SentiSum's AI tagging software applies granular 'reasons for contact' to support tickets in real-time. We make insights from every ticket easy to access, so you can report on tags in minutes and drive company wide improvements.
"I can now easily show the rest of the company what's driving customer contact and together we can drive positive change. It's exciting."
Director of Customer Service, +$50m revenue fast-growth company
SentiSum's core technology is a machine-learning based NLP engine.
It's designed to uncover ticket tag insights that are:
1/ Accurate: It tags based on meaning, not keywords.
2/ Granular: It applies topics at a root cause level.
3/ Up-to-date: It surfaces new and trending issues.
You can trust them to underpin strategic change across your business.
P.s. We cover almost every language and contact channel (even voice).
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 team, can simply switch between contact channels, filter by topic or subtopic, and have instant access to granular AI tags across every contact channel.
There's no longer any need to rely on customer's self-tagging or an agent manually tagging tickets. Blast through queues by getting requests in the right inbox automatically, in real-time.
Tickets can often get lost in a large queue, with SentiSum's AI tagging you'll never miss a high priority issue and our machine-learning will surface trending or anomalous support ticket queries..
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.
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.
Intelligent automations, like AI tagging software, improves customer service in a number of ways.
Firstly, it allows you to leverage customer service data to understand issues facing your customers. Once you know what those issues are, you can start to fix them. This creates a beautiful feedback loop where, over time, customer service deals with less requests because your product and operations have been improved to the point where customers are, simply, happy.
Secondly, AI for customer service automations give back time to your agents. Agents with more time are happier and can spend more time talking to and engaging your customers.