.jpg)
SOFTWARE
Simplified customer complaints analysis
SentiSum's AI-powered support ticket tags apply granular 'reasons for complaints' in real-time. We make understanding complaints at scale easy, so you can report in minutes and start driving company-wide improvements.
-min.png)
"It's easy to setup and the insights are accurate. Every team has started using customer conversation insights!"
Director of Customer Service, +$50m revenue fast-growth company
.png){kind=logo}
.png){kind=logo}
.png){kind=logo}
.png){kind=logo}
-min.png)
How it works
SentiSum is built using machine-learning based NLP. It's designed to understand and tag customer contacts in a way that's:
1/ Accurate: It tags based on meaning, not keywords.
2/ Granular: Tags get to the root cause of the topic.
3/ Real-time: Everything happens in milliseconds.
You can trust SentiSum tags to underpin strategic change across your business.
P.s. We cover 100s of languages and channels (even voice.)
Simple customer complaint root cause analysis
SentiSum's machine learning-based analytics uncovers granular insight, whatever the scale of complaints you have.
You'll suddenly have access to quantitative topics and their sentiment, in enough detail to uncover what's responsible and work on a fix.
Get 'reasons for complaints' trends in your inbox
Our daily digest email ensures you stay up-to-date with performance, top ticket drivers and the largest rises and falls in topics.
Subscribe anyone to bring company-wide access to support data. You'll see a refocus on customer experience that helps you to reduce ticket volumes.
To be actionable, it must be simple
With SentiSum's simple-to-use UI, you won't need technical know-how to understand the topic and sentiment of every support ticket.
You, or anyone in your company, can simply switch between contact channels, filter by topic or subtopic, and have instant access to the issues facing your customers across every contact channel.
Why replace your existing tagging system?
Most tagging systems take a lot of manual work or the insights can't be trusted to back up business decisions. Usually tags are inaccurate, inconsistent or generic, so customer support is like a black box.
Before SentiSum
- Tags are broad and require manual digging
- Tags become outdated so insight is missed
- Tags are based on 'keywords' = inaccurate
- Tags are applied inconsistently by agents
- Reporting is still time-consuming
After SentiSum
- Tags are granular and get to the heart of the issue
- Tag taxonomies are continuously up-to-date
- Tagging is machine-learning based = accurate
- Tags are applied consistently to 100% of your tickets
- Reporting is made simple with automation
- Tags can be trusted to guide triggers, automations and company-wide improvements
All your channels under one roof
SentiSum is a single source of truth. In one simple-to-use dashboard, you'll understand the topic and sentiment of every customer conversation, survey and review.
Why is customer complaints analysis important?
Customer support is frequently described as a 'black box'. There's endless amounts of data hidden away in those customer conversation and complaints but it's largely inaccessible. Uncovering that data is critical. And reporting it companywide creates a competitive advantage. When you create access to complaints, by quantifying large volume of qualitative data, you can help your team to start tackling bad CX, customer disatisfaction and drivers of churn in a heartbeat.
.jpg)
“We can now proactively identify negative feedback, respond to it, and fix issues.”
Jack Ames
Contact Centre Manager
See it in action
.png)