Naming Categories and Sub-Categories
Simple Nouns or phrases are not enough to name categories and sub-categories. This is a challenge with the traditional way of triaging category and sub-category. The process requires algorithms to consider word frequencies, probabilistic importance and contextual importance. This methodology gives us a way to be consistent and standardizes the way to define problems to operate in autonomous mode.
We have also seen that an external “source of truth” can be created by experts in a different system of record. Ascendo is also able to connect to this external system of records and drive predictions in semi-autonomous mode. We find this scenario is popular with customers who have a very large install base, extensive categorization and are looking to drive consistency in agent quality.
Manages Your Knowledge
I'm a paragraph. Click here to add your own text and edit me. It’s easy. Just click “Edit Text” or double click me to add your own content and make changes to the font. Feel free to drag and drop me anywhere you like on your page. I’m a great place for you to tell a story and let your users know a little more about you.
This is a great space to write a long text about your company and your services. You can use this space to go into a little more detail about your company. Talk about your team and what services you provide. Tell your visitors the story of how you came up with the idea for your business and what makes you different from your competitors. Make your company stand out and show your visitors who you are.
01
Understanding the Problem
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02
Recommendation Engine
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03
What is behind the engine?
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04
Categories & SubCategories
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05
A Classic Example
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06
Conclusion
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Every interaction data is automatically categorized and indexed without bias.
Every interaction data is automatically categorized and indexed without bias.
Every interaction data is automatically categorized and indexed without bias.
Every interaction data is automatically categorized and indexed without bias.
Every interaction data is automatically categorized and indexed without bias.
Every interaction data is automatically categorized and indexed without bias.
Support with Ascendo
Support without Ascendo
Vs
The list of problems keeps expanding as product expands
.
Thousands of historical data points are needed.
Each data point needs to be filled in with expert knowledge and accurately defined.
Inaccurate learning.
Even for a small support team, about 17.5 hours per week is being spent on manually classifying problems.
Possibility of multiple unknown issues.
Multiple people talk about the same issue differently!
Mapping new problems with the existing list of problems causes inaccurate classes of category assignment.
Manual work hurts getting Voice of the customer feedback into product in a timely manner.
Not understanding issues in real time is an impediment to provide proactive support.
As product expands, new categories are automatically created.
Every interaction data is automatically categorized and indexed without bias.
Every agent is an expert so escalations and onboarding goes down.
Consistent learning.
Realtime categorization is right at your fingertips.
No surprises with unknown issues.
Consistency in how issues are discussed across the teams.
New problems are mapped on its own.
Real time Voice of the customer feedback into product.
It is not just support is fully proactive but support operations is fully proactive.
