Tag Archives: customer interaction analytics

Stop Poor CX! A New Way of Analyzing Operational Issues on PureEngage

It’s common for issues to pop up during day-to-day contact center operations and with a lot of customer interaction and agent activity within your PureEngage platform, many of those issues may be hard to find.

Contact centers continuously monitor metrics to:

  • Analyze data that affects customer experience (CX)
  • Ensure that performance goals are met
  • Catch issues

The tools they use often only show summarized data and don’t help much when the “devil is in the details”. When issues fall within what those tools look for and capture, they are easy to spot and solving them is usually straightforward. For example, if the call volume is unexpectedly high, the contact center will make more agent time available (e.g. bringing on more agents or canceling off-queue time).

However, for issues lurking beneath the surface, evidence may show up in the CX metrics, but standard tools don’t offer an easy way to pinpoint the detailed contact center activities behind the issue. Worse still, is that there are likely activities causing issues that companies don’t even know about.

For example, there could be agent behavioral issues occurring, such as this issue (happened to one of our clients), where some agents were placing customers on hold immediately after greeting them and increasing customer frustration. While this issue was caught by accident (by the VP of Customer Service’s office assistant!), the contact center didn’t have the tools to know who was doing this, how long it had been happening, nor how widespread this hidden issue was.

These more complex issues take time to identify and figure out, causing a lot of time to pass before a resolution is found and put in place. For contact center directors and customer experience executives, this means that their key customer experience metrics (like NPS and CSAT) are affected.

Wouldn’t it be great if contact centers could find those hidden and complex issues much faster, and reduce the impact on customer experience? This is possible but requires contact centers to shift from traditional methods.

Making do with traditional methods and tools

Contact centers use many tools to measure customer experience and identify customer experience problems when they arise. They look at contact center operational metrics (often aggregated data), analyze conversations, or pick up issues directly reported by customers and agents.

Reports, analytics (such as customer journey analytics), WFM, and QA, are tools that contact center professionals use to see how customer experience is impacted (such as higher call volumes, or agents adhering to their schedules), but these tools barely offer a glimpse into those harder to find day-to-day operational problems.

Basically, contact centers are “making do” with the tools they have.

New methods and technology to detect poor customer experience in real-time

To understand those hard to find or unknown issues affecting CX, without spending tons of time sifting through low-level system details, contact centers need to adopt a new way and new technology.

There are new and emerging ways to more quickly, accurately and proactively examine the contact center activity for issues and problematic agent behavior that can affect the customer experience. These methods and technology also help monitor these issues to keep them at bay.

For example, Aria’s Visualizer for Genesys that works on PureEngage helps contact centers:

  • Identify agent behavior and compliance automatically by listening to ALL calls instead of just spot checking a small sample of calls.
  • Analyze calls by learning and improving what is defined as a problem call.
  • See detailed analysis in real-time that captures all the low-level activity in a contact center. This will provide a visual picture of the customer experience, making it easier to spot issues you didn’t even know you had and that are beyond the reach of listening to calls.

Contact centers now have options for resolving issues that happen in day-to-day operations and can reduce the effect on customer experience. Visualizer provides the detailed insights that find the issues quickly so they can be actioned immediately, and affect a smaller number of customers.

 

Top 3 Reasons Why You Need Customer Interaction Analytics

Businesses are losing $62 billion per year through poor customer service (Serial switchers strikes again, NewVoiceMedia, Jan. 2016). This means the new goal must be getting every interaction right.

Forrester Research predicts that by 2020, insights-driven businesses, like Baidu and Netflix will quadruple their revenue from $333 billion to $1.2 trillion, growing eight times faster than global GDP (Top Five Imperatives To Win In The Age Of The Customer, May 23, 2017).

Customer-centric companies like these are a real threat to a lot of businesses who choose to prioritize areas like manufacturing and distribution, instead of better understanding their customer needs and wants and delivering personalized experiences.

To deliver such experiences, you need insights; but to get insights, you need to start using all your data the right way. Once you get to a phase when you no longer have data silos across business systems, it is important to start looking for a good operational, employee, and customer interaction analytics application. And here are the top three reasons why:

1. Customer retention

No one would argue that customer retention is critical for survival. Your brand and company Net Promoter Score (NPS) is constantly being reevaluated with every interaction handled and socially-shared commentary by your customer base.

Back in the day, a negative customer experience would simply make interesting conversation over coffee. But with the advent of social media, customers that are not able to resolve issues, can blast their complaints to a global audience that will hear about any shortcomings your business may have.

A lot of companies out there focus more on customer acquisition than on customer retention. But did you know that it costs five times as much to attract a new customer than to keep the existing one, and if you only increased your customer retention rates by 5% your profits could increase by 25% to 90% (Customer Acquisition Vs. Retention Costs, Invesp, Dec. 2015).

The best way to increase your customer retention rate is to improve customer experience.

2. Agent behaviors

Your front-line agents are also a crucial element to your customer experience. By gaining visibility into your agent interactions you can make better decisions.

But do you really know what is going on? Are you able to easily see the whole picture when it comes to your agent performance?

Traditionally, agent behavior analysis has been based on a set of standardized aggregated metrics that were supposed to summarize good agent performance. But to provide good customer service, aggregated metrics just don’t cut it and so you need to look at customer interaction analytics.

Granularity and automation are needed to look for negative behavioral patterns (placing customers immediately on hold, flashing Not Ready while Ready, etc.) in your agent performance and flag them immediately.

The ROI in this case can be simple. As an example, let’s assume a fully loaded agent cost of $65K. That translates to $280/day/agent. If we manage to identify 15 mins of lost time for every agent day and assume a 300-agent contact center. It translates to $2700/day which over the course of 220 work days in a year is just under $600K!

And that is not even considering the impact a negative behavior may have on the customer experience or revenue opportunities.

3. The “hidden” costs of support

Most firms are swimming in data, but they’re only using about a third of it. Worse, only 29% say they are good at translating the result of data and analytics into measurable business outcomes (Top Five Imperatives To Win In The Age Of The Customer, May 23, 2017).

As a matter of fact, the top two challenges preventing organizations from making use of analytics are “ensuring data quality from a variety of sources” and “accessing data from a variety of sources” (Pick A Powerful Pilot To Propagate Customer Analytics, July 19, 2017).

Speed of issue resolution carries a significant impact. The quicker issues can be resolved, the less chance there would be of repeating poor customer experiences, thus minimizing the impacts to your brand. Outages that critically impact service delivery are a ticking money bomb. Financial impacts increase exponentially the longer you are unable to service customers. One of the largest banks in Canada implemented Aria’s Visualizer (business and support analytics) and improved support response times by 75%. Such customer interaction analytics applications cannot be underestimated.

Systems that deliver customer interaction analytics in an efficient and accessible manner empower lower tiered or less senior support staff to extract necessary system information required for issue resolution. This can help focus the energy of senior technical staff on critical and future facing initiatives.

Business analytics resources can also leverage data on agent and system behaviors to make better operating decisions.

Lack of proper visibility into these three areas: customer experience and retention, employee behavior, and support issues – translates into a significant financial impact. Analytics applications like Aria’s Visualizer allow for an improved unified approach to visualizing interactions level data, strategic support approach and behavioral performance analysis which can help you provide top rated customer service.

To sign up for a demo of Aria’s Visualizer visit the Genesys AppFoundry or the Aria’s Visualizer product page.