Customer analytics software is designed to help teams understand their customers behaviours, frictions and pain points. Customer data, on usage, product interaction and service feedback, now comes in such high volumes that's companies find it hard to manage. Customer analytics software should make it simple to understand large amounts of data, doing both the analysis and visualisation for you.
Customer insights should be actionable. Actionable customer insights are are uncovered quickly, in detail and in a way that can be trusted by teams across your company.
Once 'actionable', customer insights enable these use cases:
• Optimise the customer support department: tackle drivers of customer contact, train staff on product pain points, automate ticket triage and save your agent's time tagging tickets manually.
• Enhance customer satisfaction: identify anomalies and customer pain points in real-time, proactively solve issues at the root cause, and develop a long-term product improvement strategy.
• Improve profits: reduce customer churn, improve product adoption and usage, reduce call centre costs, and optimise conversion rates by removing customer friction points. Each of these points improves the customer lifetime value.
We've built one of the most powerful machine learning-based customer analytics softwares around today. SentiSum is built to uncover highly granular customer insights from large volumes of qualitative data in real-time.
We integrate into your help desk, survey system and customer review platform and turn hundreds of thousands of data points into clear, actionable insight. Our, and your, superpower is support tickets. They're high volume, rich sources of unbiased feedback. We're one of the few companies who can automatically make sense of them at scale.
So, how does this works:
1. Integrate Sentisum's platform with thousands of different channels.
2. Following the integration, we run your data through our exploration system which extracts important text words and phrases that are being mentioned in the support tickets. These words and phrases help us to identify granular insights that needs to be tagged.
3. We build you a custom AI model ased on historic data exploration.
4. Once the model is built and trained, we'll get back to you to kick off your customer analytics. Not only is your historical data organised, so we can tell what's normal and what's an anomaly, but any new support tickets are also tagged and categorised in our system.
5. Detecting anomalies: monitors the daily volume of each topic event and our custom anomaly detection module notifies you if there is an abnormally high number of mentions as compared to the number forecasted by our system
6. For you, this is a seamless one-click experience.
Request a demo today and we'll show you around the platform.