The productivity-enhancing Freshdesk automation suite

SentiSum automates support ticket tagging, team-based routing and ticket prioritisation. Get Freshdesk customer insights at scale and implement new workflows to boost productivity.

Customer support ticket analytics and insights using AI automation

Trusted by the customer service leaders of the world's most loved companies

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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.)

Insights & automations for Freshdesk

Freshdesk automation suite | Easy integration

Freshdesk tagging automation

Automatically tag every ticket with topic, sentiment and priority. Use our tagging Freshdesk automation to uncover granular insights, reduce ticket volume and remove repetitive tasks for agents.

Ticket routing automation

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.

Ticket routing automation
Prioritise the urgent, angry and damaging tickets first

Prioritise the urgent, angry and damaging tickets first

Tickets can often get lost in a large queue, with SentiSum's prioritisation automation you'll never miss important tickets. In fact, you'll significantly reduce first response time to those tickets.

Prioritisation is an important Freshdesk automation to have in your belt. Not every customer request is equal, and with sentiment analytics-powered prioritisation, you'll know which tickets are most important automatically.

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  • Tags become outdated so insight is missed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.

How to prioritize customer service requests

It can be difficult to know which customer service requests to prioritize when you're bogged down in the day-to-day of contact centre life. However, by following a few first principles, it can be easier than you think.

Some people suggest 'first come, first serve', but that's too simplistic (and isn't really a prioritisation strategy' at all). We suggest categorising tickets in three ways: urgency, sentiment, and importance to the business.

Urgent requests are 'customer driven' in that they are requests that are time-sensitive to the customer. If a customer is about to catch a train and doesn't know where it is, you should prioritise that customer request above a refund request, for example.

Sentiment prioritisation places particularly angry or upset customers top of the list. Those customers are at a high risk of leaving you, spreading bad reviews and associating your brand with negativity, and should be prioritised accordingly.

Finally, we have 'importance to your business'. By pulling disparate data together, it's easy to see that some complaints, tickets and request topics are more closely associated with churn—i.e. a customer leaving your business never to return. Tackle those first to directly impact your bottom line.


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