January 27, 2026

GLG's Opaque Credit System: How It Masks the True Expense of Expert Calls

GLG's credit-based pricing model creates a layer of complexity that can obscure actual costs of expert interviews. This article examines how this opaque system affects budgeting, comparing it with transparent alternatives that help teams build their own research networks rather than rent access.

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When conducting market research, the clarity of your investment should match the clarity of the insights you're seeking. Yet for many teams relying on expert networks like GLG (Gerson Lehrman Group), the true cost of knowledge acquisition remains hidden behind an elaborate credit system that transforms straightforward transactions into complex calculations.

The Credit System Explained: A Layer of Abstraction

GLG, like several traditional expert networks, operates using a credit-based model rather than straightforward dollar amounts. In this system:

  • Credits are purchased upfront in large bundles
  • Each expert interaction costs a variable number of credits
  • Credit values fluctuate based on expert seniority, call duration, and other factors
  • Credits typically expire within a contractual period

At first glance, this might seem like a convenient way to streamline the purchasing process. However, this abstraction layer serves another purpose: it effectively masks the true dollar-per-minute or dollar-per-call costs of your research activities.

The Hidden Costs Behind Credit Pricing

Difficulty in Budget Planning

When your team can't easily translate credits to dollars, forecasting and budgeting become challenging exercises. Marketing and product teams often find themselves in difficult positions:

"We need to conduct 15 more interviews, but we're not sure if our remaining credits will cover them."

"The CFO is asking for the per-interview cost, but all I can provide is a credit consumption rate."

According to research from the Market Research Society, transparent pricing models lead to more efficient research spending, with organizations reporting 18-24% better budget utilization when costs are clearly understood.

The Broker Markup Reality

The credit system obscures a fundamental truth about traditional expert networks: you're paying a significant premium for the broker layer. When GLG connects you with experts, you're not just paying for the expert's time—you're paying for:

  1. GLG's expert recruitment and vetting
  2. Account management
  3. Administrative overhead
  4. Profit margin

Industry analysts estimate that in many cases, the expert receives only 30-40% of what clients ultimately pay, with the remainder going to the broker's operations and profit.

The Expiration Pressure

Credits typically come with expiration dates, creating artificial pressure to use them before they disappear. This urgency can lead to:

  • Rushed research decisions
  • Sub-optimal expert selection
  • Conducting unnecessary interviews to avoid "losing" credits

A Harvard Business Review analysis of subscription models found that expiring credits create a psychological pressure that often leads to lower-quality decision making and less strategic resource allocation.

The Cost of Renting vs. Owning Access

Perhaps the most significant hidden cost in the GLG model is more structural than financial: you're perpetually renting access rather than building your own research network.

When you pay GLG for expert access:

  • The relationship remains owned by GLG
  • Future contact requires going through GLG again
  • The valuable network connections don't become your asset

This creates a dependency cycle where your team never develops its own research capabilities or network assets, remaining perpetually reliant on the broker layer.

Alternative Models: Transparency in Research Costs

The market has evolved beyond the traditional broker model, with newer platforms offering more transparent approaches:

Direct Pricing Models

Some newer platforms offer clear per-interview or per-hour pricing without the abstraction of credits. This allows for straightforward budgeting and clear ROI calculations.

Network-Building Platforms

Perhaps most disruptively, tools like 28Experts are changing the game entirely by helping teams conduct outreach through their own LinkedIn accounts. This approach:

  • Eliminates the broker markup
  • Creates transparent, predictable costs
  • Allows teams to keep the connections they make
  • Builds a lasting research asset rather than a temporary rental

Making the Switch to Transparent Research Costs

Transitioning from GLG's credit system to more transparent alternatives requires some strategic planning:

Audit Your Current Research Spend

Calculate your effective per-interview cost by dividing your total GLG investment by the number of completed interviews. This baseline helps you evaluate alternatives.

Consider Your Research Needs

If your research requires extremely niche experts that only firms like GLG can access, the premium might be justified. However, for many B2B research needs, direct outreach platforms may provide comparable or better results at lower costs.

Test Alternative Approaches

Many teams find success with a hybrid approach, using traditional firms for highly specialized needs while building their own research capabilities for ongoing needs.

Conclusion: From Opacity to Ownership

The shift from opaque credit systems to transparent, network-building research tools represents more than just a pricing change—it's a fundamental shift in how organizations approach knowledge acquisition.

By moving from renting access through credit systems to building your own research network, your team not only gains cost clarity but also develops a lasting asset that grows in value over time.

The most valuable insight might not come from any single expert call, but from recognizing that in today's connected world, you no longer need to pay a premium to access the knowledge you seek. The choice between renting access and building your own network has never been clearer—or more consequential for your research budget and capabilities.

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