Customer Service

6 Ways to Use AI Ticket Tags to Optimise Customer Service

6 Ways to Use AI Ticket Tags to Optimise Customer Service
Customer Service Researcher
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6 Ways to Use AI Ticket Tags to Optimise Customer Service

As yet, natural language processing (NLP) technology is the only answer to efficiently, consistently and objectively uncovering topic and sentiment insight from support tickets.

Imagine that you work for an eCommerce company selling furniture.

A customer contacts your support team and requests a refund. They say, “Hello, half the screws are missing from the package so I can’t put the furniture together. I’d like my money back please.”

NLP would ‘look’ at the ticket and in real-time it'd apply tags like ‘refund request’, ‘missing item’ and ‘screws’. This is a classic example of AI-driven support ticket tags.

This insight is just the first step. Add in an automated ticket tagging system and the topic could trigger that ticket to route directly to the refunds team to handle, and because ‘refund requests’ are usually indicative of a customer about to churn, the system would prioritise the request as 'urgent'.

Over time, as trends appear in the topics, you might realise that screws are responsible for 75% of refund requests.

You could pass that knowledge to your operations team who build a process to double check the screws are there. Refunds reduce, support ticket volume reduces, and your customers are happier.

I won’t continue to spoil the fun, but the list of possibilities goes on and on.

Here are 22 ways you can use AI ticket insights to optimise your business and drive bottom line growth.

6 Use Cases for AI Customer Service Tags

We've built the most accurate AI ticket tagging software on the market today, and have built support ticket automations that fulfil all of the points mentioned here. Reach out to us for a product demo or read more about how AI in customer service can help fast growing companies.

#1 Reduce average handle time

  • Auto-route tickets: Based on AI ticket topic tags, we can create rules and triggers that route tickets directly to the right team.
  • Auto-prioritise tickets: Based on urgent topics or those particularly linked to bad CX, assign priority to tickets so they are handled more quickly.

Related read: How to properly prioritize customer support issues

#2 Improve agent productivity

  • Auto-suggest macros: AI understands the topic and can suggest pre-created responses to agents. They'll save time digging for the right response.
  • Improve agent training: AI topic tagging allows you Surface common issues, niche issues and highly impactful issues to centre agent training around.
  • Automatically turn negative social media comments and reviews into tickets: Save agent time reviewing and responding to negative comments and reviews but having AI identify them and auto-generate a ticket that is added to the queue.

#3 Reduce ticket volume

  • Reduce ticket volume: Whether it's contacts-per-order or another volume metric, having clarity on 'reasons for contact' enables you to tackle those problems at the root cause.
  • Build a knowledge base: Curate a data-driven knowledge base that addresses the real issues facing your customers.
  • Anomaly detection and trend analysis: Surface unexpected tickets trends in issues facing customers so you can proactively prevent the causes for other customer
  • Link tickets to CSAT: AI-driven topic tagging and sentiment analytics allows you to understand drivers of your survey results. By linking those CSAT survey to the support ticket topics that drive them, AI allows you to tackle dissatisfaction drivers at the root cause.

We've built the most accurate AI ticket tagging software on the market today, and have built automations that fulfil all of the points mentioned here. Reach out to us for a product demo to see how we enable all this to happen.

Companywide Benefits of AI Ticket Tags

Implementing AI support ticket analytics and automation has company-wide benefits.

By connecting the work of customer service to the big picture company goals: growth, retention, and product adoption, we believe the customer support will become the most strategically valuable part of any business.

