Contact Centers are complex places. The omni-channel environment we live in gives customers the freedom to call, email, chat or social media their way into a contact center.
Some customers need help, some want to buy a product and some won’t hang up until they speak to a supervisor.
But they’re all important!
To further compound the complexities mentioned above, COVID-19 has severely impacted contact center operations. Over the last year, it has been reported that there has been a decrease in FTEs by ~50-70%, whilst call volumes have increased anywhere between 300-800% across the same time period.
This “perfect storm” highlights the need for contact centers to become more efficient in dealing with omni-channel customer interactions, ensuring that the cost to serve customers does not become an unsustainable cost for their business.
How to better understand the omnichannel customer experience
Historically, it has been extremely difficult to get a holistic view of how customers are interacting & feeling when they enter the contact center. This is because data from different channels often sits in different systems. And even if your company is able to consolidate the datasets into one platform, there has been no real way to make any sense out of these unstructured data sources that contribute to 90% of your interactions - webchats, emails & phone calls.
The main source of reporting (disposition codes) are generally static in nature and can be quite subjective due to the heavy reliance on agent behavior. Due to lack of better information, task workflows are generally prioritized according to time-based sequential queues or by customers who are screaming the loudest.
But what if there was a solution which could change this?
Enter Medallia’s Contact Center Suite …
Medallia’s Contact Center Suite has the capability to;
Capture signals from disparate data sources; calls, emails, webchats, social media, post-contact surveys
Analyze & synthesize these datasets utilizing an array of machine learning & natural language processing techniques; Speech to Text, Natural Language Processing, Sentiment Analysis & Automated Scoring
Proactively flag issues that are causing the most pain to business outcomes across all methods of customer interaction.
Medallia’s AI now provides the capability to objectively score all unstructured datasets (calls and emails), ensuring that 100% of interactions are objectively measured & considered. The native text analytics platform also provides the capability to apply natural language processing to 100% of unstructured datasets, providing an objective insight into the key themes & topics emerging from omni-channel datasets.
From this point, role-based dashboards and automated workflows democratizes relevant data, ensuring that actionable insights are packaged and distributed to the right people, at the right time, to take action.
From an inner loop perspective, TLs or Closed Loop Feedback (CLF) teams are able to proactively contact “at risk” customers before the situation worsens, reducing the volume of inbound repeat callers.
From an outer loop perspective, CCMs, TLs & Agents are all equipped with information to understand how they’re performing today and what they need to do to improve the customer experience tomorrow.
Improved channel optimization → cheaper cost to serve customers
Proactively addressing “at risk” customers → less customer churn
Role-based dashboards with KPIs & feedback → more engaged employees
Keen to learn more?
Feel free to reach out for a chat today!
Ben the Bearded Man