Start Here: Your Current CX Reality

• Who formally owns customer experience and which executive KPIs do they report on? Options: Chief Customer Officer / VP CX, Head of Operations, Head of Contact Center, Head of Digital/Product, Chief Marketing Officer, Shared/Matrixed ownership, Other
• Which 2–3 customer journeys are you most focused on improving this year (e.g., onboarding, billing dispute, service recovery)? Options: Onboarding / new account setup, Billing & invoices, Service activation/installation, Technical support / troubleshooting, Service recovery / complaints, Returns/refunds, Loyalty/retention interactions, Other
• How often do you review CX performance and with which audience (e.g., weekly ops, monthly execs)? Options: Weekly — operations, Biweekly — cross-functional, Monthly — executives, Quarterly — board-level, Ad-hoc when issues surface, We don't have a regular cadence
• Which systems currently contain the feedback and signals you trust (select all that apply)? Options: Contact center surveys (post-call), Contact center transcripts, Digital analytics / session replay, Email/CSAT campaigns, NPS surveys, Social monitoring tools, CRM / support tickets, Other
• Describe a recent example where a customer experience issue produced a real business consequence (lost revenue, churn, escalated costs). Tell us what happened and why it mattered.

What’s Losing You Customers Right Now?

• If you had to point to the single experience that is costing the most customers and revenue today, which journey or touchpoint would that be? Options: Billing disputes, Onboarding friction, Repeated IVR transfers, Failed digital payments, Service outage response, Complaint handling/escalations, Other
• How do you currently quantify the impact of that failure (est. churn rate, cost per contact, average lifetime value lost)? Options: Churn rate estimates, Contact volume / AHT increase, Revenue loss per incident, Customer lifetime value (LTV) impact, We have anecdotal estimates only, We cannot quantify today
• Who first raised this specific problem—front-line managers, analytics, marketing, CFO, or customers themselves—and how persistent has it been? Options: Front-line managers, CX analysts, Product/engineering, Marketing/CRM, Finance/CFO, Customers/advocacy, Other
• How often do customers experience this problem (daily, weekly, <1% of interactions) and which segments are most affected? Options: Very frequently (daily), Often (weekly), Occasionally (monthly), Rarely (<1% of interactions), Unknown / not measured
• What’s the most common customer response when this happens (churn, repeat contact, social complaint, write-in), and which response scares leadership the most? Options: Churn / account closure, Repeat contacts/queues, Refunds/credits requests, Negative social media/posts, Regulatory complaints, Other

When the Data Doesn't Tell the Full Story

• Where do feedback sources contradict each other and leave you with uncomfortable blind spots? Options: Survey scores look fine but contacts spike, Digital metrics disagree with support transcripts, NPS differs by channel, Social complaints outpace internal logs, We don't see contradictions clearly
• Which feedback sources do you consider high-quality vs. low-confidence today (select all that apply) and why? Options: Post-call surveys — high confidence, Transcripts — high confidence, Digital session data — mixed, Email/NPS campaigns — mixed, Social listening — low confidence, Customer complaints — high confidence, Other
• How accessible is raw feedback for analysis (easy access to transcripts and session data, significant ETL required, legal barriers)? Options: Immediate access to raw data, Some connectors but ETL needed, Significant data engineering effort, Legal/security blocks access, Unknown — needs investigation
• Who owns data quality and tagging for feedback (analytics, CX ops, vendor) and how long does fixing a data issue typically take? Options: Analytics team, CX operations, IT / Data engineering, Third-party vendor, Shared responsibility, Unknown
• Give an example of a time you discovered a hidden driver in unstructured feedback that changed your approach—what was found and what changed?

Who's Really Deciding?

