Conversational Intelligence: 5 Use Cases to Enhance Contact Center Performance – CX Today

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Almost half of the contact center agents don’t have the skills they need to deal with the current demands of their job – according to Calabrio’s recent State of the Contact Centre report.


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To make matters worse, progress doesn’t appear to be on the horizon as managers can’t agree on the necessary path of training that would rectify the situation.

Visibility is the answer, and conversational intelligence solutions are the knights in shining armor, spotlighting critical areas for agent development.

Yet, these solutions offer much more than that. They also shed light on broken processes, contact center demand drivers, customer sentiment, and much more.

The following five use cases showcase their versatility and emphasize how service leaders can leverage the tech to bolster crucial customer, agent, and business outcomes.

1. Tag Interactions With Intents Automatically

The best contact centers often strategize over their most prominent contact reasons or “intents”.

Such strategies include implementations of self-service, conversational AI, and automation to address common demand drivers and drive the anticipated ROI.

However, thanks to agents manually logging these intents, without sufficient time or coaching, those strategies often fail to meet expectations.

Conversational intelligence solutions that automate tagging, gather accurate intent data, and dashboard it, ensure contact centers can lay the foundations for improvement initiatives.

Moreover, that data may support CX teams in pinpointing customer journey pain points, workforce management teams in perfecting their forecasting and scheduling, and coaches in delivering targeted and personalized coaching. (More on this below!).

2. Embrace Quality Automation

Thanks to conversational intelligence engines, contact centers can draw insights from every conversation, automatically identifying how effective individuals are in dealing with different elements of an interaction across customer touchpoints.

As such, contact centers can understand where improvements can be made, with metadata attached for further analysis.

Previously, many contact centers attempted to do this via the time-consuming completion of manual evaluation forms.

However, now contact centers can assess the performance of live and virtual agents on a much deeper level – and hone in on contacts that likely present the best learning opportunities.

Yet, the tool also showcases which agents typically perform best across specific intents.

Now this is excellent for reward and recognition. But, as Scott Budding, Manager of Sales Engineering at Calabrio, also noted:

“By diving into how the best agents handle specific interactions, the contact center can create new case management flows and tailored coaching programs, so the rest of the team follows their lead.”

Moreover, contact centers can run several other performance-improving initiatives with Auto-QA. These range from keeping tabs on new agent proficiency to informing new contact routing and automation strategies.

The possibilities are boundless!

3. Measure First Contact Resolution (Accurately!)

First contact resolution (FCR) and short wait times are the two “most important factors” for customers when contacting customer service – according to ContactBabel.

As such, FCR is a mission-critical metric for contact centers to track. The only trouble is – without conversational intelligence – businesses can’t measure FCR accurately.

Sure, they could send out a post-contact survey, but what if the customer hasn’t yet realized that the solution the agent presented won’t work? And, if they have, they still may not complete your survey.

Other businesses have tried to track repeat contacts by identifying when an identical number makes contact multiple times Yet, this isn’t a true indicator of FCR either, as the customer may reach out about different issues.

The accurate way to do this is by tracking customer intent and repeat contacts together to ensure the second contact relates to the first. Conversational intelligence systems can do this and dashboard FCR rates so the contact center can track the metric accurately over time.

4. Run Root Cause Analysis

When a contact center tracks FCR accurately, it can split the metric across different customer intents.

By doing so, service leaders can isolate the specific queries customers often have to recontact customer service regarding.

From there, they can use the conversational intelligence platform to spot pain points and address them via technology, process, or coaching changes.

“So often we see contact centers fighting against the symptoms on an issue,” said Budding. “Conversational intelligence allows them to get more granular.”

“Service leaders can get to the bottom of what’s causing the issue in the first place, monitoring keywords and phrases from a group of contacts that share the same customer intent.” – BLOCK

With that information, contact centers can work backward, dive into the customer journey, and amend the broken processes they’ve grudgingly learned to live with.

Importantly, the conversational intelligence solution is also able to provide a constant temperature check, informing contact centers as to whether or not the intervention(s) had the desired impact.

5. Track Customer and Agent Sentiment

Conversational intelligence systems monitor sentiment across every conversation. As such, the service team generates more insight into customer satisfaction than ever before.

The contact center can then use that data in many ways. For instance, they can track how sentiment changes across channels and intent.

In doing so, an organization can target changes to business processes as well as offer personalized coaching and training to agents which will deliver the best experience to agents when serving customers who are using their channel of choice.

“This level of insight will enable you to make informed decisions on changes in your business which can reduce contact volumes being presented to your human workforce,” added Budding.

“For example, where sentiment is high and outcomes are positive when a customer accesses a particular service through a virtual agent, perhaps you can update your Voice IVR to offer a link for that service rather than the customer waiting in a queue. Think of it as a contact deflection strategy that customers won’t hate!”

Yet, perhaps most fascinating is how contact centers can look at correlations between sentiment and NPS (Net Promoter Score) as well as correlations with different customer outcomes.

Such a level of insight enables sales and marketing teams to make informed changes to their customer engagement, sales and retention strategies.

“By spotting when an agent is struggling, the supervisor can reach out and support them, perhaps offering a post-contact break to recharge,” Budding continues. “That’s next level well-being.”

Also, it’s possible to track historical sentiment levels. So, if sentiment drops over the course of weeks, the supervisor can interact with the agent directly, uncover any teething issues, and work to resolve them. Doing so is excellent for agent mental health and decreases absence/attrition rates.

Calabrio: Giving Your Contact Center 20:20 Vision

Calabrio offers the conversational intelligence platform for contact center leaders to run all these initiatives and many more.

Its solution also detects dead airtime, uncovers cross-talking, and creates alerts and triggers so supervisors can gain even more insights and – crucially – act on them.

As such, service leaders unlock 20:20 vision alongside the assistive tools to power the contact center team to perform to the best of their ability.

Eager to learn more about these capabilities? If so, visit:

This post was originally published on 3rd party site mentioned in the title of this site

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