Why Shapley Regression Is Better for Reputation Driver Analysis

In an era where brand perception can shift overnight, understanding what truly drives reputation has never been more important. Yet many organisations still rely on surface-level tools like correlations or stepwise regression to assess reputation drivers. These methods often miss the mark — especially when variables are interdependent or when subtle factors influence outcomes.

Shapley regression changes that.

Originally developed in game theory, Shapley regression attributes the contribution of each variable by evaluating all possible combinations of inputs. This method provides a fair and reliable estimate of how much each factor contributes to an outcome — in this case, brand reputation.

Why It Matters

Reputation is shaped by a complex mix of leadership, ethics, innovation, social responsibility, customer treatment, and employee experience. These elements often overlap. Traditional models struggle to isolate their true impact. Shapley regression solves this by accounting for interdependencies and showing how each driver performs in all contexts.

For example:

• Microsoft used Shapley-based attribution to evaluate the impact of environmental initiatives on stakeholder trust. The result? Sustainability efforts accounted for more than twice the reputational impact of advertising.

• Unilever discovered that internal employee engagement — not just external sustainability messaging — had a measurable effect on public trust and brand admiration.

• Salesforce applied driver analysis to understand the reputation risk of leadership changes. While initial assumptions pointed to product strategy, it turned out that visible ethical leadership was the dominant trust driver.

• Patagonia, widely respected for its sustainability stance, used advanced analytics to test what most influenced its reputation. Surprisingly, it wasn’t only eco-certifications — it was the company's consistent legal challenges against environmentally harmful policies that resonated most.

Who Uses It?

Global brands across industries — from tech to FMCG to non-profits — are now using Shapley regression in their analytics teams and with external insight partners. The method is especially valued in reputation risk analysis, stakeholder trust modelling, and corporate affairs reporting.

The Bottom Line

If you’re still relying on basic statistics to uncover your brand's most important reputation drivers, you're missing critical insights. Shapley regression offers not only mathematical rigour but the ability to surface unexpected, actionable truths about what your stakeholders really value — and why they trust you.