• If the CFO asked for a dollar-and-cents case for improving a journey tomorrow, what evidence would you be missing to answer them confidently? Options: Quantified churn impact, Estimated LTV improvements, Operational cost savings (AHT, contacts), Validated statistical model, Executive sign-off/ownership, We could already answer
• Which people need to be convinced for a funded rollout (select all that apply) and what does each person require to be persuaded? Options: CFO — financial ROI, COO — ops feasibility, CIO — data/security, Head of CX — customer outcomes, Legal/compliance — data agreements, Front-line managers — operational fit
• What timeline does finance expect for ROI from a pilot (60 days, quarter, year), and how flexible are they? Options: ~60 days, Quarter (90 days), Two quarters, One year, No firm expectation / exploratory
• Who on your analytics team will validate methodology and models, and how do they prefer to see proofs (code, whitepapers, reproducible notebooks)? Options: In-house data science, Center of excellence, External consultants, Vendor-provided black-box, We have no preference / unsure
• How would you describe the CFO/finance tolerance for model uncertainty—do they need conservative lower-bound estimates, full probabilistic ranges, or a single point estimate? Options: Conservative lower-bound, Probabilistic range, Single point estimate, Depends on context, Unsure

Imagine a Pilot That Actually Converts Skeptics

• What would make a 60–90 day pilot undeniably persuasive to your COO or CFO—what exact outcome changes would flip a budget decision? Options: Clear churn reduction %, Contact volume decrease %, Net revenue retention improvement, Reduced operational cost ($), Customer satisfaction lift (CSAT/NPS), Combination of the above
• Which 2–3 specific journeys should we pilot to deliver the fastest, cleanest signal of value? Options: Billing disputes, Onboarding, Technical support, Service recovery/escalations, High-value customer retention, Digital checkout/payment flows
• What success metrics would you require for pilot acceptance (select up to 3)? Options: % churn reduction, % contact volume reduction, Incremental revenue or saved revenue ($), Customer satisfaction uplift (CSAT/NPS), Reduction in repeat contacts, Time to resolution improvement
• Who should be the accountable owner for the pilot (name or role), and who will run day-to-day operations? Options: VP/Head of CX, Head of Analytics, Head of Contact Center Ops, Product/Engineering lead, Program Manager, Other — please specify
• What minimum data connectors and samples must be available before we start (transcripts, CRM, billing, digital session data)? Please list any hard blockers.

What Could Break the Pilot Before It Starts?

• What's the single most common reason pilots stall here—data access, security concerns, competing priorities, or something else? Options: Data access / ETL delays, Security / privacy approvals, Lack of clear owner, Overloaded analytics team, Competing executive priorities, Legal / vendor contracts
• What security or compliance requirements will our platform need to meet (SOC2, ISO, encryption, data locality), and how long does that review typically take? Options: SOC2, ISO 27001, GDPR/DPAs, Encryption at rest & transit, Data residency requirements, Other / custom requirements
• Can you provide a realistic estimate for how long approvals take (data, legal, procurement) and which group usually causes the longest delay? Options: <2 weeks, 2–4 weeks, 1–2 months, 2+ months, Unpredictable
• What sample size and timeframe do you consider sufficient to validate a predictive model on a given journey? Options: 1–2 weeks of data, 4–8 weeks, Quarter of historical data, 6+ months, Depends on journey
• List any integration/APIs that are mandatory for this pilot (e.g., Genesys, NICE, Salesforce, Google Analytics) or any vendor we cannot integrate with.

Agreeing Next Steps — From Conversation to Commit

• If we left this meeting with one immediate next step you could approve, what would make it impossible for you to say no?
• What decision cadence do you prefer for pilot governance (weekly scrum, biweekly steering committee, monthly exec review)? Options: Weekly — working team, Biweekly — steering, Monthly — execs, Ad-hoc as needed, Prefer vendor to lead cadence
• Who must sign off for scope, data sharing, and budget (names or roles), and what is the expected timeline for each approval?
• What level of commercial transparency does finance require up front (high-level estimate, line-item budget, full TCO), and do you have a preferred procurement route? Options: High-level estimate, Line-item budget, Full total cost of ownership, Use existing vendor procurement, Other
• What would success look like at pilot close that would make you confident to scale (specific thresholds, stakeholder endorsements, or an executive memo)?

