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Zendesk chat analytics integration

SentiSum's AI engine categorises Zendesk conversations with unparalleled accuracy and granularity.

Simplify reporting with access to real-time trends & insights across every customer contact channel—even voice.

Find us in the Zendesk marketplace.

Customer support ticket analytics and insights using AI automation

"No more tagging, just root cause insights on-demand. Every team has started using support insights!"

Director of Customer Service, +$50m revenue fast-growth company

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What it looks like to use machine learning tagging in your customer support system

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.)

Get granular insights from every conversation channel

Auto-apply granular tags to every ticket within Zendesk

Our insights dashboard makes tag insights accessible, but we can also push tags directly to Zendesk so they can be used for analysis, routing and prioritisation.

Watch the short video to see it in action.

Understand and improve customer satisfaction

Our analytics solution ties support tickets to CSAT surveys. You'll have a 360º view of every feedback and support channel, supercharge with additional context.

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A daily email full of customer insights

Make every Zendesk channel accessible

Like Google for customer support, you'll be able to answer questions from other teams by simply searching for an answer.

It's truly multichannel. We've even cracked voice—so you can search historical phone calls for insight.

Say goodbye to manually analytics and reporting. And welcome in a new age of insight that's uniform, easy, searchable and impactful.

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.

Must-reads

ai buying guide cover
SOFTWARE

You must test an AI-analytics tool on your own data.

Read more
Impact of AI tagging Image
IMPACT

How to use ticket tags across your organisation.

Read more
Machine learning ticket tagging
TECHNOLOGY

Machine learning vs. Keyword tagging

Read more
“We can now proactively identify negative feedback, respond to it, and fix issues.”

Jack Ames

Contact Centre Manager

See it in action