athenahealth operationalizes customer feedback to drive clinical and financial results
Company Size
1,000+
Region
- America
Country
- United States
Product
- Luminoso
Tech Stack
- Natural Language Understanding (NLU)
- Automated Tagging
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Natural Language Processing (NLP)
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Healthcare & Hospitals
- Software
Applicable Functions
- Business Operation
- Quality Assurance
Services
- Software Design & Engineering Services
- System Integration
About The Customer
athenahealth is a prominent provider of network-enabled services for hospital and ambulatory customers across the United States. The company partners with healthcare providers to drive clinical and financial results by leveraging insights from its extensive network of 160,000 providers. The Voice of the Customer (VoC) team at athenahealth plays a crucial role in collecting and analyzing customer feedback to inform decision-making processes. The team focuses on quantifying trends and priorities that impact customer retention, growth, and loyalty. By collaborating with service and product teams, the VoC team advocates for customers and ensures that their needs and concerns are addressed effectively. athenahealth's commitment to operationalizing customer feedback highlights its dedication to improving the overall customer experience and delivering high-quality healthcare services.
The Challenge
athenahealth, a leading provider of network-enabled services for hospital and ambulatory customers, faced the challenge of managing and analyzing large volumes of customer feedback. The Voice of the Customer (VoC) team at athenahealth collects and analyzes feedback from over 160,000 providers, receiving over 6,400 monthly survey responses from various user groups including doctors, nurses, and managers. The datasets were too large to manually review but not large enough for most natural language understanding (NLU) tools. Previous attempts to address this issue included manual reading and summarizing of comments, building in-house tools, using open-source NLU, and conducting two-week 'tagging marathons' each quarter. An effective solution was needed to quickly categorize customer feedback, identify and quantify issues affecting customers, and uncover deeper insights without consuming analyst time on manual work.
The Solution
athenahealth implemented Luminoso to operationalize the tagging and classification of customer survey feedback. By integrating Luminoso with preexisting customer data, the Voice of the Customer (VoC) team was able to uncover the most discussed issues and topics, as well as understand the intent, wants, and needs of users more deeply. This enabled athenahealth to implement fixes, improve functionality, and prioritize product requests more effectively. The automation of tagging through Luminoso allowed the team to chain different types of classification across preexisting and newly-created labels, preserving internal structure and logic while making labels both simple and informative. The process was not only faster and more accurate but also eliminated the need for quarterly tagging marathons. This freed up the VoC team to spend more time analyzing data and improving the customer experience.
Operational Impact
Quantitative Benefit
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