A quick map: Where is customer feedback actually living right now?

• Which channels do you currently collect feedback from (pick all that apply)? Options: Contact center surveys (post-call/IVR), Contact center transcripts/recordings, Email surveys (CSAT/NPS), In-app/product analytics feedback, Web feedback widgets, Chatbot transcripts, Social media mentions/comments, Online reviews (third-party sites), Field/service technician notes, Other
• Roughly how many feedback items do you receive per month across all channels? Options: < 1,000, 1,000–10,000, 10,000–100,000, 100,000–1,000,000, 1M+
• Which single channel generates the largest volume of meaningful feedback for the journeys you care about? Options: Contact center transcripts, Post-call surveys, Digital in-app feedback, Web chat transcripts, Social media, Email surveys, Other
• Who on your team is currently responsible for collecting or owning each channel (briefly list role/team next to the channel)?
• Can you share one recent example where a customer comment from any channel changed how a team acted (what happened and what changed)?

Are your scores telling the truth — or just keeping everyone comfortable?

• When you look at your overall CSAT/NPS trends, how often do those trends correlate with real business signals like churn, repeat contact, or revenue loss? Options: Almost always, Often, Sometimes, Rarely, Never
• Tell me about a time when a high-level score masked a serious operational problem—what did you miss and who noticed it later?
• Which feedback source do you think is the most misleading (produces false positives/negatives), and why? Options: Post-call surveys, Short NPS emails, Digital session ratings, Social media volume, Verbally collected feedback, Other
• How often do analytics or CX teams try to match feedback to downstream behavior (e.g., did the unhappy customer churn, call back, or cost more)? Options: Weekly, Monthly, Quarterly, Ad hoc, Never
• If we could point to the single experience driver that is most predictive of churn for one journey, how would that change leadership’s willingness to invest? Options: Immediate funding approval, Pilot funding only, Need more evidence, No change

Who really owns the data — and the power to act on it?

• Which teams or roles currently own raw feedback data, dashboards, and any derived analytics (select all that apply)? Options: CX/Insights team, Contact Center Ops, Digital/Product Analytics, Marketing, IT/Engineering, Data Science/BI, Customer Success/Account Management, Other
• How easy is it today for a CX analyst to get a month of raw transcripts or session data for a pilot? Options: Same day, Within a week, 2–4 weeks, Longer than a month, Not possible
• What formal agreements or approvals (e.g., DPA, security review) are required before a third-party analytics tool can access sample data?
• Is there a single data steward or cross-functional contact we should plan to work with during discovery and a pilot? Options: Yes—single contact identified, Yes—team but no single owner, No, we need to assign one, Unsure
• Are there any legacy systems or black-box platforms that routinely block access to customer feedback? If so, which and why?

When feedback fails, where does the bill come due?

• Which failure modes have you seen most often when customer feedback doesn’t lead to action (pick all that apply)? Options: No clear owner for issues, Data silos / no integration, Low signal-to-noise in feedback, Slow access to historical data, No operational playbooks, Leadership skepticism, Poor tagging/metadata, Other
• Describe a recent instance where a failure mode caused visible business impact (increased churn, repeat contacts, regulatory complaint, cost overruns). What was the impact?
• How do front-line teams surface recurring issues today, and how long does it typically take from identification to any corrective action? Options: Same day, Within a week, 2–4 weeks, Months, Never
• Who gets escalated to when a repeat contact or high-risk complaint is identified? (role names or teams)
• If you had to estimate, what percentage of repeat contacts or avoidable churn do you suspect are caused by the top two failure modes you've selected? Options: <5%, 5–10%, 10–25%, 25–50%, 50%+

What are you already trying — and why hasn’t it scaled?

