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Top 5 Use Cases for Delivering Business Value with Speech Analytics

July 21, 2022 | | Customer Experience, Speech Analytics

Speech Analytics has exploded in adoption in recent years.  As consumers get increasingly survey fatigued, many customer experience teams are looking for other ways to gather insights.  Speech Analytics tends to fit the bill – it utilizes customer interaction recordings of conversations already occurring and provides ready insights that can uncover unknown issues, quantify known issues, and give practitioners insights into their business that is otherwise difficult to achieve.

Done properly, the use of Speech Analytics is often a path to immediate benefits, whether you are searching for cost savings or revenue generation.  Most of our clients who have recently implemented a Speech Analytics platform see a complete payback of the implementation costs AND our consulting within a few short months.

So – how do they do it?  Here are a few examples of the most common ways of finding value :

1. Reducing Repeat Calls (or Boosting FCR)

First Call Resolution (FCR) is a worthy goal of any organization that benefits both customers and the company.  No customer wants to call or otherwise contact a company multiple times to accomplish the same task or issue.  And no company wants to take on the operational costs of fielding multiple contacts from the same customer about the same task or issue.

Speech Analytics is uniquely designed to tackle this problem.  Searching for multiple terms like “I called last week” or “when I called last time” and all the similar variations reveals a good quantification of how many Repeat Calls are truly occurring.  Overlaying this set of contacts with searches for common call drivers like billing, returns, payments, product support, digital navigation, and so on will then illuminate what kinds of customer contacts are driving Repeat Calls most frequently.

One client already knew they had a data replication timing issue with their CRM systems that sometimes led to incorrect information driving repeat calls.  The cost to add the hardware and modify the interfaces and data stores was just too great – or so they thought. After uncovering the number of Repeat Calls driven by the issue (as well as duration of calls when a lengthy workaround was employed to overcome the issue), and determining the associated cost, it suddenly became a no brainer.  The total quantifiable benefit was annually about 2x the cost of the needed system implementation.

2. Improving Effectiveness of Self-Service Channels

While nearly all customers prefer not to call more than once for the same reason, many customers prefer not to have to call at all.  So what do they do first?  Try to find what they need or get what they need done online or through an app.  Only if (or when) that fails, do they call the company’s customer service line.  So, just like in the first use case, we have a situation that should benefit both the customer and the company – a customer experience win-win if the top root cause(s) can be found and addressed.

Looking for interactions that include phrases like “I tried online” and other related phrases can reveal how often and for what reasons customers are calling after an unsuccessful attempt through self-service options.  Here’s a quick spoiler: the top reason is often due to login challenges.

With another client, username and password reset calls were just considered the cost of ensuring data security for their customers.  We uncovered a set of usability challenges that had no impact at all on security but were a collective game changer for providing accessible self-service options and avoiding the cost of unnecessary calls.  The improvements included re-writing challenge questions that were more relevant for their demographic, better on-screen guidance regarding character minimums and character types, improved IVR prompts, and re-design of a problematic process for customers to reset their own password.  It turns out that all of these were designed with security in mind and no thought to ensuring they were intuitive and usable.  In the end, this case study was not based on any new exciting discovery, but it certainly paid the bills with happier customers and fewer calls.

3. Finding New Applications for Automation

When it comes to gaining efficiencies and reducing costs, many companies turn to automation to help them. However, in a call center, customers generally prefer to interact with a live person making automation rather difficult. Looking internally and finding ways to automate actions for agents rather than customers can reduce handle times, improve customer experience, and limit repeat calls.

A client from the healthcare industry was trying to solve the problem of long handle times, higher than average repeat calls, and customer escalations. The agents were dealing with complex healthcare situations that required them to ask for supervisor assistance. Most supervisors were constantly tied up leading the agents to put the customer on hold for long periods of time. This inevitably frustrated the customer and lead to a poor customer experience. The solution was multipronged and involved AI. With Speech Analytics, the customer was able to perform call studies and drill down to the topics that were most likely to confuse agents. Calls matching these categories were much more likely to experience repeat calls due to potential misinformation or to be escalated to a supervisor. The customer took the categories from Speech Analytics and built an AI tool that would allow agents to ask questions and get instant answers. The AI tool was fed information based on situations and categories pulled from Speech Analytics. For example, if a customer called in and wanted to dispute a claim on their account but the agent was unfamiliar with this process, they could simply use the text-based AI tool and ask how to complete that task. The AI tool would then respond with step-by-step instructions for that agent.

