AI Case Study

H&R Block improves filing acceptance rates by 10% by monitoring the performance of its online tax filing application and user experience using machine learning

H&R Block monitors the performance of its online tax filing application by automating load balancing and monitoring traffic and stack traces. The application also monitors front-end user experience. Any variations in the network is detected and support team is alerted. New Relic platform also supports DevOps by keeping track of changes and generating alerts in case of deviations.

Industry

Professional Services

Consultancy And Business Services

Project Overview

"New Relic's platform performs back-end monitoring to automate activities such as load balancing as well as front-end business performance. By using New Relic to build a dashboard that tracks the software’s NETFILE system, H&R Block Canada was able to see the transaction details in real time...
Using New Relic Mobile they can collect and analyze all kinds of metrics around mobile, including what devices and OS versions its customers are employing, where users are dropping off the application, conversion statistics, and more—and rolling all of these metrics into a single Insights dashboard. "

Reported Results

According to the company they:

* Delivered complete visibility into front and backend performance of online tax filing software
* Improved acceptance rate of returns filed using the software
* Simplified the adoption of DevOps
* Improved its NETFILE acceptance rate by more than 10% within a single week

Technology

Function

Strategy

Analytics

Background

"H&R Block is the world’s largest tax-preparation firm, generating just over $3 billion USD in revenue in FY2017.

In 2014, H&R Block Canada aimed to disrupt the market by launching an online DIY application for tax return preparation and filing process".

Benefits

Data