Picture this: You’re a new customer-success rep at an AI-powered communication tools company. You’ve just received a call from a long-standing client whose email campaigns are consistently landing in spam folders. The client is frustrated, threatening to switch providers. What do you do next?

This scenario highlights a common challenge in AI-ML communication platforms: maintaining customer loyalty by improving product outcomes like email deliverability. Continuous improvement programs, when focused on customer retention, can help prevent churn and boost engagement by systematically refining how customers achieve success with your tool.

Understanding Continuous Improvement from a Customer-Retention Lens

Imagine continuous improvement as a relay race where each handoff represents a small step forward—each step focused on making your customer’s experience better and more valuable. For an entry-level customer-success professional, this means consistently gathering feedback, analyzing usage data, and collaborating with product teams to fix issues that affect your customers directly.

A 2024 Forrester report revealed that companies engaging in ongoing improvement programs reduced churn by an average of 18% in the first year, mainly by addressing pain points before customers decide to leave. This kind of success doesn’t happen overnight; it requires structured, repeatable efforts grounded in your customers’ real-world challenges.

The Business Context: Email Deliverability as a Retention Challenge

For AI-ML communication tools, email deliverability is a frequent sticking point. Algorithms that personalize email timing, subject lines, and content often struggle when emails fail to reach inboxes. Imagine a client using your platform’s AI to send personalized marketing messages, but their campaigns bounce or land in spam folders. Their perceived value of the platform drops sharply.

One company we’ll call “CommuAI” faced this exact issue. Their clients' average campaign open rates dipped from 38% to 24% over six months, primarily because of degraded email deliverability. As customer-success reps began receiving more complaints, churn risk grew.

Step 1: Start With Data-Driven Customer Feedback

You don’t want to guess why customers are unhappy. Use targeted surveys and user feedback to identify specific friction points.

At CommuAI, the customer-success team used Zigpoll alongside in-app feedback tools to ask clients simple questions: “Are your emails reaching inboxes?” and “What challenges do you face with campaign results?” Over 65% of respondents mentioned deliverability concerns.

The feedback nailed down a clear focus area: improving deliverability was the key to boosting retention.

Tools to try:

• Zigpoll for quick pulse surveys
• Intercom or Zendesk for in-app feedback
• Customer interviews for deeper insights

Step 2: Collaborate Across Teams on Small, Iterative Fixes

Continuous improvement thrives when customer-success teams work closely with product, marketing, and engineering.

At CommuAI, the CS team passed summarized feedback to the product team. Engineers then tested improvements like better spam filter detection using AI models trained on new datasets. Marketing updated client education about best practices for list hygiene and authentication protocols like SPF and DKIM.

Instead of a one-time fix, CommuAI rolled out weekly deliverability tweaks—slow and steady improvements that built trust with clients.

Step 3: Use AI-ML Insights to Monitor and Predict Churn Risks

Your AI-ML platform can analyze usage patterns to flag clients at risk of churning. For example, CommuAI’s analytics detected clients whose campaign open rates dropped below 30% for three consecutive months. These clients were flagged for proactive outreach.

This predictive approach allowed the customer-success team to intervene early, offering tailored advice and resources to improve deliverability before clients considered leaving.

One client’s open rates improved from 27% back to 42% after a customized deliverability checklist and a dedicated CS call, reducing their likelihood of churn.

Step 4: Educate Customers to Empower Better Use of Features

Deliverability is partly technical but also behavioral. Clients need to understand how their actions impact results.

CommuAI’s CS team created short video tutorials and webinars explaining:

• How AI models optimize send times
• The importance of verifying email lists
• Authentication settings like DMARC

They also shared benchmark reports showing how deliverability correlated with retention.

This proactive education increased feature adoption by 15% and reduced support tickets related to deliverability issues.

Step 5: Regularly Measure Retention Impact of Improvement Programs

Without measuring, you won’t know if your efforts work.

CommuAI set up monthly retention metrics to track customers who reported improved deliverability. The team measured:

• Churn rates before and after program launch
• Changes in average campaign open rates
• Customer satisfaction (CSAT) scores via Zigpoll surveys

After six months, churn among clients engaged in the continuous improvement program dropped by 12%, with open rates rising 8 percentage points on average.

Step 6: Recognize What Doesn’t Work and Pivot Quickly

Not every idea pans out. Early in the program, CommuAI tried sending automated push notifications about deliverability tips. Unfortunately, these messages annoyed some customers, leading to decreased engagement.

Learning from this, the CS team switched to less intrusive email newsletters and personalized outreach, which received better feedback.

This shows that continuous improvement is a cycle — experiment, learn, adjust — not a straight path.

Quick Comparison: Traditional Support vs. Continuous Improvement Approach

Limitations to Keep in Mind

Continuous improvement programs require resources—time, tools, and cross-team coordination. For startups with limited staff, dedicating the bandwidth to run structured surveys or weekly fixes might be challenging.

Also, not all churn can be prevented through deliverability improvements. Some customers leave due to pricing, competitive offers, or changes in business needs. It’s crucial to identify which causes your program can actually influence.

Final Thoughts on Starting Your Own Program

Imagine the difference you could make, as a customer-success professional, by championing continuous improvement focused on your customers’ biggest headaches. By gathering clear feedback, collaborating with product teams, educating users, and tracking retention impact, you don’t just solve problems; you build loyalty.

In the AI-ML communication tools space, where email deliverability can make or break your customer’s campaigns, continuous improvement is a practical path to keeping existing customers happy and engaged.

You might start by sending out a Zigpoll survey this week asking your clients about their deliverability issues. See what patterns emerge. Then work with your teammates to test small changes. The journey to higher retention starts with one thoughtful step.