Sisense Case Studies Job Agency Moves to Real Time Insights

Edit This Case Study Record

	Job Agency Moves to Real Time Insights Sisense

Job Agency Moves to Real Time Insights

Sisense

Technology Category	Analytics & Modeling - Predictive Analytics Analytics & Modeling - Real Time Analytics Application Infrastructure & Middleware - Data Visualization
Applicable Industries	Professional Service Software
Applicable Functions	Business Operation Sales & Marketing
Use Cases	Real-Time Location System (RTLS)
Services	System Integration Software Design & Engineering Services
Challenge	Bold collects a huge volume of data, currently 60TB, and actively analyzes 2TB. They provide subscription-based services, including resume builders, cover letter builders, interview prep, job postings, and worker postings. Each subscription has different frequencies and levels that need to be tracked. They wanted to see which subscription types were getting renewed the most, which products were being purchased the most, and the most effective model for connecting employees to employers. Their existing tool for visualizing transactional data was not meeting their needs. Balaji Jayapal, Head of BI and Big Data, sought a better way to manage their 2TB of transactional data and visualize it effectively. Read More
About Customer	Bold is a company transforming the career industry through the creative use of technology. They work with job seekers and recruiters to connect the best people and companies. They provide subscription-based services, including resume builders, cover letter builders, interview prep, job postings, and worker postings. Bold collects a huge volume of data, currently 60TB, and actively analyzes 2TB. The company aims to fine-tune their builder tools for maximum efficiency by understanding which subscription types are getting renewed the most, which products are being purchased the most, and the most effective model for connecting employees to employers. Read More
Solution	Balaji Jayapal conducted an extensive search for a new tool, testing several on live marketing data and showing them to various departments to get buy-in. Sisense was chosen for its superior visualizations and ease of use. Sisense was implemented in several creative ways, including system monitoring for variances outside of standard deviation and reducing the number of credit card chargebacks. The Platform team used Sisense to analyze credit card chargeback ratios, identifying the most problematic cards and prompting users to use a new card or bail out of the purchase. This process significantly reduced chargeback rates. Sisense was also used to create 20 Elasticubes and 50 dashboards across various data types, including transaction, business, ecommerce, and marketing data. The ETL tool with Sisense enabled hourly analyses of transactions, applying standard deviation to compare to the prior six months and sending alerts for any significant variances. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Analytics & Modeling - Real Time Analytics

Application Infrastructure & Middleware - Data Visualization

Applicable Industries

Professional Service

Software

Applicable Functions

Business Operation

Sales & Marketing

Use Cases

Real-Time Location System (RTLS)

Services

System Integration

Software Design & Engineering Services

Challenge

Bold collects a huge volume of data, currently 60TB, and actively analyzes 2TB. They provide subscription-based services, including resume builders, cover letter builders, interview prep, job postings, and worker postings. Each subscription has different frequencies and levels that need to be tracked. They wanted to see which subscription types were getting renewed the most, which products were being purchased the most, and the most effective model for connecting employees to employers. Their existing tool for visualizing transactional data was not meeting their needs. Balaji Jayapal, Head of BI and Big Data, sought a better way to manage their 2TB of transactional data and visualize it effectively.

About Customer

Bold is a company transforming the career industry through the creative use of technology. They work with job seekers and recruiters to connect the best people and companies. They provide subscription-based services, including resume builders, cover letter builders, interview prep, job postings, and worker postings. Bold collects a huge volume of data, currently 60TB, and actively analyzes 2TB. The company aims to fine-tune their builder tools for maximum efficiency by understanding which subscription types are getting renewed the most, which products are being purchased the most, and the most effective model for connecting employees to employers.

Solution

Balaji Jayapal conducted an extensive search for a new tool, testing several on live marketing data and showing them to various departments to get buy-in. Sisense was chosen for its superior visualizations and ease of use. Sisense was implemented in several creative ways, including system monitoring for variances outside of standard deviation and reducing the number of credit card chargebacks. The Platform team used Sisense to analyze credit card chargeback ratios, identifying the most problematic cards and prompting users to use a new card or bail out of the purchase. This process significantly reduced chargeback rates. Sisense was also used to create 20 Elasticubes and 50 dashboards across various data types, including transaction, business, ecommerce, and marketing data. The ETL tool with Sisense enabled hourly analyses of transactions, applying standard deviation to compare to the prior six months and sending alerts for any significant variances.

Impact #1	Sisense enabled Bold to monitor system variances outside of standard deviation, reducing the number of credit card chargebacks.
Impact #2	The Platform team used Sisense to analyze credit card chargeback ratios, identifying problematic cards and prompting users to use a new card or bail out of the purchase.
Impact #3	Sisense was used to create 20 Elasticubes and 50 dashboards across various data types, including transaction, business, ecommerce, and marketing data.

Impact #1

Sisense enabled Bold to monitor system variances outside of standard deviation, reducing the number of credit card chargebacks.

Impact #2

The Platform team used Sisense to analyze credit card chargeback ratios, identifying problematic cards and prompting users to use a new card or bail out of the purchase.

Impact #3

Sisense was used to create 20 Elasticubes and 50 dashboards across various data types, including transaction, business, ecommerce, and marketing data.

Benefit #1	Each prevented chargeback is worth about $30 to the company.
Benefit #2	Bold has been able to drop the chargeback rate dramatically with the new process.

Benefit #1

Each prevented chargeback is worth about $30 to the company.

Benefit #2

Bold has been able to drop the chargeback rate dramatically with the new process.

Download PDF Version

Overview

Job Agency Moves to Real Time Insights

Operational Impact

Quantitative Benefit