In Conversation with Pratap Ramaiah, Strategic Operations & Customer Experience Leader, Conversive

What does it take to deliver a consistent customer experience across regions, teams, and time zones? And how do you scale support without losing the human touch?

With nearly two decades of experience across customer experience, service delivery, and operations, Pratap Ramaiah brings a practical perspective on building support teams that go beyond resolving tickets. From strengthening global support operations across APAC, EMEA, and the US to improving customer satisfaction and exploring the potential of conversational AI, Pratap shares how the right balance of people, processes, and technology can turn customer support into a true driver of customer success.

Let’s get into it.

1. You’ve built your career across customer experience, service delivery, and operations. What drew you to support and CX, and what keeps you excited about it today?

What drew me to Support was the opportunity to solve real problems and understand the customer’s perspective. Over nearly two decades, working across different domains and business environments, I’ve seen how customer interactions provide valuable insights into how a product performs in the real world and where the experience can improve.

My perspective has evolved over time. I see Support as much more than a function that resolves issues. It plays an important role in customer retention, product improvement, and business growth. The insights we gain from customer interactions help organizations make better decisions across the entire customer journey.

At Conversive, what excites me is the opportunity to work beyond traditional support operations. Along with leading Global Support across the US, EMEA, and APAC, I’m involved in cross-functional initiatives and Voice AI validation. Exploring how AI can make customer interactions more natural, efficient, and useful is particularly exciting, it opens up new possibilities for customer experience.

2. Running global support means covering multiple time zones and regions. What’s the hardest part of delivering a consistent experience across geographies?

The biggest challenge is maintaining consistency while accounting for differences in time zones, customer expectations, technical complexity, and team capabilities.

Having teams available across regions is only part of the equation. The experience a customer receives should not depend on when they raise a ticket or which team happens to be working at that time.

At Conversive, I focus on establishing common operating standards, clear escalation paths, structured training, and consistent quality expectations across APAC, EMEA, and the US.

I’ve also restructured our support model around capability development, technical expertise, communication, and a consistent customer experience across regions. We use a structured progression framework and targeted cross-training to strengthen team capabilities and prepare people to handle increasingly complex customer scenarios.

Global support is about building one cohesive organization rather than separate regional teams operating independently. That requires shared accountability, regular communication, and a common understanding of what good customer support looks like.

3. When you’re scaling a support team, what do you put in place first: people, process, or tooling? What breaks if you get the order wrong?

Process first, while recognizing that people and processes need to evolve together.

Before scaling, you need clarity on what the team is expected to deliver, how priorities are defined, who owns an issue, when it should be escalated, and how success will be measured. Without that foundation, adding people increases activity without necessarily improving outcomes.

At Conversive, I established a comprehensive SLA framework covering account segments, ticket priorities, resolution timelines, escalation responsibilities, and support coverage. This gave the teams a common reference point and brought greater structure to how customer issues are managed.

Once the process is clear, you can identify the skills required, develop the team, and introduce tools that support the way you want the organization to operate.

Getting the order wrong leads to inconsistent customer experiences, unclear ownership, and technology that automates inefficient processes. Scaling successfully is not about doing more, it’s about building a model that delivers consistently as the business grows.

4. Customers often care which team owns their problem. How do you design support operations so that issues moving across Support, Product, and Engineering don’t lose momentum?

From the customer’s perspective, there is only one company. They should not have to navigate internal team structures to get a problem resolved.

The key is distinguishing between the team responsible for investigating an issue and the person accountable for driving it forward. Different teams may need to contribute, but the customer should always have clarity on next steps.

At Conversive, I developed a cross-functional Customer Journey Ownership and Escalation Guide covering responsibilities across different stages of the customer lifecycle Onboarding and Implementation, Customer Success, Billing, Telecom, and Support. The objective is to clarify ownership, streamline handoffs, and address situations where responsibilities overlap.

Within Support, I also emphasize proactive escalation, meaningful customer updates, and clear next steps rather than allowing issues to sit pending without progress.

Good collaboration isn’t simply about bringing the right teams into a discussion. It’s about ensuring every handoff moves the issue closer to resolution and that someone continues to drive the overall customer experience.

5. Many teams track CSAT, response time, and resolution time, but not all metrics tell the real story. Which support metrics do you trust most, and which do you think are misleading?

I look at a combination of customer feedback, service performance, and quality rather than relying on any single metric.

CSAT helps us understand how customers perceive the support experience. Response and resolution times tell us how efficiently we’re operating, while quality assessments reveal whether issues are being diagnosed correctly, communication is clear, and the right processes are being followed.

One area I pay particular attention to is the CSAT survey response rate. A high satisfaction score is encouraging, but it’s equally important to understand how many customers are providing feedback. At Conversive, our response rate has grown from around 7–8% initially to 20% last year and 32% this year. Alongside that, customer satisfaction has remained above 96.5% last year, with an average of 98.3% this year.

