BPM

Thousands of accurately annotated customer emails serve as training data to develop ML algorithms to analyze customer sentiment in real time.

Thousands of accurately annotated customer emails serve as training data to develop ML algorithms to analyze customer sentiment in real time. Banner

Client Profile.

The company is a technology-enabled service provider, operating in the Digital Solutions, Engineering and Business Process Management space. It services a global clientele across the US, Europe and Australia, ranging from SMBs to Fortune 500 companies.

Business Need.

The company was looking to build a machine learning algorithm to analyze and leverage customer sentiments in near real time (every 12 hours) based on customer emails. The insights generated would be harnessed to preempt problems in customer journey and enhance customer experience.

As a first step, it was important to feed the model with training data and this task involved:

  • Capturing tens of thousands of customer emails from email inboxes, integrating and structuring the data
  • Manually tagging/annotating/labeling each email against a pre-defined sentiment

The follow-up step required validation of model performance against manually annotated data.

The client approached HitechDigital to label the emails against multiple categories and sub-categories, defining customer sentiment. The annotated data was to be used by the machine learning algorithm being developed to analyze customer sentiment.

Challenges.

Solution.

The HitechDigital data annotators delivered tens of thousands of accurately decoded, labelled and annotated customer email records in a standardized database. The emails were annotated against predefined customer sentiment categories. The annotated data proved to be a perfect training baseline to feed the customer sentiment analysis ML algorithms.

Approach.

Quality Check:

Technology and Software Used:

Business Impact.

Accurately annotated data provided deeper understanding of customer sentiment for real-time and informed actions
Drove tailored strategies based on customer responses
Accuracy of annotated data improved performance of NLP algorithms
Offshore delivery model offered cost advantage and increased operational efficiency
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