• Which tools or approaches are you currently using to analyze unstructured feedback (select all that apply)? Options: In-house NLP, Vendor sentiment tools, Manual tagging/agents, Rule-based text analytics, No tools—manual review only, Other
• Have you piloted linking feedback to outcomes (churn, LTV, VOC-driven cost) before? If yes, what did the pilot show and why didn’t it expand? Options: Yes—showed strong linkage, Yes—weak/no linkage, No pilot yet, Pilot incomplete
• Who on your team runs or validates models that claim to predict churn or revenue impact from feedback? Options: Data Science, Analytics/CX Insights, Third-party vendor, No one currently, Other
• What has been the biggest blocker to taking a successful pilot to production (pick one)? Options: Data access, Executive buy-in, Operational integration, Scale/engineering effort, Budget, Compliance/security
• Share one short example of a change you implemented from feedback that stuck—what enabled it to succeed?

If a clear signal could show which experience drives the most revenue loss, what would that enable?

• Which measurable outcomes would you need to see from a proof-of-value to feel confident expanding the program? Options: Reduction in churn (%), Decrease in repeat contacts (%), Lower cost-to-serve ($), Increase in retention LTV ($), Improved NPS/CSAT tied to revenue, Other
• Which 2–3 customer journeys would you prioritize for a 60-day pilot (choose examples or add your own)? Options: Onboarding/activation, Billing and disputes, Outage/service interruptions, Returns/refunds, Service recovery, Subscription cancellation flow, New device provisioning, Other
• What would you accept as minimum statistical evidence that a driver predicts churn or repeat contact (e.g., lift, p-value, effect size, dollars per customer)? Options: Pre-defined % lift (we'll specify), Statistical significance + business case, Top drivers with qualitative validation, Unsure—need vendor guidance
• Who needs to be convinced by the pilot results (names or roles), and what does each person need to see to sign off?
• If the pilot proved an answer that saved X% in churn-related revenue loss, how would that budget request be routed (operating budget, transformation, CFO sign-off)? Options: Operating budget, Reallocation within CX, CFO/Finance approval, One-off transformation fund, Other

What would safe, fast data sharing look like for you?

• What data types can you provide for an initial model build (select all that apply)? Options: Raw contact center transcripts, Post-call survey responses, Session-level digital analytics, CRM/transactional records, Billing/financial records, Social media exports, Masked PII only, Other
• Which security or compliance constraints must we respect (e.g., PII masking, data residency, vendor security review)?
• How quickly could your team produce a 60–120 day sample dataset for a pilot once approvals are in place? Options: Immediately (within days), 1–2 weeks, 2–4 weeks, Longer than a month, Not possible currently
• Which connector types are preferred or already supported by your stack? Options: Pre-built contact center connector, SFTP/secure file drop, API access, Database extracts (secure), SIEM/ETL pipeline, Other
• Are there legal or vendor-governance steps we should prepare for up front to accelerate approvals?

Small commitments that unlock big proofs — what would you be ready to try?

• Would your team be willing to commit an owner, 2–3 SMEs, and weekly 30-minute checkpoints for a 60-day pilot? Options: Yes—already identified, Yes—but need to assign, Maybe—need executive buy-in, No
• What minimal operational changes would you accept to act on pilot findings (e.g., script changes, routing rules, targeted outreach)? Options: Immediate playbook changes, Small A/B tests only, Process redesign, No changes without lengthy approval, Other
• How would you prefer results packaged for leadership (select all that apply)? Options: Executive one-pager with $ impact, Interactive dashboard for analysts, Recorded walkthrough with examples, Operational playbook with actions, Raw model outputs and code
• Assuming the pilot hits agreed success signals, what is the earliest you could commit budget to scale the solution? Options: Immediately, Next quarter, Next fiscal year, Unsure / depends on CFO
• Who should we add to the invite for a 30-minute discovery readout to confirm scope and next steps?

Quick Check — Who's in the Room?

