Act on Early Warnings with Proactive Analytics

The onset and continuation of the COVID-19 pandemic has had widespread consequences for just about every aspect of our lives, from how we gather to how we educate our kids to how we do business. Who would have predicted the pandemic would hit so hard, last so long, and change so much?

Unfortunately, it wasn't even on most businesses' radars. Disaster recovery and business continuity plans often focus on scenarios such as, "What if our data center catches on fire?" or "What would we do if our contact center is hit by a tornado?" These plans can be effective for handling temporary, localized crises, but many organizations were caught flat-footed by the more widespread, long-lasting effects of COVID-19. In fact, in a survey administered by Mercer at the beginning of the crisis, a little over half of businesses admitted that they didn't have a business continuity plan to address a global pandemic.

This particular disaster is much different than a "fire in a data center" because of how far-reaching the effects are. Not only are businesses impacted, but their customers are, as well. In the early days of the lock downs, contact volume spiked and average handle times increased as people reached out to contact centers to get help for issues ranging from applying for unemployment to delaying mortgage payments.

Businesses (and government agencies) owe it to their customers to be prepared to assist them, no matter the circumstances. While organizations may not be able to control external factors that impact them and their customers, they can control their own readiness to deal with the unexpected.

These days, understanding customers is vitally important, not only because they need increased support, but because the survival of many businesses depends on holding on to every customer they can. One tool that helps businesses know their customers better, anticipate their needs, and proactively address emerging issues is interaction analytics.

A recent Aberdeen report stated that 59% of companies rate Augmented Analytics as critical or very important in the COVID-19 environment. Additionally, the study found that investments in analytics correlate to strong business outcomes. For example, 23% of businesses that widely use analytics experienced an increase in revenue despite the pandemic.

Let's take a closer look at the capabilities of interaction analytics and then discuss three use case examples.

What is interaction analytics software?

Interaction analytics, sometimes referred to as speech analytics, leverages artificial intelligence to review and assess call recordings and transcripts from digital channels such as email, chat, text (SMS), and social messaging. Because it's automated, an interaction analytics tool can scour through 100% of interactions, thereby delivering a more comprehensive view of quality and customer experience than traditional sampling methods can provide.

Interaction analytics zeroes in on key words and phrases to identify contact drivers, potential problems, compliance issues, and more. For example, if the phrase "couldn't check out" is suddenly used more frequently, that can alert the contact center that there may be a problem with the website's check out functionality. Additionally, interaction analytics can key in on words like "disappointed," "frustrated," "happy," or "wonderful" to determine customer sentiment.

Customer sentiment can also be derived from characteristics of a phone call. Long pauses, voice pitch and volume, and the caller and agent talking over each other are examples of qualities that can be used to determine both customer and agent sentiment. The analytics tool can develop a sentiment score for each customer and roll it up to an overall customer sentiment score. The same is true for agent sentiment.

The information provided by analytics software gives contact centers the ability to provide proactive customer service and gain more insight into their operations and the customer experience.  Here are three use cases that provide specific examples of the value of interaction analytics.

Use case #1 - Establish better visibility 

Contact center leaders spend a lot of time analyzing results and investigating issues. The dynamic nature of the business requires that of them. But there's always more to be done - more process inefficiencies to find and squeeze out, more customer journey pain points to identify and eliminate, more relationships to save, and more general issues to research and address.

Interaction analytics can bring more visibility to all these areas, providing more insight and color commentary to data on reports and dashboards. Aberdeen found that 27% of contact center leaders want to have more visibility into their operations in order to improve efficiencies. Analytics can support this goal by being the extra eyes and ears every contact center manager wishes she had. Even better, this is a resource that listens and analyzes 24/7.

Contact centers can "aim" their analytics software at specific customer pain points they want to investigate. For example, if they want more information about short calls, analytics can provide analysis of calls below a certain length. This analysis might help identify routing issues, behavioral or training problems, and call types that would be good candidates for IVR self-service.

Analytics can also help contact centers improve the processes they use to "save" customers who are about to churn. Sentiment and keywords that indicate extreme dissatisfaction that can provide an early warning that a customer is looking for churn away from your company, giving agents and supervisors a chance to prevent it from occurring proactively. Analytics software can also access customer records to determine if the customer is high value, in which case a larger incentive might be offered.

