The world and all of its industries have adapted to the technological changes and new era of information data. Well except for one – the customer service industry. They are
The world and all of its industries have adapted to the technological changes and new era of information data. Well except for one – the customer service industry. They are lagging behind because they are reluctant to make a major change in their operations and feel complacent.
The way customer service organizations collect data now is mainly through surveys. As you can imagine, not the most effective way. It was found that only 2% of customers actually respond to surveys. And if they do it is overwhelmingly likely that they were either extremely happy or angry at the service provided. So not only do surveys not deliver you many responses, but the responses you receive are most likely very biased.
Manual methods simply can’t compare to new technologies that can track 100% of conversations across all channels of communication at the same time and deliver you the breakdown.
In almost every customer service organization there are crucial positions called QA specialists (Quality Assurance). Their main priority is to maintain the quality of customer service provided by agents for every customer interaction. The way they do this right now is by manually reviewing calls they usually randomly select because they know they can’t cover all of them. This results in only 2-5% of calls being monitored which paints a hazy picture at best of support/agent performance.
Technology solutions such as Summatti can automate a large part of their process. As seen in the graphic, Summatti for example can fully automate the measure, score, analyze, and feedback stages. This means that the QA specialist can focus a majority of their time on improving and working with the data to find solutions, rather than collecting it.
One of the best advantages of using a technology solution comes with real-time notifications and feedback systems. This is what enables the QA specialists to coach in real-time versus later. What usually happens is when a QA specialist finds that one of their agents is consistently struggling, they would have to manually sort through their many calls and analyze them. The problem is that because the manual process is so time-consuming the agent would get the feedback 1 week later.
It’s been found that instant feedback is significantly better at changing an agent’s behaviours and mistakes than a delayed feedback process. It’s the reason real-time notifications are so important now. If your goal is to have the best team of agents, quick and accurate feedback is a must.
When it comes to facilitating a consistent customer experience across channels, there is really only one way. By having your agents perform consistently. Your agents regardless of channel should be working with similar scripts, respond to complaints in a consistent manner, and uphold your business’s values.
Using AI we can tell if the customer is frustrated because of something the agent said, if their tickets are consistently being escalated (brought to management) etc. The reason technology is so great at creating a consistent customer experience is because when you’re measuring agent performance, the technology is using the same “measuring stick” to track everyone. And if you want to be able to compare agents you need to be measuring them equally.
If you’re in the customer service industry you’ve definitely heard of NPS (Net Promoter Score). It’s an important metric that gives you an idea of the customer’s “likelihood to recommend” your company. And although it’s widely used across the industry it doesn’t quite give you the full story.
The current methods to get NPS is the key problem. It hosts issues such as small sample size (about 2%) and customer bias. To go beyond NPS, AI is a great tool to consider. There is no need for surveys when AI can pick apart that information for you directly from communication channels with customers. It does this by listening and understanding the human language as it’s spoken and can even understand the context of the conversation. AI is the driver behind going beyond NPS that is cost-effective and scalable across 100% of customer interactions.