• Who is the primary sponsor we should keep informed, and who will be our day-to-day contact for technical delivery? Options: Chief Customer Officer, VP of CX, Head of Analytics, CIO, CISO, Program Manager, Other (please name)
• Which 2–3 customer journeys are you committing to for this pilot? Options: Onboarding, Billing disputes, Service recovery, Churn-risk journey, Claims handling, Support escalation, Other (please specify)
• What is your target timeline from kickoff to model-ready (the 60-day window is our baseline)? Options: Within 2 weeks, 2–4 weeks, 1–2 months, 2–3 months, Undetermined
• Who will need to approve budget or commercial terms if the pilot shows the expected value? Options: CFO, VP of CX/CCO, CIO, Head of Operations, Procurement, Other
• What one success signal would make the CFO comfortable treating this as a funded operating line item?
• How solid is the current budget for the pilot? Options: Fully funded, Partially allocated, Contingent on pilot, No budget yet, Unsure

Are We Sure the Data Exists?

• If I asked your data team for a representative sample from the prioritized journey(s) right now, could they hand it to me? Options: Yes — ready now, Yes — extraction needed (≤1 week), Yes — will take time (1–4 weeks), No — needs approvals, No — doesn't exist
• Which systems currently hold the feedback, interaction, and outcome data we’ll need for the model? Options: Contact center transcripts, Post-call surveys, Email/NPS surveys, CRM notes, Digital analytics (web/app), Chat transcripts, Social media listening, Billing/ops system, Other (please list)
• For the candidate datasets, do records reliably include a customer identifier, timestamp, and a measurable outcome (e.g., churn flag, revenue tag)? Options: All present, Most present, Some present, Rarely present, Unknown
• How many records per journey can you realistically provide for a pilot (approximate order of magnitude)? Options: <1k, 1k–10k, 10k–100k, >100k, Unsure
• Are there pre-built connectors or APIs we can leverage for extracts, or will this require manual exports? Options: Pre-built connectors available, APIs available but need work, Manual exports only, No integration available, Unsure
• Who is the canonical owner of the customer ID and data dictionary we should align to?

What’s Actually Flowing — Not What You Hope

• How often do projects like this hit a showstopper because a critical field was missing or misaligned between systems? Options: Never, Rarely, Occasionally, Often, Almost always
• Which specific fields or signals have historically been inconsistent or unreliable across your data sources?
• When was the last full data quality audit performed on the sources we've listed? Options: Within 30 days, 30–90 days, 3–6 months, 6–12 months, Over a year, Never
• Do transcripts and feedback exports preserve original timestamps, conversation IDs, and parent interaction links? Options: Yes — reliably, Mostly, Sometimes, No, Unknown
• How are PII and sensitive attributes handled in shared samples (automated masking, manual redaction, vendor controls)? Options: Automated masking, Manual redaction, Vendor access controls, We do not redact, Unsure
• Can you attach or provide a de-identified sample file (schema + 50–500 rows) for our schema review? Options: Yes — attached now, Yes — after approvals, No — cannot share, Unsure

Who’ll Say Yes to Data Access?

• If security or legal could block this pilot with one email, who would likely send it? Options: CISO, Legal Counsel, Data Protection Officer, Vendor Risk/Procurement, CIO, Compliance Officer, Other
• Which security standards or certifications are required for any external vendor handling your sample data? Options: SOC 2 Type II, ISO 27001, PCI DSS, HIPAA, Local data residency, No specific certification, Unsure
• What contractual documents or evidence will you require before we receive sample data (e.g., NDA, DPA, security questionnaire)? Options: NDA, DPA, MSA/SoW, Security Questionnaire, Data Flow Diagram, Other (please specify)
• Do you require the data to stay on-premises, or can we receive appropriately de-identified extracts in our cloud environment? Options: On-premises only, Cloud allowed with controls, Cloud not allowed, Unsure
• What encryption, key management, or access control practices are mandatory for transfers and temporary storage of pilot samples?
• How long does your typical internal security or legal review take for a pilot-level data access request? Options: <1 week, 1–2 weeks, 2–4 weeks, 1–2 months, Longer, Unsure

Can Analytics Validate This Model — Before We Build?

