Data Orbitz, an intelligent managed cloud service provider with widespread expertise in any cloud-any platform solutions partnered with ITTStar to leverage Machine Learning functionalities into their contact center environment to improvise customer service to their clients.
Being an IT solutions provider, the customer wanted to invest in spearheading innovation and digital transformation by leveraging Machine Learning (ML) functionalities such as transcription, text-to-speech, translation, chatbots, business intelligence, and language comprehension into current contact center environments. In order to help their customers be agile, the customer wanted to implement contact center intelligence to enable self-service, live-call analytics, post-call analytics and agent assist to kick start their journey of transformation..
To help implement this innovation, the customer engaged with ITTStar who built an AI solution using AWS. This solution enabled customers to transcribe, translate and analyze each customer interaction using Amazon Connect. It helped provide customer insights in real time, and helped agents and supervisors better understand and respond to or resolve customer queries, thus improving the overall customer experience.
To solve this business challenge, ITTStar’s goal was to automate the process of capturing the logs from customer calls to the call center and to host the chat on the website. The calls from the clients were converted into text using transcribe and stored in in AWS S3 bucket using AWS Lambda function. In parallel, the logs from the chat were taken from AWS CloudWatch and stored in another S3 bucket. The files from the bucket were fetched by AWS Lambda by creating an event for PUT objects. Inside the AWS Lambda function, the sentiment analysis on the input data is done and along with the contents filtered out from the input, the sentiment of the chat is stored in a csv file. This final output is visualized and presented using AWS QuickSight.
AWS provides a host of innovative ML solutions. Services like Amazon Lex, Comprehend and Transcribe run highly sophisticated algorithms which can be interconnected to make these complicated solutions user friendly for users. Amazon Comprehend analyzes call interactions in real time, detecting the sentiment of the caller, and identifying key words and phrases in the conversation using NLP. Generating actionable insights such as product and service feedback loops, or the best performing interactions such as those ending with a positive sentiment score were all possible with these AWS ML solutions.
To solve this business challenge, ITTStar engaged with the customer on a discovery workshop to understand the pain points, challenges and objectives. After getting an understanding of the requirement, ITTStar devised an ML solution and walked the customer through the entire process of end-to-end implementation. The client envisioned many perks of the solution proposed and availed the partner support for implementing AWS CCI solutions as proposed by ITTStar.