Automate your Intercom sentiment analysis using AI

SentiSum's AI-powered analytics applies granular topic and sentiment tags in real-time. Insights from every email, chat, call and survey become easy to access, so you can report on tags in minutes and drive company wide improvements.

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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.
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2. Granular: Tags get to the root cause of the topic.
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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.)
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About our Tech

Understand chat and survey trends at a granular level

SentiSum understands multiple topics in each conversation and applies one consistent taxonomy to your entire Intercom conversation history. You'll have the volume and sentiment of every channel in one place, so you can simply switch between them and undertake root cause analysis in minutes—our customers always find things they didn't yet know about.

More than just sentiment analysis

When you have accurate tags across your Intercom conversation channels, you can leverage those to automate who gets tickets on each topic, which tickets are prioritized, and if to create a ticket when a customer leaves a negative review. Neat.

Report granular insight each week in minutes

We had a unique twist to the Intercom tag reporting process. Every day, anyone who subscribes gets up-to-date insights about what topics are trending in the customer support department.

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.
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•Tags become outdated so insight is missed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.

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