• If your lead data scientist were to push back on our approach, what would their sharpest objection be?
• Which internal analytics or data-science resources will be involved in validation and review? Options: In-house data science team, BI/Analytics team, Data engineering, Third-party consultants, No internal resources, Unsure
• Which validation standards should govern the pilot (holdout sets, cross-validation, A/B test, backtest, explainability)? Options: Holdout/validation split, Cross-validation, A/B testing, Backtesting historical events, Explainability/feature importance, Business metric uplift only, Other
• What minimum statistical or business thresholds would make the analytics team comfortable (provide metrics or targets if possible)? Options: AUC / ROC target, Precision/Recall targets, Lift vs baseline, Minimum revenue impact, Contact volume reduction target, Undefined — will discuss
• Do you require reproducible artifacts (notebooks, code review, audit logs) as part of validation? Options: Yes — full notebooks and code, Yes — summarized reproducible artifacts, Optional, No, Unsure
• Which financial metrics should the validation plan map to (choose all that apply)? Options: Revenue uplift, Retention rate improvement, Contact volume reduction, Cost-per-contact reduction, Customer lifetime value (CLTV), Other (please specify)
• Would you want a signed statistical validation plan before we start the model build? Options: Yes — required, Maybe — depends on scope, No — not required, Unsure

What Could Break the Pilot?

• Thinking of past pilots, what single operational failure caused the most surprise or delay?
• What SLAs must be met during the pilot for data delivery, model refresh, and dashboard updates? Options: Near real-time (<5min), Hourly, Daily, Weekly, Monthly batch, Other
• Which teams must be staffed and reachable during the pilot (and who covers if they are unavailable)?
• What training or change support will frontline teams need to act on model-driven recommendations? Options: Scripts & coaching, Automated workflow integration, Manager dashboards & KPI alerts, One-time training session, No training required, Other
• Are there scheduled maintenance windows, release freezes, or regulatory blackout periods we must avoid during the pilot? Options: Yes — defined windows (please detail), Possibly — varies, No regular windows, Unsure
• What escalation path should we use if data ingestion or model scoring stops mid-pilot? Options: Primary contact, IT ticketing system, Security team, Weekly executive sync, Emergency hotline, Other (please specify)

What Does ‘Good to Deploy’ Look Like?

• If you had to name three non-negotiable exit criteria for this pilot, what would they be?
• Which stakeholders must sign off on the go/no-go decision to move from pilot to wider deployment? Options: CCO / VP CX, CFO, CIO, CISO, Head of Analytics, Head of Ops, Other
• How should final acceptance be documented to satisfy finance and operations (scorecard, slide deck, signed memo)? Options: KPIs scorecard, Executive briefing with ROI, Signed acceptance email, Pilot report + recommendation, Other
• What monitoring, alerting, and rollback mechanisms do you expect post-deploy if model behavior drifts?
• Assuming the pilot meets acceptance, what is your preferred timeline and approach for scaling to additional journeys? Options: Immediate scale (within 1 month), Phased (1–3 months per phase), Quarterly cadence, Annual roadmap, Unsure
• Would you like us to prepare a tailored 'pre-deployment readiness checklist' mapping your security, legal, and analytics gates? Options: Yes — please prepare, Maybe — send a template first, No — we have our own checklist, Unsure

Setting the Table: A Short Orientation

• What's the single CX priority that has been greenlit with budget today? Options: Onboarding, Billing disputes, Service recovery, Retention/Churn reduction, Acquisition conversion, Digital experience, Other
• Which specific customer journey do you want this pilot to prove value on first? (name the journey and a one-sentence objective)
• Who will be our primary sponsor and the day-to-day champion inside your organization? Options: Chief Customer Officer / VP CX, Head of Analytics / Data Science, CIO / Head of IT, Contact Center Director, Head of Operations, Other
• How quickly are you expecting a functioning pilot (analysis + model + initial dashboards)? Options: <30 days, 30–60 days, 60–90 days, 3–6 months, Undecided
• What single metric or outcome would make the CFO comfortable signing off to expand after the pilot? Options: Reduced churn (%), Retention lift (pts), Call volume reduction (%), Operational cost savings ($), Increase in LTV ($), Increase in NPS/CSAT, Other

Are We Measuring What Matters—or Just Measuring Noise?

