How Can Contact Analytics Help Improve a Poor Customer Experience? [Use Case]

In today’s multichannel digital world, customers want options for how they get in touch with companies. With consumer expectations steadily rising, many companies are adopting omnichannel communications strategies, which allow them to develop a 360 degree view of the customer, consider messaging from the customer viewpoint, and capture customer communications across channels.

But what happens when a company fails to provide a positive customer experience? What can the company do to retain and satisfy customers – and make them more likely to want to recommend the company to family or friends?

The following use case from one of CallMiner’s senior executives outlines the importance of using contact analytics to help improve the customer experience.

I recently booked a hotel room for an upcoming presentation on utilizing contact analytics in the call center. Ironically, my poor experience interacting with the hotel reinforced many of my presentation points.

Following the email link provided by the conference organizers, I entered my arrival and departure dates in the online form. While the calendar showed rooms available, the system returned an error that none were available on these dates. There were no help links available from this page so I returned to the invitation email and dialed the telephone number provided.

After stating my business to an automated reservations system (which asked me to provide the same basic data I had entered online, a process that took 10 minutes), the auto-attendant placed me on hold to speak with a live agent. The live agent and I then spent another 5-6 minutes on the phone, the end result being that she reported that the hotel only had one room available and it was for a different date than I needed.

So after 20 minutes using three different communication channels, I still had no resolution to a simple hotel booking. As an alternative to my initial approach, I went to an online booking website that I often use. The first result on the list was the hotel I had been trying to book! There were five different room types available, multiple rate options, and a 10% discount for having used their site previously. In less than 90 seconds, I had a room reserved.

The bigger challenge came the next day, when I discovered that the conference coordinator had already booked a reservation for me at the same hotel. Because my booking from the previous day had a 100% cancellation fee, I had no choice but to call the hotel again to consolidate the double booking and avoid the fee.

Again, my first point of contact was an automated system, which did not understand my request and began to go into an inquiry loop repeating “How can I help you with this reservation?” After saying the magic word – “agent” – I was transferred to the live agent queue, where I waited for 3 minutes on hold only to then be disconnected.

Two agents (and more than 15 minutes) later, I found myself in queue for a third time, where I waited for 13 minutes in near-silence (I had to check my phone’s screen every minute or so to ensure I hadn’t been disconnected again).

Finally, an employee answered and I re-explained the purpose of my call. Instead of providing me with a recommendation on what to do, the employee instead restated the situation to me, confirmed my email address and telephone number, and stated that she’d send a note to another department to look into the matter and decide whether to issue a refund.

The end result of all of this? A partial reservation (it’s unclear if I’m paying for two rooms), wasted personal time, and a pretty sour feeling about the entire experience.

Oh, and I am still waiting for an email confirming the charge has been reversed.

Would the Hotel Know That I Am a Potentially Dissatisfied Customer Using Current Tools Available to the Call Center?

The typical tools used by service companies cannot analyze, highlight, or escalate dissatisfaction unless the transaction has already been flagged for review. While there is a remote chance that my voice conversation may have been recorded – and an even more remote chance that someone listened to it – there was nothing within the call that would indicate I felt dissatisfied with the process or service.

I did not use escalation language and maintained a relatively even tone throughout all of the conversations (non-agitated, non-aggressive). I will not receive a survey of any kind for this interaction as I did not provide any contact information directly with the hotel’s reservation systems. Unless I proactively contact the hotel with a complaint, there will be no analysis of the various business process failures.

How Could Contact Analytics Have Helped Here?

Contact analytics solves several of the challenges in finding useful and actionable insight from interactions such as this one.

  1. Multichannel: One of the most useful benefits of an automated contact analytics platform is the ability to see linked interactions, which create a complete picture of the customer experience journey. When focused only on a subset of live calls, a manager or supervisor cannot analyze from the point of connect, through the IVR and automated attendant, each voice transfer nor any text-based interactions (such as chat or SMS).
  2. Sample Error: Monitoring three calls, per agent, per month misses too much. Quality Analysts and team leaders are also notorious for “cherry picking” only short calls from the least complex call queues. Amplifying this problem is the fact that not all business units, teams, or personnel are monitored (TLs and specialty care for example). A properly deployed contact analytics platform objectively captures and analyzes 100% of voice and non-voice conversations, eliminating any chance that the output has been filtered.
  3. Contextually Relevant: Word or phrase-spotting could provide some usefulness to the call center manager, but it requires a level of pre-work and manual data manipulation to deliver useful and actionable insight. Allowing the technology to highlight relationships between words, categories, acoustic information and other metadata elements (such as AHT, employee organization, sales performance, CSAT surveys, transfers, CRM data, etc.) creates context. There is no insight without context.
  4. Process and Procedure Compliance: Having context also creates analysis opportunities on employee – and customer – compliance with legal or company requirements. Automating compliance monitoring with contact analytics increases accuracy, reduces risk, and delivers substantial cost savings.
  5. Trend Analysis: Contact analytics can highlight customer dissatisfaction and system issue trends by mining variations of customer questions such as “Why does the online system show availability but I can’t reserve a room online?” and “How many customers are being transferred incorrectly when trying to cancel a reservation?”
  6. First Transaction Resolution: Contact analytics can automatically highlight the frequency of similar bottlenecks, unnecessary transfers, and repeat calls. By understanding which customer types, employee workgroups, IVR exit nodes, websites, company policies, work procedures, etc. are creating unnecessary volume, the call center manager can focus on improvement opportunities.

Final Thoughts

The example above represents a customer experience that could have been significantly improved with the use of contact analytics. In what ways has your organization used speech analytics technology to monitor agent to customer interactions, deliver feedback to improve agent performance, provide customer support across channels, and ultimately improve the customer experience?


Image Credit: © Popov