Insights Are Cheap. Decisions Are the Bottleneck: 5 Lessons from Zack Hamilton on the Future of CX
AI has made it easier than ever to understand what customers are saying. But turning that understanding into meaningful business outcomes remains one of the biggest challenges for customer experience teams.
Customer experience teams have spent years investing in better ways to collect, analyze, and report on customer feedback. Now, AI can surface patterns, identify friction, and generate insights in minutes instead of days.
Yet many organizations are still struggling with the same fundamental problem: knowing what customers need doesn't necessarily mean anything gets done about it.
We recently hosted Zack Hamilton, former CX leader at Aaron's and Medallia and host of the Unf*cking Your CX podcast, for a conversation with Jack Divita, Head of Customer Success at Enterpret, about why faster insights aren't enough and what it takes to turn customer intelligence into real business impact.
Here are five lessons from their conversation.
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1. The problem isn't a lack of insights. It's a lack of decisions.
For years, CX teams have been measured by their ability to collect feedback, identify trends, and communicate findings across the business.
AI has dramatically accelerated that work. Analysis that once took hours or days can now happen in minutes.
But as Zack pointed out, the speed of insight generation doesn't matter much if organizations still struggle to act on what they learn.
Part of the challenge is how companies are structured. Product, marketing, support, operations, and other functions each have their own priorities and KPIs. When customer feedback comes in, teams naturally evaluate it through the lens of their own responsibilities.
The result? Multiple teams may address different symptoms of the same problem without ever solving the underlying cause.
A customer struggling with a checkout experience, for example, might generate a support ticket, a product bug report, and negative feedback about a marketing promotion. Each team can respond independently, but unless they connect those signals, the actual source of friction may remain unresolved.
The takeaway: Customer intelligence becomes valuable when it helps teams understand the same problem, agree on what matters, and coordinate action around a shared outcome.
2. CX teams need to speak the language of business outcomes.
One of Zack's strongest arguments was that CX leaders need to move beyond reporting on traditional experience metrics.
NPS, CSAT, and sentiment can help identify where something is happening. But they don't necessarily explain the financial impact of a problem or why another team should prioritize solving it.
Zack shared an example from his experience leading contact center operations.
Rather than sending an ecommerce leader a monthly report about customers calling with website issues, he began framing those issues as business problems.
How many customers were affected? What did those contacts cost the company? How much potential revenue was being lost through abandoned carts? And what could the business gain by removing that friction?
Suddenly, the conversation wasn't about reducing support volume. It was about improving conversion and recovering revenue.
That shift helped connect customer feedback to the KPIs that other leaders were already accountable for.
It also changed the role of CX from reporting problems to helping the organization make better investment decisions.
The takeaway: Don't just explain what's frustrating customers. Show what that friction is costing the business, what solving it could unlock, and what happens if the organization chooses not to act.
3. AI agents need a learning loop, not just a knowledge base.
AI support agents are becoming increasingly effective at handling customer inquiries, reducing response times, and resolving routine issues.
But Zack and Jack challenged whether those improvements always translate into better customer experiences.
An AI agent might resolve an inquiry quickly and earn a positive satisfaction score. Yet the customer may still be experiencing a recurring problem that shouldn't exist in the first place.
And when agents rely on outdated documentation, policies, or FAQs, they risk reinforcing the very friction they're supposed to resolve.
Zack argued that organizations need to treat AI agents more like human employees: with ongoing training, performance evaluation, and feedback.
When a customer escalates from an AI agent to a human, what can the organization learn from that interaction? When an experienced support representative goes beyond the standard playbook to deliver an exceptional outcome, how can that behavior inform future agent decisions?
These questions become especially important as organizations move toward more autonomous AI systems.
Zack described the missing link as experience operations: the systems and processes that connect customer intelligence, decision-making, action, and measurement.
Without that foundation, companies risk automating processes they haven't fully figured out themselves.
The takeaway: The goal isn't simply to automate more customer interactions. It's to build systems that continuously learn from those interactions and improve the experience over time.
4. Customer feedback should help teams decide what not to build.
Customer feedback is often used to answer a familiar question: What should we prioritize next?
But Jack and Zack discussed an equally important use case: helping organizations confidently decide what not to prioritize.
Consider a CEO who sees a negative review or receives a complaint from a customer and immediately asks the team to address it.
Without broader context, that individual piece of feedback can quickly become the organization's most urgent priority.
But what if the team could show that the issue affects only a handful of customers, while three other problems affect significantly larger customer segments or accounts with upcoming renewals?
Now the discussion becomes a deliberate tradeoff rather than a reaction to the loudest complaint.
Zack shared how he used this approach when executives escalated individual customer issues. By explaining the scale of the problem and the reasoning behind existing priorities, he could reinforce confidence in the team's decisions.
The key wasn't dismissing feedback. It was putting that feedback into context.
And that context helped build credibility with leadership.
The takeaway: Great customer intelligence doesn't just tell teams what deserves attention. It gives them the evidence to defend priorities, make tradeoffs, and stay focused on the problems that matter most.
5. Measure the impact of actions, not just the volume of activity.
Product and CX teams often measure progress through activity: bugs fixed, features shipped, reports delivered, or initiatives completed.
But activity and impact aren't the same thing.
Zack described working with a retailer whose product team was shipping improvements every two weeks. Despite that consistent activity, cart abandonment performance had remained largely unchanged over the previous year.
The team was moving quickly, but the business wasn't seeing the expected improvement.
This is where Zack and Jack agreed that customer intelligence has an opportunity to play a much larger role.
It's not enough to identify a problem and help prioritize a solution. Teams also need to understand what happens after the solution ships.
Did complaints decrease? Did customers change their behavior? Did conversion improve? Did the business achieve the outcome it expected?
Without that final step, organizations risk repeating the same cycle of identifying problems, shipping fixes, and moving on without knowing whether anything actually improved.
For CX leaders, Zack recommended focusing on two measures: the actions taken as a result of customer intelligence and the financial impact those actions delivered.
He also encouraged teams to start small.
Rather than trying to lead a massive transformation immediately, identify one meaningful friction point, build a business case, help drive the decision, and measure the result.
Those smaller wins can build the credibility and momentum needed for broader change.
The takeaway: Closing the feedback loop means more than acknowledging customer feedback or shipping a fix. It means measuring whether the action actually improved the customer experience and the business.
From customer insights to customer impact
As AI makes customer insights increasingly accessible, the role of CX is changing.
The opportunity is no longer just to produce better reports or surface more feedback. It's to create a shared understanding of customers that helps every team make better decisions.
That requires connecting feedback across channels, understanding the root causes of friction, translating problems into business impact, and measuring what happens after action is taken.
For CX leaders, Zack offered a practical place to start: meet with cross-functional stakeholders to understand their most important KPIs, identify one customer problem preventing progress, and build a business case for solving it.
Because the organizations that succeed won't necessarily be the ones generating the most insights.
They'll be the ones that know what to do with them.
Want to go deeper? Watch the full conversation with Zack Hamilton and Jack Divita to learn more about turning customer intelligence into better decisions, building influence across teams, and measuring the business impact of CX.
