Predict Customer Churn

Customer loyalty is fragile. Loris helps you spot at-risk customers early – so you can fix the problem before they churn.

One Loris client found that even among their most loyal customers, conversations with a decline in customer sentiment reduced reorder rates by almost 10%!

Customers tell you how they’re feeling in every conversation. Are you listening?

Asking customers for feedback after a bad support interaction makes a bad situation worse. Because they’ve already told you everything you need to know: why they contacted you, how they’re feeling, and whether you’ve resolved their issue.

What if you could use the elements of the conversation to understand which customers are a churn risk today?

Loris helps you get smarter about understanding and fixing customer issues with:

  • A library of pre-trained AI models proven on 500+ million interactions
  • Deep conversation insight on everything from customer intent to sentiment to frustration
  • Transparent and consistent AI outputs that you can see and understand

Your recipe for predicting churn: The right combination of AI insight

Loris combines different AI models to create deeper and more accurate insights into every conversation, pinpointing your most urgent and highest priority issues. Here’s the right mix that helps you predict potential customer churn.

Step 1

Understanding Contact Drivers

Loris analyzes every conversation – across email, chat, phone, and AI agent interactions – to automatically detect the primary reason driving customer contact (Contact Driver) as well as additional intent signals (Topics). This gives you the complete picture of every issue coming to your CX team.

Why it matters

This insight is the critical source of truth missing from most contact centers – and one of the strengths Loris has. This knowledge gives you a map of your main issues driving customer contact. From here, Loris clients layer on additional conversation data, from volume trends to changes in sentiment to how often your human and AI agents are resolving these issues.

Step 2

Analyze Sentiment Delta to see each customer's emotional journey

Once you have a clear view of customer contact issues, Customer Sentiment helps you go deeper. Because Loris analyzes sentiment on every message within a conversation, you can see the customer’s emotional journey, or Sentiment Delta, to understand whether they left the conversation positively or negatively on a 5-point scale. In addition, Sentiment Target provides the focus of the customer’s sentiment, whether towards the agent or the company.

Why it matters

Customer sentiment analysis is where Loris started, and where our clients say we differentiate most from competitors. Our sentiment model is one of the ways clients understand their highest priority issues and which of their customers are at the highest risk of churn.

Step 3

See Resolution rates for all your issues

While Sentiment tells you how the customer feels, Resolution gives you the outcome of all your customer conversations – in aggregate as well as within individual interactions. It also provides insight into whether your human and AI agents are able to handle specific issues effectively, so you know if agents need more training or your bot shouldn’t handle certain use cases.

Why it matters

Without Resolution, you could assume positive sentiment in customer conversations means that the customer is happy with the overall experience. But without actually resolving issues, you’ll see higher costs from repeated contact or miss signals from frustrated customers who never come back.

Step 4

Spot additional risks impacting churn

Loris Reasons to Review flag conversation outliers to identify everything from regulatory threats to manager escalations to profanity to frustration. Though infrequent, these provide a quick way to triage conversation review and map risks to your business by agent, team, or AI Agent.

Why it matters

This additional dimension of conversation analysis helps you identify a dozen different markers that warrant attention – and that pose risks to your business. 

Step 5

Find the Root Cause to remove issues entirely

The best way to resolve a customer issue is to not have that issue happen in the first place. Loris analyzes every interaction to uncover the core issues breaking the customer experience, not just what the customer thought the issue was. With this insight, you can fix your product, your documentation, or whatever gap is causing unnecessary friction.

Why it matters

Reacting to individual issues spends valuable time and money. But removing the underlying cause of unnecessary contacts, like confusing policies or product bugs, prevents those contacts from happening in the first place. This can significantly reduce contact center costs and make for a better overall experience.

Case Study

Predict and Prevent Customer Churn

Read how one Loris client used their customer service interactions to:

  • Predict customer churn using customer sentiment
  • Connect churn and reorder rates for different customer segments
  • Develop a white glove strategy to prevent churn for high-value customers
Whitepaper

See Why Loris AI Models Deliver Better Insight

Hard to tell the difference between all the AI vendors? That’s why we developed this whitepaper, to help you clearly understand how each of our AI models works, the role each AI model plays in understanding your customers, and the philosophy guiding how we use different AI techniques.

Still have questions? Let’s chat!

Schedule a meeting to learn more about how we reduce cost per case while increasing customer insights.