GLG vs User Intuition: Expert Opinions vs Actual Customer Evidence for Due Diligence

The distinction between expert opinions and customer evidence is the most important concept in modern commercial due diligence, and it is the core difference between GLG and User Intuition.

GLG connects deal teams with industry experts—former executives, consultants, regulators, and practitioners who have deep knowledge of specific markets. A typical PE engagement involves 10-20 expert calls over 2-4 weeks, each lasting 30-60 minutes. Experts share their perspectives on market size, competitive dynamics, regulatory risks, technology trends, and growth drivers. This is genuinely valuable context for understanding the landscape in which a target operates.

User Intuition interviews the target company's actual customers—or customers of comparable companies when lists are unavailable. The platform conducts 50-200 AI-moderated interviews in 48-72 hours, each applying 5-7 level laddering methodology to uncover not just what customers do, but why they do it, what would make them leave, and what would make them buy more. The output is IC-memo-ready: quantified retention risk, growth thesis validation, competitive positioning evidence, and NPS benchmarking.

The gap between these approaches becomes clear in practice. An industry expert might say: "Customer retention in this SaaS vertical is typically 85-90%, and the competitive landscape is consolidating." That is an informed opinion. A customer due diligence study might reveal: "37% of the target's customers are actively evaluating alternatives, citing implementation complexity and unresponsive support. The top competitive threat is not the obvious market leader but a mid-market challenger offering a simpler product at 40% lower cost." That is customer evidence.

Both are useful. Neither replaces the other. But when a deal team needs to understand whether customers will stay, grow, or churn after an acquisition, expert opinions about the market cannot substitute for evidence from the customers whose behavior will determine the outcome.

Reliability depends on the question being asked and the proximity of the data source to the answer.

GLG's reliability strengths:

• Regulatory context: Former regulators and policy experts provide firsthand knowledge of regulatory frameworks, enforcement patterns, and upcoming changes. This is expert knowledge that customers simply do not have.
• Market sizing: Practitioners who have operated in a market for decades can provide informed estimates of market size, growth rates, and segmentation. Their experience adds nuance that desk research cannot match.
• Competitive landscape: Former executives at competitor companies can describe strategies, capabilities, and vulnerabilities from the inside. This is proprietary intelligence not available from other sources.
• Technology trends: Technical experts can assess the viability of a target's technology, potential disruptions, and technical debt with credibility.

GLG's reliability limitations for customer questions:

• Experts opine on what they think customers value; customers describe what they actually experience
• Expert knowledge can be outdated—market dynamics shift faster than practitioner networks update
• Experts have inherent biases: anchoring to their own experience, pattern-matching to familiar situations, and recency effects from recent projects
• Small sample size (10-20 calls) means individual expert perspectives carry outsized weight, including their blind spots
• Compliance constraints mean some experts cannot discuss certain topics in detail

User Intuition's reliability strengths for customer questions:

• Direct source: Customers describe their own experience, not someone else's interpretation of it
• Scale: 50-200 interviews provide statistical confidence—you can distinguish signal from noise
• Systematic methodology: 5-7 level laddering uncovers motivations that customers themselves may not articulate unprompted
• Behavioral evidence: Customers report their actual usage, switching behavior, and purchase intent—not hypothetical market dynamics
• Quantifiable patterns: With 100+ interviews, themes can be quantified: "43% of customers cited X as their primary retention driver" is more actionable than "our expert believes retention is driven by X"

The bottom line: for questions about the market, ask market experts. For questions about customers, ask the customers.

The pricing gap between these platforms is dramatic, but context matters—they deliver different types of intelligence.

GLG pricing:

• Expert calls: $1,000-$2,000 per hour per expert
• Typical PE engagement: 10-20 calls = $50,000-$200,000
• Additional costs: Project management fees, rush scheduling premiums
• Expert surveys: Separate pricing for quantitative polling
• Value proposition: Access to scarce expertise that would otherwise be unavailable

User Intuition pricing:

• Per interview: $20/interview
• Typical PE study: 50-200 interviews = $2,000-$15,000
• No platform fees, no per-seat charges, no monthly subscriptions
• Enterprise plans available for portfolio-wide programs
• Value proposition: Actual customer evidence at a fraction of traditional research costs

The 10-40x pricing difference reflects fundamentally different economics. GLG's value is access—connecting you with specific individuals whose expertise would otherwise be inaccessible. That scarcity commands premium pricing. User Intuition's value is evidence at scale—technology enables hundreds of deep customer conversations at marginal cost per interview.

For PE firms, the relevant comparison is the cost of the total diligence workstream. A customer due diligence program using GLG might involve 5-10 expert calls focused on customer dynamics, costing $25,000-$50,000, and still delivering expert opinions about customers rather than customer evidence. The same budget funds 1,250-2,500 actual customer interviews through User Intuition—orders of magnitude more data from the direct source of truth.

Many PE firms are discovering that dedicated customer due diligence provides higher-conviction insights per dollar spent than additional expert calls when the question is about customer behavior. This does not mean expert calls are overpriced—it means the two platforms serve different functions and should be budgeted accordingly.

Speed matters in PE diligence because deal timelines are compressed. The exclusivity period is finite, and investment committees need evidence before they need opinions.

