Customer Success Story

A Leading Electricity Generation Company Is Leveraging Stratifyd to Increase Customer Retention

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70-point increase

on employee satisfaction scores

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43% decrease

in contact center calls projected using speech analytics

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100% visibility

into omni-channel customer feedback

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The Challenge

This company, which is a sustainable energy company serving more than half a million homes and businesses in New Zealand, struggled to quickly and easily analyze and aggregate its huge amounts of customer feedback.

The Resolution

The company is focusing on improving the customer experience to increase loyalty. It used prebuilt and custom-made data connectors to analyze social feedback, NPS, interaction notes, and call center recordings to identify unhappy customers with the potential to churn. Our solution’s predictive modeling analyzes historical data to identify the words used in reviews of customers who deflected and determine future churn risk so analysts can look for the same indicators in new data sets.

When these types of customers are identified, the company has call center representatives proactively reach out and address their concerns.


"No matter what the vertical, it’s all about the customer, and their feedback is invaluable."

The Full Story

Customer feedback has helped the company shape the constantly evolving set of products, services, and rewards it provides. The company’s use of data, insights, and digital channels will be crucial for giving customers personalized service and increasing customer engagement.

The company generates and retails green energy – such as hydro, geothermal, wind, and solar – in the country and strives to keep its costs among the lowest in the market. Stratifyd is helping to identify whether certain discounts and fees go over well among customers, keep tabs on competitors, analyze marketing efforts, and maintain a positive image in the community. These efforts to better understand customers will help aid in the company’s goal to decrease contact center calls by 43%.

Our platform isolated the model and class and was able to use the geographical location feature to pinpoint the exact facility in Alabama which was the root of the problem. The company was able to recall just the affected vehicles instead of issuing a mass recall, which saved millions of dollars.



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