional texture of the experience (frustration, confusion, relief, delight). Collect customer-generated improvement ideas.
Analysis framework. Build a Touchpoint Experience Map with three layers. Layer one is the Process Layer: the actual steps the customer took, in their own sequence (which may differ from your designed sequence). Layer two is the Friction Layer: where customers encountered obstacles, confusion, delays, or workarounds. Layer three is the Emotion Layer: how customers felt at each stage of the process. Overlay these three layers to identify the moments where process friction and negative emotion coincide, as these are your highest-priority improvement targets.
Output deliverable. A Touchpoint Intelligence Brief containing: the customer-described process flow (their version of the journey, not yours), a ranked list of friction points with frequency, severity, and emotional impact, the expectation gaps driving friction (what customers expected versus what they got), 3-5 specific improvement recommendations with customer evidence supporting each one, and before/after projections for how addressing each friction point would affect the relevant satisfaction metric.
The Journey Probe’s value multiplies when used systematically. Running Journey Probes across 8-12 key touchpoints over the course of a year builds a comprehensive, evidence-based customer journey map that reflects actual customer experience rather than internal assumptions. This evidence-based journey map becomes a strategic asset that guides investment allocation, feature prioritization, and process improvement across the organization.
How Do You Build a Continuous CX Intelligence Program?
The first three plays are discrete research initiatives, specific studies you run in response to specific needs. The Continuous Intelligence Program is the operational framework that ties them together into an always-on research capability. This is where CX research stops being a project and becomes a function. It is the difference between having a research team that answers questions when asked and having an intelligence system that continuously surfaces the insights your organization needs to improve customer experience.
Building a continuous program requires three structural decisions. The first decision is what triggers research automatically. The most effective triggers are customer events that signal opportunities for learning: a detractor NPS score triggers a Detractor Deep-Dive interview, a churn event triggers a Churn Autopsy interview, a support escalation triggers a Journey Probe of the support experience, and a completed onboarding triggers an onboarding Journey Probe. These event-based triggers ensure research is always running, always timely, and always focused on the moments that matter most.
The second structural decision is how findings are distributed and acted upon. Research intelligence that lives in a report read by three people has minimal organizational impact. Continuous programs need distribution mechanisms that put findings in front of decision-makers at the moment they are making decisions. This means integrating research findings into weekly CX team standups, monthly product reviews, quarterly business reviews, and real-time dashboards. User Intuition’s Intelligence Hub supports this by making all findings searchable and queryable, so any team member can pull relevant customer evidence when they need it.
The third structural decision is how you measure the program’s impact. Track three categories of metrics. Input metrics measure research volume: how many interviews per month, how many studies, what percentage of detractors and churned customers are being interviewed. Output metrics measure intelligence quality: how many actionable findings per study, how quickly findings are distributed, and how many unique stakeholders access the intelligence hub. Outcome metrics measure business impact: which research findings led to specific improvements, what was the measured impact of those improvements, and what is the cumulative ROI of the research program.
A well-designed continuous CX intelligence program, leveraging User Intuition’s $20 per interview pricing, 48-72 hour turnaround, 4M+ global participant panel across 50+ languages, and 98% participant satisfaction rate, costs less annually than a single traditional consulting engagement while producing orders of magnitude more customer understanding. The platform’s G2 rating of 5.0 reflects the experience of teams that have made this transition from periodic research to continuous intelligence, discovering that the compounding value of accumulated customer evidence far exceeds the impact of any individual study.
The playbook is simple. The Detractor Deep-Dive explains why scores drop. The Churn Autopsy explains why customers leave. The Journey Probe explains why specific experiences fail. And the Continuous Intelligence Program ensures you are always learning, always improving, and always building on everything you have learned before. Start with the play that addresses your most urgent gap, run it this week for under $1,000, and expand from there.
Frequently Asked Questions
Which playbook play should a CX team run first?
Start with whatever is causing the most urgent business pain. If churn is accelerating, run a Churn Autopsy. If NPS dropped, run a Detractor Deep-Dive. If a specific touchpoint is generating complaints, run a Journey Probe. At $20 per interview with 48-72 hour turnaround, you can run your second play the following week rather than waiting until next quarter. Most teams start with the Detractor Deep-Dive because it addresses the most universal CX gap.
How do CX teams scale from running individual plays to a full continuous intelligence program?
Start with one play, refine it over two to three months, then layer in additional plays. Most teams begin with the Detractor Deep-Dive, add the Churn Autopsy in month two, introduce Journey Probes in month three, and establish the Continuous Intelligence Program framework by month four. The cross-functional intelligence sharing workflow develops naturally as other teams see the value of the findings and request access.
What tools does a CX team need beyond the research platform to execute this playbook?
Three things: User Intuition for the AI-moderated interviews, access to your CRM for customer segmentation and automated triggers, and a shared workspace such as Notion or Confluence for documenting findings and tracking action items. No specialized research tools, statistical software, or dedicated research analysts are required. The platform handles moderation, transcription, analysis, and evidence tracing automatically.
How quickly do CX teams see measurable business impact from this playbook?
Most teams identify actionable root causes from their first study within the first week. Implementing fixes for the top findings typically produces measurable NPS improvement within one quarter. CX teams running continuous Churn Autopsy programs consistently report 15-30% retention improvements within 6-12 months because they are addressing actual causes of churn rather than assumed ones, with each monthly study refining the understanding further.