Using Automation to Improve Data Integrity and Reduce Costs
The Data Accuracy Challenge
Under the best conditions, quality review for tens of thousands of calls, emails, white mails, chats, texts and social media engagements each month is time-consuming and costly.
In order to help streamline and augment our manual agent-driven process, C3i Solutions designed and piloted a cloud-based data analytics solution to automate the timely quality-check process. The goals were clear: improve the accuracy of CRM coding — regardless of channel — and do so at a reduced cost. We knew we needed an intelligent solution that could effectively scale, without losing data integrity.
Using Automation to Improve Data Integrity
Using advanced language models, our newly developed, cloud-based Data Analytics tool automates quality review by “listening” to what the consumers are saying and transcribing it right into the proper CRM fields. This brings structure to unstructured data – a company first that’s driving an almost real-time comparison to the CRM record created by the contact center agent.
Did it Work?
Not only did the solution improve accuracy, it also identified scoring inconsistencies and gaps in contact center training. Immediately we saw a time savings and accuracy improvement over our legacy manual sampling and scoring processes. Quality review that had taken 80 hours a week was being competed in just 20 hours! This 75% improvement has a direct impact on the bottom line, with a cost savings estimated at $90,000 annually.
That part was expected, though. What we didn’t expect was the solutions’ added bonus: the ability to transcribe unstructured text started to bring to light consumer sentiments previously hidden from view by the sheer “noise” in the CRM. And it was getting “smarter” over time! The more data consumed the more accurate and efficient it became.
The results are clear. Automation greatly improved our data integrity, has a direct impact on clients’ bottom line and surfaces insights within data that would otherwise go unnoticed.
Tags: AI, analytics, automation, data