How conversations shape the customer experience in 2026: 4 key takeaways

Every time a customer reaches out to your support team by chat, email, or phone, that interaction becomes part of their experience with your brand. 

But unlike traffic, engagement, or conversions, conversations haven’t traditionally been measured in a way that connects them to the broader digital experience. That makes important signals—like whether a customer is becoming increasingly frustrated or confused during the conversation—easy to miss. Those changes in sentiment shape how customers feel about your brand and whether they return.

In this article, we explore key findings from our 2026 Digital Experience Benchmarks Report, including how conversations shape the customer experience and how to guide conversations toward better outcomes and boost retention.

Key insights 

• A customer’s emotional state during a support interaction is a strong indicator of whether the issue will be resolved and how they will feel about your business afterward

• Using humans and bots together significantly improves resolution rates, especially for refunds, security concerns, and technical support, where customers often need judgment, empathy, and more nuanced support.

• Email support conversations start with more frustration than any other channel. The issue may not be the channel itself, but gaps in documentation, FAQs, or in-product guidance that keep customers from solving the problem on their own.

• Conversation insights become more useful when you connect them to the wider customer journey—using experience intelligence tools like session replays, journey analysis, and heatmaps—to see what customers experienced before reaching out

1. Sentiment is a strong indicator of resolution

For this year's benchmark report, we analyzed 20 million+ customer service conversations across chat, email, and voice in 2025. Two key findings:

• In conversations where customer sentiment improves during a support interaction, 67% of issues get resolved. When sentiment worsens, the resolution rate drops to 28%.

• In support interactions where the customer’s sentiment stays neutral, 41% of issues still get resolved

What does this mean for you?

The quality of a customer conversation can tell you a lot about how well your product is working for customers. 

When customer sentiment improves during an interaction, it usually means the customer feels heard and is getting the help they need. When it worsens, the customer likely feels frustrated, confused, or unsure about next steps, which affects whether or not they return. 

But when sentiment stays neutral, more than 4 in 10 issues still get resolved, which means you don't always need to make every interaction positive.

What to focus on

Identify the conversation patterns behind frustration and unresolved issues. Look for moments customer sentiment starts to decline, the types of questions that repeatedly trigger negative sentiment, and the interactions that fail to reach a resolution. 

From there, dig deeper to see whether unresolved conversations are concentrated within a specific team, which points to a coaching or training gap. Or whether they cluster around the same issue, which signals a problem with your policies, documentation, or offering. 

When you track sentiment alongside resolution rates, you can see which conversations are going wrong and where to focus improvements first.

💡 Pro tip: use Contentsquare’s Conversation Intelligence to analyze customer interactions, understand why customers are reaching out, and track how their sentiment changes throughout the conversation. Contentsquare also lets you see which conversations get resolved and which don't, so you can prioritize the issues, teams, or workflows that need attention based on real data.

BILL, a financial operations platform, used Contentsquare’s Conversation Intelligence to give agents real-time visibility into customer sentiment. That allowed agents to adjust their responses during the interaction, reduce frustration before it escalated, and help shift conversations from negative to positive while the issue was still being handled.

2. Human-bot conversations resolve issues nearly twice as often as bot-only interactions

Our benchmark data also shows that who handles the conversation—whether it's a bot, a human, or both—has a significant impact on whether the issue gets resolved. 

• When humans and bots work together to resolve a customer's issue, the resolution rate is 57%. When bots handle it alone, that drops to 29%. 

• Bots alone resolve just 18% of refund conversations compared to 53% when a human is involved. For security and compliance, bots resolve 14% versus 47% of a human. For technical support, it's 15% versus 46%.

What does this mean for you?

Automation works best when paired with human agents, especially for sensitive, complex, or high-stakes issues like refund requests, security concerns, and technical problems. 

These topics require the kind of judgment and empathy that bots cannot yet provide on their own. So, teams automating these topics fully are likely leaving a significant number of issues unresolved or customers frustrated.

One thing to keep in mind is that businesses are often routing easier, more straightforward issues to bots and routing complex customer issues to human agents, namely because human agents can handle complexity better than AI. As AI agents improve, bots may be able to handle more complexity, but, for now, they seem to be resolving simpler use cases effectively.

What to focus on

Understand why customers are reaching out first. From there, look at which topics are consistently going unresolved with bots. This helps you decide when to use bots alone, when to involve a human, or when a combination of both works best. 

💡 Pro tip: Contentsquare’s ‘Contact Drivers’ feature shows you why customers are reaching out—whether it's a billing question, a product issue, a refund request, or something else. Once you can see the reason behind each interaction, it becomes easier to decide which topics bots can handle effectively, which ones should be routed to a human, and where your AI agents need refinement.

Contact Drivers surfaces the main reason behind each support interaction, which makes it easy for you to match the right support approach to each conversation

3. Channel choice shapes how conversations start, recover, and resolve

Our benchmark report revealed that the channel customers use to contact support influences how conversations begin, how sentiment changes during the interaction, and how likely the issue is to be resolved. 

The data shows:

• Nearly 2 in 3 email conversations (64%) begin with negative sentiment, compared to just under 1 in 3 for voice (29%)

• Sentiment improves over the course of the interaction in 89% of voice conversations and 77% of chat conversations. Only 7% of voice interactions remain negative, compared with 20% for chat and 41% for email.

• Voice has the highest overall resolution rate at 56%, followed by chat at 48% and email at 45%

• Voice conversations resolve 60% of refund issues compared with 39% on email. For orders, resolution is 62% on voice vs. 43% on email. Email performs worst on security and compliance (31%) and billing and payments (37%).

What does this mean for you?

The channel a customer uses shapes how the conversation starts, how likely sentiment is to recover, and how often the issue gets resolved.

Customers who reach out by email are more likely to start frustrated, and email offers the least opportunity to turn that around. Phone and chat conversations let agents pick up on tone, clarify issues quickly, and adapt their approach before the conversation gets worse, which is why they consistently outperform email on both recovery and resolution.

What to focus on

Make it easy for customers to reach you through the right channels. Start with your highest-friction topics and look at which channels those conversations are landing in. If the same issue consistently gets resolved more on a specific channel, redirecting customers there will help resolve more issues.

💡 Pro tip: combine call center analytics, speech analytics, and conversational intelligence to understand what's driving outcomes across all channels. Together, these insights let you track signals like sentiment and resolution rates, analyze what customers are saying and how they're saying it, and compare performance across voice, chat, and email, so you can spot where changes will have the most impact.

To dig deeper, connect those conversation insights with Contentsquare's Experience Analytics tools. Use Session Replay, Journey Analysis, and Heatmaps to see what happened before customers reached support. Then use Contentsquare’s AI agent Sense to ask questions about the data and quickly identify the root causes behind those issues.

Sense AI lets you ask questions about your conversation data and get instant answers to identify root causes and prioritize improvements

Track conversations as part of the digital experience

Customer conversations shape how people experience your brand and can influence whether they come back. That’s why teams should track and improve conversations with the same rigor they apply to traffic, engagement, and conversions.

Conversation Intelligence, paired with Contentsquare’s Experience Analytics tools, makes that possible. It helps teams analyze every customer interaction, connect conversation insights to the wider digital experience, and take action based on what the data reveals.

FAQ about customer conversations