Enjoy a slice of customer data analytics Pi (e)
There is an infinite amount of data in contact centres but what does it really tell us? I believe that educated insights are better than wandering around in the unknown and that taking a lead from Pi is the answer.
International Pi (π) Day is held every year on March 14. Pi is an amazing mathematical constant because it articulates the unique ratio between the circumference of a circle and its diameter. Supercomputers have calculated it to over 60 trillion decimal places but most of us struggle to get beyond 3.14 (hence the date—American style). You may be asking what Pi has to do with customer data analytics in contact centres? Well, please bear with me.
The Power of Pi
As mentioned, Pi is an infinitely long number. Scientists use it to calculate trajectories of spacecraft, design buildings and understand DNA. We do not question the integrity of this analysis or the results derived. So, why don’t we think the same when it comes to analyzing customer data?
For example, there is an ongoing paranoia around transcription accuracy and a distrust of insights if a transcription is not 100% accurate. We seem happy to calculate the area of a circle using the crude 3.14 figure but are not happy to trust a transcript that is 90% accurate. However, in my mind speech analytics engines are accurate enough to give confidence in the results. Yes, the transcript might not be 100% accurate but you can typically understand what is going on in the conversation and should be able to trust the insights that are derived.
Given the potential to leverage customer analytics for tackling unknowns in contact centres and boost agent productivity, customer engagement, and customer loyalty, it is time to worry less about ultimate accuracy and take a bite out of the initially intimidating pi that is contact centre analytics.
Dive into the Unknown
Here are 6 ways to implement customer analytics tools to help contact centres to dive into the unknown:
1. Eliminate Human Bias
Rather than look for needles in the proverbial haystack, focus on blowing away all the straw to see what needles you are left with. This means applying Machine Learning (ML) to call transcripts to automatically find the ‘needles’ or key topics and library of associated phrases that really matter such as those relating to churn risk, compliance or upsell. ML saves time and effort, reducing human input—and error—while saving critical customer data from falling through the cracks.
2. Create Conversational Clarity
The average organisation analyses just 2% of customer interactions. What usually happens is the Quality Assurance (QA) team selects a few interactions a month to evaluate and then they try to make business decisions based on that small amount of data. This means the other 98% of interactions potentially filled with valuable unfiltered and unbiased customer information just sit there on the shelf. The beauty of customer analytics is it analyses 100% of customer interactions, making it easy to fill in the gaps and make the unknown known.
3. Ease Customer Effort
Customers expect their journey to be seamless. If an organisation is too difficult to do business with, customers are likely to look elsewhere for their favourite fashion accessory or latest hi-tech gadget. Implementing customer analytics keeps customers loyal by uncovering the root causes of poor customer experiences. If you can quickly pick up on the warning signs, such as multiple apologies, escalations, or regulator mentions, this allows agents to stay one step ahead. They can proactively call disgruntled customers to nip potential problems in the bud.
4. Reduce Contact Load
Harnessing customer analytics identifies unnecessary and costly repeat or avoidable contacts that might be handled elsewhere in the organisation, be better suited to self-service or are caused by long handle times, high hold times, unnecessary transfers, and silent time. These insights also empower the contact centre to highlight and address high risk interactions more efficiently and, in our experience working with customers, navigating to the precise point in an interaction improves efficiency of quality assurance and compliance by 30-40%.
5. Coach Employees in the Right Direction
When agents have opportunities to learn something new and have a clearly defined career path, their motivation levels increase exponentially. Today’s sophisticated analytics are designed to deliver a personalised and meaningful view of staff performance wherever your teams are. Dashboards powered by analytics give agents all the visibility they need to create their own self-assessments and personal development plans. Remember, what goes on behind the scenes is just as important as what happens on the frontline. Use desktop and speech/text analytics to identify and improve systems that are slow or poorly designed.
6. Build Business Intelligence
Let your data drive value across the business by using real-time information for data management. Employ in-the-moment data insights and share them with the rest of the organisation to drive greater certainty, trends, better action planning and decision-making across the wider organisation. For example, powerful CX insights from within the contact centre can help the marketing team understand brand awareness, competitor influence and the overall effectiveness of their campaigns. Sales can quickly identify new opportunities for renewals, referrals, and cross-sells while the finance department benefits from insights into billing issues, refunds, and credits.
Are You Ready to Step into the Known?
Customers have long memories, and their expectations are constantly rising. What better time to unearth what they really think and the service you are really delivering? Customer data analytics can sift through the piles of customer data your contact centre collects to help make the unknown known. Just look at what these three customers achieved with the benefits of data analytics! For more ideas, read Jim’s longer blog or stay connected with all things CX by visiting The CX Lab.
Jim Davies served as Vice President of research at Gartner for over 20 years. During his tenure, he advised thousands of organisations across the globe on how to best adopt CX, WFO, and WEM strategies and technologies. He was especially well-known for helping brands initiate successful VoC programmes, both to collect the right data and build...
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