Analyzing Unstructured Data to Improve Program & Customer Experience
Solix Case Study
Situation
One of the largest U.S. telecoms needed to determine what steps it could take in order to improve its approval percentage for individuals who would qualify for its discounted broadband services. The primary goals were to increase enrollment and the percentage of applicants that were approved during their initial attempt in order to lower re-applications. Understanding the application processes and frequent causes of errors or missing data that results in application denials, Solix leveraged its business intelligence and prescriptive analytics capabilities to analyze raw data and make informed fact based operational suggestions for the customer to improve results.
Objectives
- Increase applicant approval rate.
- Reduce subsequent correctable denial outbound applications.
- Identify circumstances or steps in process that lead to denials and remove if possible.
Challenges
- Maintain integrity of program qualification/eligibility requirements.
- Achieve concurrence of client legal team on operational or customer experience changes.
Solution
- Captured historical customer information to perform descriptive analysis.
- Mined data to pinpoint source of denials and applicant steps that led to denial.
- Revised application fax submission process accounting for the majority of denials (50%).
- Updated external website content removing fax reference as a source of submission.
- Revised and removed contact center scripting promoting fax as a method of application submission.
- Simplified external website and application language regarding program eligibility requirements.
Results
- Increased applicant first approval rate to 85% (a 10% increase).
- Reduced outbound/inbound fulfillment & imaging costs related to correctable denial applications by 10%.
- Reduced inbound applicant/customer contact center traffic related to denials.
- Delivered self-service executive reporting dashboard to client decision makers providing data on demand with key performance indicators and visualizations as it relates to applicant/customer lifecycle.
- Established timely programmatic data text mining processes to gain customer activity insight and identify trends. This promotes fact-based decision making which allows for both future systematic and operational efficiency improvements.