• What if your current CX metrics are comforting but useless to the business—what would that reveal about how you’ve been prioritizing work?
• Which feedback and interaction sources do you currently collect and rely on most? Options: Post-call surveys (CSAT), NPS/email surveys, Contact center transcripts, Chat transcripts, Digital analytics (page/session events), Social listening, Billing and transaction logs, CRM notes, Other
• Which of those sources are siloed by team today (not centrally available)? Options: Contact center platform, Digital/product analytics team, Marketing/survey team, Social/PR team, Billing/finance team, Analytics/BI, None — largely centralized, Unsure
• How often is customer feedback data refreshed and validated for analysis? Options: Real-time/streaming, Daily, Weekly, Monthly, Ad-hoc / exports only, No regular cadence
• Give a recent example where a CX metric moved but leadership saw no financial action—what was the disconnect?

Where Value Is Actually Leaking (No Sugarcoating)

• Which precise customer moment do you suspect is costing the most revenue—and why have you not been able to prove it yet?
• What supporting evidence do you already have that this moment drives churn, repeat contact, or costs? Options: Customer verbatim themes, Account closure logs, Billing dispute counts, Support volume spikes, Anecdotes only, None
• Approximately what portion of your churn or avoidable cost would you be comfortable attributing to experience issues today? Options: >50%, 20–50%, 10–20%, <10%, Unsure / No estimate
• When leadership has asked for a dollar impact before, what stopped your team from delivering it? Options: No integrated data, Attribution uncertainty, Analytics capacity, Governance/privacy limits, No clear owner, Other
• Which financial KPIs matter most to your CFO when evaluating a CX investment? Options: Churn rate, Retention lift, Customer lifetime value (LTV), Cost per contact, Refunds/credits reduced, Revenue uplift from cross-sell, Other

The Data Roadblock: Are the Pipes Open?

• If we could not get the key feedback and transaction data in 14 days, would this pilot still move forward? Options: Yes — we can prioritize access, No — access is the gating factor, Maybe — depends on which systems are blocked, Unsure
• Which systems contain the raw inputs we’ll need to model drivers of churn and cost? Options: Contact center platform (IVR/ACD), Transcription service, CRM (Salesforce, etc.), Billing and payments, Digital analytics (GA, Mixpanel), Survey platform, Social listening, Data warehouse / lake, Other
• Who owns data access provisioning and typically how long does it take to get credentials and schema access? Options: Days, 1–2 weeks, 3–6 weeks, Months, Requires legal/contract review, Unknown
• Do you have pre-built connectors or will we need custom extracts and transformations? Options: Pre-built connectors available, APIs exist but limited, Only scheduled exports available, No integrations — manual work needed, Unsure
• Which security, privacy, or governance checks must be completed before we ingest PII or customer feedback? Options: Privacy office review, Security assessment / pen test, Data processing agreement, Anonymization/pseudonymization, Vendor risk review, None / minimal, Other
• Tell us about a prior analysis that failed because of data quality or access—what broke and how long did recovery take?

Who Gets to Decide—and Who Will Make It Happen?

