Self-service is changing, evolving from being primarily a cost reduction initiative to a revenue enhancer. No wonder then, that one of the key findings of the ContactBabel Inner Circle Guide to AI-powered Self-Service, sponsored by Enghouse Interactive, is that an overwhelming 91% of contact centres now have some form of self-service in place.
The Changing Nature of Self-Service
Self-service is no longer just touch tone IVR but has advanced to more sophisticated offerings from chatbots to automated speech recognition technologies. For all of these to succeed, it relies on access to a comprehensive, up to date knowledge base.
These depend on AI to help better understand customer queries and to provide fast, relevant answers. But where do you start? In our latest blog we take a look at some of the questions posed by the Inner Circle to Self-service and give you our insight on how to evolve your self-service.
1. Which Self-Service Solutions Work for Smaller Contact Centres or Those with Restricted Budgets?
Even smaller organisations already have some level of self-service on their websites which they can build on cost-effectively to create more capabilities. Start by identifying the most successful self-service areas of the website such as FAQs about products, order and delivery status, or product return requests.
You can then link this information to your voice IVR system, using text-to-speech and pre-recorded material, to provide self-service for customers that call in. Similarly, in web/text chat conversations, agents can share a link to the website self-service page and walk the customer through the process.
Another idea is to layer natural language AI capabilities into self-service via speech enabled IVR, voicebots and chatbots.
To limit the cost, focus on use cases with a very clear customer intent, a small number of well-defined responses, and a large number of interactions. A simple change like this could make a significant difference to call volumes and overall efficiency.
2. What Does Creating and Maintaining a Self-Service Knowledge Base Actually Involve?
To begin, the key challenge is collecting the right knowledge from across the organisation and turning it into articles with structured, visual content. Again, it’s best to prioritise creating content for the highest-value use cases, on which you get a large number of queries.
Once you’ve created your knowledge base, success largely depends on the usefulness of the information and how often it is accessed. Even if the information is accurate and high quality, if it’s rarely used, it isn’t delivering value. A good knowledge system will let you analyse and understand this.
While there is overhead in maintaining a knowledge base, automation and collaboration tools can minimise the effort involved.
For example, new self-service content can be created directly from agents’ written responses in real customer interactions. Appointing a knowledge manager to keep content organised ensures a consistent tone of voice and lets you easily incorporate and feedback from agents and consumers.
3. What Are the Most Common Pitfalls when it Comes to AI-Based Self-Service?
The biggest pitfall is trying to do too much too quickly. Start with a small number of self-service use cases, involving important interactions that generate high query volumes and have a small number of clear responses.
Creating a well-defined persona for the self-service virtual agent or bot is also key. Decide if you want the tone of self-service interactions to be friendly or humorous or very formal and serious. The personality of your bot should fit with your overall customer experience and brand strategy.
When measuring success two factors are key. First, remember it will take time for your bot to make a difference after it’s gone live.
It will require continuous testing and tuning, just like a new contact centre agent. And second, the bot should complement your contact centre agents, not replace them. So, make it easy for customers to escalate to a live agent who can access previous bot conversations.
4. What Measurable Benefits Should You Expect From AI-Enabled Self-Service?
Benefits can be seen in call and chat deflection rates and the percentage of interactions that are completely handled via self-service.
However, it can be tricky to assess this. Because you can’t be sure if customer call-backs relate to the same issue or something else. So, agent feedback and surveys that ask customers if self-service has answered their query can help deliver more accurate measurement.
As well as deflecting live interactions, AI-enabled self-service can help agents deliver more comprehensive and faster responses on the phone, email, or chat. This positive impact can be seen in metrics such as First Contact Resolution, and speed to answer.
However, if you focus AI only on deflection as a benefit, you could risk automating processes that are best handled by human agents.
It’s better to think of your AI as agents/channels with specific use cases. You can then define and track SLAs and usage to show senior management which tasks have been completed by automation, and the resulting cost savings.
In fact, many organisations don’t use AI and self-service to reduce agent numbers. Instead, it is to free up agents for more complex queries and tasks.
And by cutting the number of routine queries, self-service can improve agent satisfaction. This reduces attrition rates and produces savings in recruitment and training costs.
Increasing Contact Centre Self-Service Benefits
Self-service is growing in importance with the majority of contact centres now using it in some form or other. And rather than just being a way of reducing costs it’s now turning into a strategy for improving overall customer satisfaction and increasing ROI for the business.
To gain its full benefits self-service needs to be underpinned by the right knowledge. Be focused on the right areas, to deliver a seamless experience to customers.This blog post has been re-published by kind permission of Enghouse Interactive – View the Original Article
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