Here are some of the wider uses of support ticket insights:

#4 Customer experience benefits

  • Simplify your analytics: Instead of manually tagging data points, AI can uncover insight from +100,000 surveys, tickets or reviews in seconds.
  • Increase lifetime value: Understand and tackle the root cause of customer pain points so that customers stay satisfied, loyal and spend for longer.
  • Bring the customer to life: Use quantitative insights confidently to ensure ‘customer-centric’ thinking underpins the strategic roadmaps of every department.
  • Monitor third-party vendor performance: Easily access quantitative evidence that pinpoints which of your providers are negatively impacting your customers.
  • Customer journey mapping: Easily overlay data at every customer touchpoint within your customer journey mapping exercise.
  • Prevent harmful events: Automatically get alerted to potential harmful comments on social media or reviews left for your brand.
  • Track key moments: Automatically surface when things go wrong at times that are key moments for customers using your product or service.
  • Replace surveys: Surveys can be biased, costly and time-consuming, all of which can be a thing of the past with AI support ticket insights.

#5 Product benefits

  • Optimise eCommerce conversions: Easily identify key friction points on your website to reduce barriers to checkout.
  • Track product performance: Track the impact of new product or feature releases on support ticket volume.
  • Roadmap prioritisation: Identify user feedback, feature requests and pain points

#6 Marketing team

  • Elevate what your customers love: Discover what your customers love about you and double down on those in brand communications, copy and advertising.
  • Direct content strategy: Like interviewing your customers at scale, identify problems and areas of interest to address in your content marketing.

Doesn't all this sound exciting?

We've built the most accurate AI ticket tagging software on the market today, and have built automations that fulfil all of the points mentioned here. Reach out to us for a product demo to see how we enable all this to happen.

Join a community of 2139+ customer-focused professionals and receive bi-weekly articles, podcasts, webinars, and more!

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6 Ways to Use AI Ticket Tags to Optimise Customer Service

March 10, 2021
Ben Goodey
Customer Service Researcher
In this article
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Is your AI accurate, or am I getting sold snake oil?

The accuracy of every NLP software depends on the context. Some industries and organisations have very complex issues, some are easier to understand.

Our technology surfaces more granular insights and is very accurate compared to (1) customer service agents, (2) built-in keyword tagging tools, (3) other providers who use more generic AI models or ask you to build a taxonomy yourself.

We build you a customised taxonomy and maintain it continuously with the help of our dedicated data scientists. That means the accuracy of your tags are not dependent on the work you put in.

Either way, we recommend you start a free trial. Included in the trial is historical analysis of your data—more than enough for you to prove it works.

As yet, natural language processing (NLP) technology is the only answer to efficiently, consistently and objectively uncovering topic and sentiment insight from support tickets.

Imagine that you work for an eCommerce company selling furniture.

A customer contacts your support team and requests a refund. They say, “Hello, half the screws are missing from the package so I can’t put the furniture together. I’d like my money back please.”

NLP would ‘look’ at the ticket and in real-time it'd apply tags like ‘refund request’, ‘missing item’ and ‘screws’. This is a classic example of AI-driven support ticket tags.

This insight is just the first step. Add in an automated ticket tagging system and the topic could trigger that ticket to route directly to the refunds team to handle, and because ‘refund requests’ are usually indicative of a customer about to churn, the system would prioritise the request as 'urgent'.

Over time, as trends appear in the topics, you might realise that screws are responsible for 75% of refund requests.

You could pass that knowledge to your operations team who build a process to double check the screws are there. Refunds reduce, support ticket volume reduces, and your customers are happier.

I won’t continue to spoil the fun, but the list of possibilities goes on and on.

Here are 22 ways you can use AI ticket insights to optimise your business and drive bottom line growth.

6 Use Cases for AI Customer Service Tags

We've built the most accurate AI ticket tagging software on the market today, and have built support ticket automations that fulfil all of the points mentioned here. Reach out to us for a product demo or read more about how AI in customer service can help fast growing companies.

#1 Reduce average handle time

  • Auto-route tickets: Based on AI ticket topic tags, we can create rules and triggers that route tickets directly to the right team.
  • Auto-prioritise tickets: Based on urgent topics or those particularly linked to bad CX, assign priority to tickets so they are handled more quickly.