• If the pilot proves ROI, who signs the expansion check—and who is most likely to resist?
• Which stakeholders must be convinced to scale from pilot to program? Options: CCO / VP CX, CFO, CIO, COO, Head of Analytics, Contact Center Director, Legal / Compliance, Product / Engineering, Other
• Which stakeholder in that list is the most skeptical today, and why?
• What minimum evidence would each critical stakeholder need to feel confident (e.g., % retention lift, $ savings, demonstrable model explainability)?
• If the pilot succeeds, who will own day-to-day operations for the solution going forward? Options: Central CX team, Analytics / Data Science team, Contact center ops, Lines of business, Shared governance, Not decided yet

Proof That Moves Budgets: Define the Minimal Win

• What single, measurable outcome would turn this pilot from a proof into an ongoing program (be brutally specific)?
• Select the top 2–3 success signals we should target for the pilot to demonstrate proof-of-value. Options: Reduced churn (%), Reduced repeat contact (%), Call volume reduction (%), Reduced average handle time, Increase in NPS/CSAT, Direct cost savings ($), Increase in revenue per customer, Other
• What magnitude of improvement would the CFO consider a meaningful win for the chosen signal(s)? Options: >5% relative improvement, 3–5% relative improvement, 1–3% relative improvement, Fixed $ threshold (specify later), Unsure / need guidance
• How should we compute financial impact for your organization—retention uplift, cost avoidance, or a blended approach? Options: Retention uplift (top-line), Cost avoidance (opex), Both blended, Prefer finance to define, Unsure
• Who will be the owner responsible for validating the pilot’s financial calculation and signing off on methodology? Options: CFO / Finance, Head of Analytics, CCO / VP CX, Independent audit / FP&A, Not defined yet

What Will It Feel Like to Use This Insight?

• Imagine an agent receives a daily alert that prevents a churn—what would change for the agent, supervisor, and customer?
• Which operational levers are you prepared to change during the pilot if the model shows a clear driver? Options: Script adjustments, Proactive outreach campaigns, Escalation triggers, Refunds/credits policy, Routing rules, Training or coaching, No operational change planned, Other
• How quickly can a recommended operational experiment move from insight to live A/B test? Options: Within hours, 1–3 days, 1–2 weeks, 3–6 weeks, Longer / depends
• What tools do frontline teams currently use to view feedback-driven actions (so we can map delivery channels)? Options: CRM dashboards, Custom agent dashboards, Workforce management tools, Email/notify workflows, None / manual, Other
• Share a short example when a small operational tweak led to a measurable customer improvement.

Risks, Roadblocks, and the Real Dealbreakers

• What single technical or political risk would kill this project overnight?
• Which risks are you most concerned about for this pilot? Options: Data access delays, Legal / privacy objections, Model explainability to execs, Lack of operational buy-in, Analytics capacity, Competing priorities / budget, Vendor lock-in concerns, Other
• How comfortable is your analytics team explaining predictive models and driver impact to non-technical executives? Options: Very comfortable, Somewhat comfortable, Not comfortable, No analytics team, Prefer external explanation
• What mitigation (e.g., documentation, CFO workshop, gating criteria) would make leadership comfortable proceeding?
• If we hit one unexpected blocker during the pilot, who has authority to reallocate resources or escalate decisions? Options: CCO / VP CX, CFO, CIO, Program sponsor / steering committee, No clear escalation path, Other

Agreement & Next Steps: What We're Asking For

• If we asked for three immediate commitments to get the pilot started this week, what would you say yes to?
• Which of the following can you commit to within 2 weeks to unblock the pilot? Options: Data access approvals, Deliver sample dataset, Sponsor kickoff meeting, Start legal/privacy review, Dedicated analytics time, Agent access for experiments, None of the above
• Which of these items will likely take longer than 2 weeks and need planning? Options: Legal / DPA signing, Security review, Custom connector build, Provisioning live data, Executive alignment workshop, Other
• What cadence do you prefer for check-ins and pilot reviews? Options: Weekly, Bi-weekly, Monthly, Milestone-based (kickoff, mid-point, results), Ad-hoc as issues arise
• Before we finish, are there any immediate questions, objections, or conditions you want addressed so you can confidently say yes to a pilot?