The value is in improving both the customer experience and our ability to hear from a broader base of customers. Feedback becomes more useful when we can identify patterns and translate them into specific improvements.

The metric I’m cautious about is average resolution time viewed in isolation. Closing a ticket quickly doesn’t necessarily mean the problem has been resolved effectively. If the issue reopens or the customer has to repeat the same information, the apparent efficiency can be misleading.

Ultimately, metrics should help us understand the real customer experience and encourage the right behaviours, they should guide decisions and improvement, not simply make a dashboard look good.

6. In a messaging and conversational AI platform, an issue can involve the customer’s setup, the platform, or a third-party provider. How do you approach troubleshooting when the root cause sits outside your own system?

The first principle is to investigate systematically rather than jump to conclusions.

In a messaging platform, a delivery issue could originate in the customer’s configuration, an integration, our platform, or a third-party provider. The challenge is narrowing down those possibilities using the available evidence.

I believe in structured triaging, asking the right diagnostic questions and following a decision tree to isolate the potential cause. We start by understanding the symptoms, the scope, and the circumstances. From there, we validate the customer’s configuration and integration, examine the relevant evidence, and determine whether the issue requires investigation by Support, Telecom, or Engineering.

This approach helps us narrow down the root cause instead of escalating without sufficient investigation. It also means that when an issue moves to another team, the findings and troubleshooting steps are documented clearly so the next team can continue from where we left off.

Communication is equally important. Customers should understand what we’ve established, what remains under investigation, and what happens next even when an external dependency is involved.

My philosophy is simple: we may not control every part of the technology ecosystem, but we can control the quality of our investigation, the effectiveness of our coordination, and how responsibly we manage the customer experience.

7. AI and automation are changing how support works. Where do you think they add the most value, and where does a human still make the difference?

I see AI as an opportunity to make customer experience more accessible, responsive, and scalable. However, the value of AI depends on how well it’s designed, configured, and implemented.

AI adds significant value to repetitive, well-defined interactions answering common questions, checking status, guiding customers through standard processes, and routing queries to the right team. Conversational AI also creates opportunities to support customers beyond traditional operating hours and in the languages they’re comfortable using.

At Conversive, my involvement in Voice AI validation has given me a practical view of what it takes to make these interactions work well. It’s not enough for an AI agent to generate an answer, the response needs to be accurate, relevant to the context, and natural for the customer.

Without the right configuration, a well-structured knowledge base, and carefully designed conversational flows, AI can sound repetitive, artificial, or disconnected from what the customer is actually asking. The choice of voice, language, tone, and conversational style matters too. These interactions need to be tested across languages and scenarios to identify where the experience can be improved.

Human expertise remains essential when an issue is technically complex, emotionally sensitive, or requires judgment across multiple systems and teams. People also need to recognize when an AI interaction isn’t progressing and step in when necessary.

The best approach is letting AI handle what it can do reliably while people focus on situations that require experience, empathy, and critical thinking. The objective isn’t simply to automate conversations, it’s to make those conversations genuinely useful and improve the overall customer experience.

8. If you were advising a SaaS company building its support function from scratch today, what would you tell them to do in the first year, and what would you tell them to avoid?

I’d focus on three things in the first year: establishing clear processes, building the right capabilities, and creating a culture of quality and accountability.

First, define the support model. Establish service expectations, account priorities, escalation paths, ownership, and the metrics that matter to the business.

Second, invest in people. Hire for problem-solving ability and communication skills, build product knowledge systematically, and create a development path that allows team members to take on increasingly complex responsibilities.

Third, make quality and customer feedback part of the operating rhythm from the beginning. Review interactions, identify recurring issues, and share insights with Product and Engineering so that customer feedback contributes to product and process improvements.

I’d avoid scaling headcount before understanding the nature of customer demand, and I wouldn’t invest in multiple tools before defining the processes those tools need to support.

Most importantly, I’d encourage leaders to treat Support as a business partner, not merely a service function. A well-run support organization does more than resolve problems, it helps the company understand its customers, improve its product, and build lasting relationships.

Rapid Replies:

The most underrated support metric?

Ticket reopen rate. It tells you something important about whether the resolution actually addressed the customer’s problem.

Which fictional character would make the worst support agent?

The Joker “He’d tell customers, ‘Why so serious?’ when they report a production outage.”

What’s your go-to excuse for “I’ll get back to you shortly”?

“Let me assess this, take ownership, and get the right people involved to drive it to closure.”

Which household gadget do you wish came with a better support team?

The Wi-Fi router. It’s amazing how quickly everyone at home becomes a technical support engineer when the internet stops working.

If you weren’t in customer experience, what would you be doing?

A life coach - helping senior professionals and leaders stay fit, healthy, and young while managing demanding careers.

Thank you, Pratap, for sharing your insights on building stronger support teams and creating better customer experiences. Your perspective reinforces that great support goes beyond resolving issues, it’s about taking ownership, building trust, and continuously improving the customer journey. Here’s to better customer experiences!

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