GLG timeline:

• Days 1-3: Define expert requirements, submit project brief, begin expert sourcing
• Days 4-10: Expert screening, compliance checks, scheduling first calls
• Days 7-21: Conduct 10-20 expert calls (scheduling depends on expert availability)
• Days 14-28: Synthesize findings across calls, prepare deliverables
• Total: 2-4 weeks from kickoff to usable insights

The timeline is driven by logistics: experts have day jobs, scheduling across time zones is complex, and each call requires preparation and follow-up. Rush timelines are possible but cost more and may compromise expert quality.

User Intuition timeline:

• Hour 1: Study design and launch (as little as 5 minutes for experienced users)
• Hours 2-12: First interviews complete; initial themes visible in real time
• Hours 12-48: Bulk of interviews completed; quantified patterns emerge
• Hours 48-72: Full study complete with IC-memo-ready deliverables
• Total: 48-72 hours from launch to complete customer evidence package

This speed difference is not just a convenience—it changes what is possible within a deal timeline. A deal team that learns about a target on Monday can have 100+ customer interviews analyzed by Thursday. With GLG, the same team might still be scheduling their first expert calls.

For PE firms running multiple deals simultaneously, User Intuition's speed enables customer due diligence on every deal, not just the ones with long enough timelines. This shifts customer evidence from a "nice to have" to a standard diligence workstream.

Retention risk is the single most important customer-level question in most PE acquisitions. If customers churn post-acquisition, the growth thesis collapses regardless of how attractive the market looked.

What GLG provides for retention analysis:

• Industry-level retention benchmarks from practitioners ("SaaS companies in this vertical typically see 85-90% net retention")
• Expert hypotheses about what drives retention in the sector ("in my experience, customers stay because of switching costs and integration depth")
• Competitive context that may affect retention ("if Competitor X launches their new product, retention across the category could decline")
• Perspectives from former employees of the target who may have insights into customer satisfaction

This is useful context, but it is fundamentally indirect. An expert saying "retention should be fine" is not evidence that retention will be fine.

What User Intuition provides for retention analysis:

• Direct evidence from 50-200 of the target's actual customers (or comparable customers) on satisfaction, loyalty, and switching intent
• Quantified retention risk: "34% of customers have evaluated alternatives in the past 6 months; 18% are actively considering switching"
• Root cause analysis through laddering: not just whether customers might churn, but why—and what specific experiences drive that risk
• Competitive vulnerability mapping: which competitors are winning consideration, on what dimensions, and at what price points
• Segment-level analysis: retention risk varies by customer segment, and knowing which customers are at risk matters as much as the overall number
• Verbatim evidence for IC memos: "The platform works fine but their support has deteriorated since the last funding round. I'm waiting to see if it improves before I look at alternatives."

The gap is not subtle. Expert opinions about retention are predictions. Customer evidence about retention is data. When an investment committee is deciding whether to deploy $200M, the distinction between prediction and data matters enormously.

GLG's contribution: Market sizing from practitioners, growth driver analysis, competitive intelligence from former competitor executives (strategies, R&D priorities, capabilities), and expansion feasibility assessment. GLG answers 'Is the market growing?' with longitudinal expert perspective.

User Intuition's contribution:

• Expansion intent: Do customers plan to increase usage, upgrade, or buy more? Direct evidence, not expert speculation
• Pricing power: How price-sensitive are customers? What would they pay more for?
• Unmet needs: What do customers wish the product did? These gaps are both growth opportunities and competitive vulnerabilities
• Competitive perception: Which competitors do customers actually consider? Often the real threats are not the ones industry experts assume
• Switching triggers: What specific experiences cause customers to evaluate alternatives?

The most dangerous competitive blind spot is assuming the industry view matches the customer view. GLG experts might identify Competitor A as the primary threat. Customer interviews might reveal Competitor B — a smaller player with better experience — is winning consideration among the target's most valuable segments.

An expert might say: 'This market grows at 15% annually.' Customer interviews reveal: '62% plan to increase spend 20%+ next year, but only if the target addresses data export limitations — which 3 of 5 competitors already offer.' The expert validates the market; the customers validate whether the company can capture it.

A practical combined workflow:

• Week 1: Launch User Intuition study (results in 48-72 hours) while GLG begins expert sourcing
• Week 1-2: Customer evidence arrives — retention risk and growth thesis assessment ready for deal team
• Week 2-3: GLG expert calls provide market context, regulatory perspective, and competitive intelligence that frames customer findings
• Week 3-4: Synthesis: customer evidence + market context = comprehensive commercial due diligence

This creates natural checks. If experts say retention is strong but interviews reveal switching risk, the deal team surfaces a critical finding neither source alone would provide.

On security: GLG's compliance addresses expert network risks — conflict checks, insider trading prevention, monitored calls, confidentiality protocols. User Intuition's compliance addresses research data protection — ISO 27001, GDPR, HIPAA compliance, SOC 2 in progress, end-to-end encryption, multi-layer fraud prevention (bot detection, duplicate suppression), and participant anonymization. Both meet the security bar required for institutional PE diligence.

For PE firms running multiple deals: User Intuition's Intelligence Hub compounds customer evidence across portfolio companies, building institutional knowledge that grows more valuable over time. GLG expert calls are discrete engagements without persistent knowledge accumulation.