By using Speech Analytics, the client was able to see the root causes handle time, escalations, and repeated calls. The subsequent action not only improved the customer’s experience but also improved the employee experience. Employees saw a reduced amount of emotional calls and found themselves more confident in situations where they were unsure of the answer.

4. Reducing Handle Time

Not unlike the Repeat Calls example above, reducing average handle time (AHT) is another classic cost saver and, when done right, is a big customer pleaser too.  Very few customers want to call in, but when they do, they want things taken care of quickly and efficiently – it needs to be part of the Ease in customer interactions that are such an integral part of great customer experiences.

As another example, we worked with a bank that performed outbound calls to remind customers holding auto loans that they missed a payment and were well past due.  Often, the customer would ask what the impact to them would be of their missed payments, how does this get reported to credit reporting agencies, how does this impact their credit rating.  When those questions popped up, you might as well get comfortable because the bank’s agents and the customer would embark on a 30-45 minute (sometimes longer) discussion of how credit ratings and credit reports work.  And, because this wasn’t a focus of their training and expertise, it was often a confusing, winding tale.  With Speech Analytics, we were able to quantify the impact and cost of those types of conversations (cost both in terms of real cost and opportunity cost of not reaching other customers to get payments).  And with that, the bank realized they could provide a lot more online resources and even set up a dedicated queue to help customers understand the credit impacts of their actions – while freeing up the outbound calling agents to do what they do best.  A win-win-win when you consider the customer got better help, the outbound agents were not forced into a difficult topic, and the bank saved costs while driving more revenue by reaching more customers who could make immediate payments over the phone.

5. Driving Increased Cross- and Up-Selling

A lot of companies realize when they are in an interaction with a customer (say, on the phone), that is often a good time to offer other products and services that the customer may want.  So – they try to turn customer service from just a cost center into a revenue center as well.  But, that takes new and different skills for contact center agents.  Even after training and perhaps some well-created tools to help them suggest the right products and services to the right customers, some just are better than others.  So how do we help the agents who cannot make the leap to making offers and completing a sale?  Well, with Speech Analytics, of course.  By sampling the high performers and comparing them to the low performers, you can pinpoint where the latter group might be missing the mark.  You can also search for and select several example calls of up-sell or cross-sell offers gone well.  Sure, you could find those examples through traditional methods and tools, but not to the scale and with the accuracy and speed enabled by Speech Analytics.

A wireless client of ours wanted to do just that, turn service calls into selling opportunities and then complete some sales.  With Speech Analytics, we could locate more calls with successful sales efforts and sample them to determine what the winning behaviors were that we could model for the agents who were struggling.  The particular tool we were using also included a comparison function – we could take the successful agents’ calls where a sale was made and compare them with the struggling agents’ calls where an attempt was made but no sale resulted.  With the push of a button, the system could then tell us what was different about the two sets of calls – terms and phrases, duration, agent talk time vs customer talk time, and so on.  With some interpretation and a little verification, it yielded some interesting insights about how the offer was first presented and how agents justified the offer being presented as being tailor-fit to the customer, among other things.  Those insights became a key part of ongoing training and the client saw very positive results over a short period.

These are the five most common value-creating case studies we’ve seen and helped clients achieve.  With a little guidance, we have taken numerous clients from “we’re not getting value from Speech Analytics” to “this thing is a gold mine!”  Of course, there are a lot more than just these five, and in fact, we often help on other customer experience improvements where the financial benefit may be harder to quantify.

Looking to turn your Speech Analytics program into a “gold mine”? Check out our guide, Contact Center Analytics: A Step-by-Step Guide to Drive Customer Success.

Contact Center Analytics: A Step-by-Step Guide