Enabling Ticket Deflection via Self-Service

12 Feb 2024

5 min read

Picture yourself inundated with customer support tickets, with new ones coming in all the time. Maybe you don't even have to picture it because it's happening to you right now! So it's understandable that you want to embrace ticket deflection. 

If only you could "deflect" these tickets, you think. If only you could waft them away like they were annoying wasps at a picnic. But these are your customers, and you shouldn't be thinking of them as irritants. 

However, ticket deflection is a legitimate tactic, but it's one that you need to use carefully. The best way to embrace it is by investing in effective self-service tools, and pointing customers towards that. 

Self-service is revolutionising how we deal with customer support requests by stopping them before they start. This approach has plenty of perks: happier customers who get help faster resolutions and fewer headaches for hard-working support teams are just the tip of the iceberg!

Are you all set to delve deeper into harnessing this knowledge? Let's go!

The Rise of Self-Service in Customer Service

It's evident that customer service is evolving quickly. Many customers now prefer to find solutions on their own terms without talking to a customer service agent, or having to contact a brand directly. This is often different depending on the demographics of your customers, with older ones tending towards contacting you on the phone and younger ones preferring to consult your knowledge base. 

This preference isn't just about being independent. It also comes from a desire for speed and convenience, with 24/7 availability playing a crucial role. A Zendesk report found that 50% of customers want to solve product or service issues themselves rather than calling support.

But it's not only about what customers want - companies are reaping benefits too. According to Forbes, businesses using self-service see lower costs and increased efficiency across the board.

The Challenge of Measuring Self-Service Effectiveness

Assessing the success of self-service is a tough nut to crack. It's not a straightforward query of whether purchasers attained their desired outcome, as that is only one component of the overall picture.

Traditional Metrics for Self-Service

We're all familiar with customer satisfaction scores (CSAT) and Net Promoter Scores (NPS). But when it comes to self-service, these metrics can be misleading. For example, high CSAT could mean your self-help resources are top-notch or it might signal that your live support is lacking so much users have no other choice but to rely on themselves.

A more useful measure may be deflection rate, which shows how many potential tickets were avoided thanks to your Help Centre. Yet even this stat has its flaws – like failing to consider user intent and overvaluing simple interactions at the expense of complex ones.

New Metrics for Self-Service Evaluation

Self-service has transformed the customer service landscape, but how can we truly measure its impact? Traditional metrics have their limitations. We need something more comprehensive.

The Self-Service Score

Welcome to a new way of looking at things: The Self-Service Score. It's not just about how many tickets are deflected or costs saved - it's also about assessing the overall effectiveness of your Help Centre in preventing support requests from even happening.

You'll find this approach gives you deeper insights and helps identify areas where self-service could be improved. A higher score means less burden on your human agents, allowing them to focus on more complex issues that require a personal touch.

In essence, by adopting these fresh evaluation methods, companies can get better results with self-service strategies and ensure customers continue to enjoy quick resolutions 24/7.

Reduction in tickets by Intent

If you are measuring the reasons why customers are getting in touch, known as "Intent Detection", then you can start to see whether you are getting more tickets in one area or fewer, which can be a measure of your self-service success.

As an example, if you notice that you are getting a lot of questions about how to return orders, then you would want to create some sort of self-service portal or help article to try and head this off at the pass. If the number of these questions goes down, you can infer that you have been successful. 

This is a good way to approach self-service. By categorising your customer service tickets, you can prioritise the areas that need the most attention and then work to try and create effective self-service options. 

The Role of Artificial Intelligence in Self-Service

Once you have a number of effective self-service options, and you are measuring that people are using them, and getting the results they want, then yu can start to use AI to make these more efficient.

Intent to Self-Serve

Using intent detection, you can start to triage your conversations. Perhaps there is a particular use case that needs to go to an agent 100% of the time, or others that can be solved within the chatbot. If one use case (such as our returns example) can generally be solved through self-serve means, then you can point customers towards these tools.

Self-Service using AI

One option for self-service that avoids building dedicated portals and tools is to use AI. Through deep integrations with shipping carriers, warehouse systems, order management systems, and other systems, AI tools can resolve many of the common issues in retail and ecommerce that a human would do.

This can then be activated via email, chatbot or any other channel that a brand uses. 

The Future of Self-Service in Customer Support

Customer support is heading towards a future where self-service options reign supreme. This isn't just speculation, but a trend backed by current technological advancements.

The Potential of AI and Automation

We're already seeing how AI and automation can streamline customer service processes. For example, chatbots have become more than just gimmicks on websites - they're now key tools for ticket deflection. But that's only scratching the surface.

With continued developments in machine learning algorithms and natural language processing capabilities, we expect to see even smarter self-service systems that understand complex queries, learn from past interactions, and deliver precise solutions quickly.

The Importance of Continuous Measurement and Improvement

No matter how sophisticated our tech gets though, it'll always need fine-tuning. Just like any other aspect of business operations or strategy implementation, it's crucial to regularly measure performance metrics such as resolution rates or customer satisfaction scores when it comes to your automated help offerings.

This will allow us to make sure these digital agents are meeting user expectations effectively while continuously improving their problem-solving abilities over time.