Analyze every call and not only improve contact center metrics, but increase operational efficiency, customer satisfaction and the overall customer experience.
Contact centers offer a wealth of insights, but the problem is most companies struggle to analyze and uncover important metrics and learnings from voice of the customer data. In fact, 74% of the 700 global contact center executives that Cisco surveyed this year said that one of their top challenges is analyzing their data.
And it’s no wonder. Transcribing calls isn’t a sustainable (or timely) method for companies looking to keep track of their top contact center metrics. And while analyzing sample conversations is faster, it leaves brands with an incomplete picture of performance and customer satisfaction. It’s true that there are some quantitative contact center metrics that can be easily tracked, such as call abandonment, average hold time, time per call interaction, and first-call resolution, but these KPIs can only tell companies so much.
It’s your contact center’s qualitative data — the context of the conversations between agents and customers — that reveals the whole picture of exactly what customers want, need help with, are frustrated with, and more.
And with the emergence of sophisticated artificial intelligence (AI)-powered speech analytics, it’s now possible to automate accurate and rapid contact center call transcription at scale. Companies can get an instant analysis of every call as it comes in, and learn from what their customers have to say in the moment. And take actions to prevent and resolve further issues faster than ever.
Here are the six important lessons you can learn from your customer calls using AI-powered speech analytics, helping to improve call center metrics at scale.
By analyzing the text of call transcripts, companies can distill frequent call topics and themes and get a pulse of the overall customer sentiment, especially when combined with acoustic analytics that can detect silent time, overtalk and vocal emotion. This enables more ways to see what topics are driving the most negative or positive customer impact.
While most contact centers prioritize responding to 100% of customer calls and achieving 100% customer satisfaction (CSAT) — both of which are worthwhile goals that can lead to bottom-line lifetime value and loyalty — there’s another opportunity for improvement that often gets overlooked. That is, figuring out why individuals are having to reach out to customer support in the first place and identifying process improvements that can be put into place to prevent future calls to begin with.
Phone call analysis can reveal where there are broken experiences in the customer journey that can be fixed, including what the top issues individuals are calling about and what the main drivers of long or unresolved calls are.
That way companies can not only get to the bottom of individual customer issues but also tackle the root causes underlying recurring problems. For instance, a small website or app error could be the reason behind countless calls, and the solution could be as simple as alerting the right tech team members to update a single line of code.
A holistic look at your contact center calls will help highlight agents who may need extra support as well as top performers who deserve to be recognized and rewarded and can even be tapped to offer mentorship to their peers. You should also be able to see if any persistent knowledge gaps exist and pinpoint areas for improvement to guide future training initiatives.
By taking a look at recurring questions and conversational themes across your contact center, you’ll be able to spot opportunities to create educational self-service materials, such as automated chat topics, help pages, FAQs, video tutorials, and more. After all, when contact centers and digital teams work together, brands are able to improve both digital and overall customer experiences.
Ultimately, once your company establishes the ongoing practice of analyzing contact center calls and is able to gain access to the insights detailed above in real time, your team will be able to optimize service delivery and customer experiences. A whole lot faster.
For instance, brands that use AI-powered speech analytics can improve first-call resolution (FCR) by finding enhancements that can be made to call scripts, response protocols, and customer service training initiatives.
Not only that, by comparing customer experiences across channels — calls, chat, support tickets, and emails — you can get a clearer view of the end-to-end customer journey, and identify further areas for improvement.
Whether you’re in a position to successfully monitor and analyze your contact center calls at scale or not, your customers are telling you a lot. It all comes down to being able to listen.