Related read: How to properly prioritize customer support issues

#2 Improve agent productivity

  • Auto-suggest macros: AI understands the topic and can suggest pre-created responses to agents. They'll save time digging for the right response.
  • Improve agent training: AI topic tagging allows you Surface common issues, niche issues and highly impactful issues to centre agent training around.
  • Automatically turn negative social media comments and reviews into tickets: Save agent time reviewing and responding to negative comments and reviews but having AI identify them and auto-generate a ticket that is added to the queue.

#3 Reduce ticket volume

  • Reduce ticket volume: Whether it's contacts-per-order or another volume metric, having clarity on 'reasons for contact' enables you to tackle those problems at the root cause.
  • Build a knowledge base: Curate a data-driven knowledge base that addresses the real issues facing your customers.
  • Anomaly detection and trend analysis: Surface unexpected tickets trends in issues facing customers so you can proactively prevent the causes for other customer
  • Link tickets to CSAT: AI-driven topic tagging and sentiment analytics allows you to understand drivers of your survey results. By linking those CSAT survey to the support ticket topics that drive them, AI allows you to tackle dissatisfaction drivers at the root cause.

We've built the most accurate AI ticket tagging software on the market today, and have built automations that fulfil all of the points mentioned here. Reach out to us for a product demo to see how we enable all this to happen.

Companywide Benefits of AI Ticket Tags

Implementing AI support ticket analytics and automation has company-wide benefits.

By connecting the work of customer service to the big picture company goals: growth, retention, and product adoption, we believe the customer support will become the most strategically valuable part of any business.

Here are some of the wider uses of support ticket insights:

#4 Customer experience benefits

  • Simplify your analytics: Instead of manually tagging data points, AI can uncover insight from +100,000 surveys, tickets or reviews in seconds.
  • Increase lifetime value: Understand and tackle the root cause of customer pain points so that customers stay satisfied, loyal and spend for longer.
  • Bring the customer to life: Use quantitative insights confidently to ensure ‘customer-centric’ thinking underpins the strategic roadmaps of every department.
  • Monitor third-party vendor performance: Easily access quantitative evidence that pinpoints which of your providers are negatively impacting your customers.
  • Customer journey mapping: Easily overlay data at every customer touchpoint within your customer journey mapping exercise.
  • Prevent harmful events: Automatically get alerted to potential harmful comments on social media or reviews left for your brand.
  • Track key moments: Automatically surface when things go wrong at times that are key moments for customers using your product or service.
  • Replace surveys: Surveys can be biased, costly and time-consuming, all of which can be a thing of the past with AI support ticket insights.

#5 Product benefits

  • Optimise eCommerce conversions: Easily identify key friction points on your website to reduce barriers to checkout.
  • Track product performance: Track the impact of new product or feature releases on support ticket volume.
  • Roadmap prioritisation: Identify user feedback, feature requests and pain points

#6 Marketing team

  • Elevate what your customers love: Discover what your customers love about you and double down on those in brand communications, copy and advertising.
  • Direct content strategy: Like interviewing your customers at scale, identify problems and areas of interest to address in your content marketing.

Doesn't all this sound exciting?

We've built the most accurate AI ticket tagging software on the market today, and have built automations that fulfil all of the points mentioned here. Reach out to us for a product demo to see how we enable all this to happen.

Frequently asked questions

Is your AI accurate, or am I getting sold snake oil?

The accuracy of every NLP software depends on the context. Some industries and organisations have very complex issues, some are easier to understand.

Our technology surfaces more granular insights and is very accurate compared to (1) customer service agents, (2) built-in keyword tagging tools, (3) other providers who use more generic AI models or ask you to build a taxonomy yourself.

We build you a customised taxonomy and maintain it continuously with the help of our dedicated data scientists. That means the accuracy of your tags are not dependent on the work you put in.

Either way, we recommend you start a free trial. Included in the trial is historical analysis of your data—more than enough for you to prove it works.

Do you integrate with my systems? How long is that going to take?

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What size company do you usually work with? Is this valuable for me?

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What is your term of the contract?

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How do you keep my data private?

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Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

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