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We Analyzed 834,000 Coaching Actions. AI-Guided Coaching Wins by Double Digits

Does more coaching automatically mean better performance? Not on its own. Our analysis shows that AI-guided coaching, where AI tells managers who to coach and on what, outperforms unassisted coaching by double digits.

Contributors: Melissa Chang Esposito, Senior Director of Customer Success at Centrical

This article is part of the Centrical Labs series, where we publish findings from our data research team. We study how frontline behavior actually changes using proprietary data from the Centrical platform and established behavioral science research on motivation and habit formation, then share the results to help you increase your team’s success. Subscribe and follow Centrical on LinkedIn to stay updated on the latest insights. 

Two managers put in the same coaching hours. One moves their team’s performance; the other barely moves the needle. Across 834,000 coaching interactions, we found what separates them.

The coaching that moved performance targeted the right person on the right metric, and AI guidance is what made that targeting possible at scale. For this analysis, we examined the coaching practices of 2,750 frontline coaches using the Centrical platform over six months. AI-guided coaching beat unassisted coaching by double digits. 

The Challenge: Too Little Time to Coach Everyone 

Frontline managers already know coaching drives performance. What they lack is time. 

A single team leader typically oversees 12-20 people, each with a different mix of strengths and gaps across dozens of KPIs. Coaching each of them consistently is close to impossible in a normal week. 

So coaching often defaults to a select group: the new hires, the bottom performers, or the agent who just handled a difficult escalation with an angry customer. Everyone else slips out of view. 

Inside Centrical Labs: How We Ran the Analysis

We compared AI-guided coaching to unassisted coaching across two industries, tracking KPI outcomes before and after coaching, over a six-month period. 

A coaching action (or coaching interaction) is a concrete step a manager takes to move a team member’s performance: for example, providing personalized feedback, recommending a learning module or simulation tied to a KPI that needs improvement, or assigning a performance improvement challenge. 

With AI-guided coaching, Centrical’s AI points the manager to who needs help and which metric to focus on, drawing on performance, quality, and learning signals across the whole team. Unassisted coaching is the same work without that guidance. 

Finding #1: AI-Guided Coaching Beats Unassisted Coaching by 10.2 Percentage Points 

When AI was used to guide manager coaching, it produced a measurable improvement in the specific metric the coaching was meant to move 59.1% of the time, compared to 48.9% for coaching unassisted by AI, a gap of about 10.2 points. 

Manual coaching still works, but when AI directs the manager to the right person and the right metric, the business sees a double-digit lift in performance improvement.

Finding #2: Nearly Every KPI Improved 

19 of the 20 most-coached KPIs improved after AI-guided coaching.

The lift showed up across nearly every KPI managers coached on: customer satisfaction, first-call resolution, quality, conversion rates, productivity, and more. 

The same pattern held across two very different industries, pointing to the method, not the team. 

Finding #3: The Advantage Is Targeting 

Why does AI-guided coaching pull ahead? It’s highly targeted. 

Managers coaching from memory tend to repeat familiar advice and target the same group of people. AI reads the signals across the whole team, then points the manager to the person who needs help and the metric most likely to move, ranked by what matters most to the business. The manager still does the coaching, but AI helps them focus their efforts on the highest-impact activity. 

A Closer Look: Two Industries, One Pattern 

To see whether our findings held up, we conducted our analysis on data from two different industries: banking/financial services and hospitality. 

In financial services

At a top-5 banking and financial services organization, team leaders delivered hundreds of thousands of coaching actions in six months. 

  • Coaching volume climbed by +32%.
  • More coaching went hand in hand with better coaching: the team leaders who coached more often also coached more effectively, a small but statistically significant relationship (r = 0.14).
  • AI-guided coaching outperformed unassisted coaching by 10.7 points here. Customer satisfaction rose +14.2% after coaching, and 9 of the 10 top KPI groups improved. 

In hospitality 

At a global hospitality brand, frontline managers adopted AI-guided coaching in a very different setting. As part of the initiative, the company rolled out a structured coaching methodology that focused every conversation on the specific behaviors and metrics most likely to move performance. Given their familiarity with Centrical, leadership found the platform a natural vehicle for delivering the new methodology. Centrical was already part of the frontline agents’ everyday work, making adoption seamless. 

Every one of the top 10 KPIs improved after coaching, including loyalty-tier conversion (+7.3%), vacation reservation sales (+7.1%), and loyalty program enrollment (+6.4%). 

Why It Matters 

Managers want to coach more. What they need is help deciding where to spend their time. 

AI can close that gap: it reads performance signals no manager can track by hand, then hands them a shortlist: this person, this metric, this coaching action, now. The judgment, the conversation, and the relationship stay human, while the targeting gets sharper and the impact stronger. 

The lesson is simple: target your coaching. More coaching on its own won’t move performance consistently, but prioritizing the right coaching with AI is what makes the difference. 

How to Get Started 

If you want coaching that changes performance, start here: 

  1. Tie coaching to a specific KPI. Give every coaching action a target.
  2. Let AI prioritize whom and what to coach on. Use performance signals to identify the person and the metric most likely to move, instead of relying on memory, habit, or convenience.
  3. Measure outcomes. Track whether the coached metric actually improved, and feed that back into who gets coached next and how.
  4. Keep the human in the loop. AI sets the target; your managers still build the trust and deliver the message. 

See Centrical in Action 

Want to see AI-guided coaching work within Centrical? Watch our demo here: 

Request a Free Demo