On a larger scope, analytics software can provide more visibility to customer trends, topics of interest, or issues, allowing businesses to be more proactive with how they address them. For example, if a lot of people are calling with questions about an upcoming concert series, the organization could send an email to ticket holders that contains clarifying information.

Finally, this isn't a tool that's confined to a physical facility. It also gives managers visibility to remote agent performance, something especially important now that so many agents are working from home. An Aberdeen study revealed that managing remote employees is the most commonly cited challenge with a work from home model. Analytics can bring more transparency to remote agent performance and provide leaders with the confidence that everyone is aligned on supporting customers. This will continue to be a post-pandemic priority as 81% of organizations plan to increase or maintain their current levels of at-home agents.

Use case #2 - Proactively identify targeted training needs

 If you think interaction analytics would also be a great way to identify agent training needs, you're right. And Contact Babel found that 93% of contact center leaders agree with you. When you use analytics to improve agent performance, you increase customer satisfaction and loyalty.

Analytics can help identify both deficiencies and proficiencies in hard and soft skills. Customers expect agents to be technically competent so they can solve issues on the first contact. At the same time, they value an emotional connection with the agent helping them and, ultimately, the brand. Interaction analytics can help make agents better at both aspects of the customer experience.

In terms of identifying training needs, these are all low hanging fruit. Normally, a supervisor or quality assurance analyst would need to listen to a large quantity of call recordings to identify the nature of the training issue that needs to be addressed, but interaction analytics eliminates this need by identifying common themes. Not only does this save staff time, but it can also provide a more accurate analysis. And if a situation requires a more hands on approach, the system can flag contacts that need further review.

For softer skills, interaction analytics can examine keywords as well as sentiment to identify training needs for relationship building, tone, empathy, and more. For example,  empathy is so important right now, contact centers would do well to identify agents who need to brush up on their empathy skills. Customers in need want to be heard and understood by someone who cares - it can turn a routine transaction into a loyalty-building interaction. Analytics tools can identify the presence or absence of words that indicate empathy, such as "I understand" and "I'm sorry that..." Call recordings or digital transcripts that score high on empathy can be used in agent training.

Taking the tone of the call a step further, analytics can also develop sentiment scores for agents based on the attitudes and emotions they display during phone calls. Agents who don't meet sentiment score targets are candidates for additional training.

Use case #3 - Improve customer experience results and consistency

 Customer experience is a differentiator in today's economy. Per Gartner, two-thirds of businesses now mostly compete on CX and that number is expected to grow. This means contact centers need to continuously monitor, enhance, and improve the customer experiences they deliver.

Interaction analytics support this type of continuous improvement cycle. The right tools allow organizations to establish a baseline and then measure sentiment after improvements are made to see if they had the desired effect. For example, a contact center could launch an initiative that changes its scripts to be more empathetic to customer needs. Interaction analytics would allow them to monitor both customer and agent sentiment to track the change over time.

Products and services also play an important role in CX. Obviously, quality is important, but so is addressing an unmet need. Interaction analytics can address these unmet needs a couple of ways. First, they can identify gaps in the product portfolio, which is helpful intel for product development teams. Additionally, analytics tools can inform agents about up sell and cross-sell opportunities. When handled well, introducing customers to products they want or need can enhance the customer experience.

Consistently tracking customer sentiment and using it in conjunction with other measurements like customer satisfaction scores and Net Promoter Scores, will allow organizations to provide proactive customer service, compile a more holistic voice of the customer,  and ensure their CX is meeting expectations.

The right solution

COVID-19 took everyone by surprise. While organizations can't anticipate every disaster, they can proactively plan and be prepared for the unexpected. They owe that to their customers and employees.

Analytics software can help contact centers identify issues before they become crises. This puts them in a position to provide proactive customer service that improves customer satisfaction and loyalty. The best interaction analytics solutions are cloud-based, which makes them flexible and scalable. Additionally, they should be easy to administer - end-users shouldn't need data science degrees to use the software and understand its output.

NiCE CXone Interaction Analytics is the solution our customers turn to help their customers. Cloud-based and intuitive to use, CXone Interaction Analytics identifies root cause, trends, and customer sentiment across 100% of customer interactions.

Find out more about the power of analytics by downloading Contact Babel’s new eBook “Build your Case for a Proactive Contact Center: Leverage Analytics as an Early Warning System.”