Tableau > Case Studies > Turning complex mountains of data into actionable insights at amaysim

Turning complex mountains of data into actionable insights at amaysim

Customer Company Size

Large Corporate

Country

Australia

Product

Tableau Desktop
Tableau Server
Amazon Redshift
Alteryx

Tech Stack

Data Visualization
Data Analytics
Cloud Computing

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Productivity Improvements
Cost Savings

Technology Category

Analytics & Modeling - Real Time Analytics
Analytics & Modeling - Big Data Analytics
Infrastructure as a Service (IaaS) - Cloud Computing

Applicable Industries

Telecommunications

Applicable Functions

Business Operation
Sales & Marketing

Use Cases

Real-Time Location System (RTLS)
Predictive Quality Analytics
Predictive Replenishment

Services

Data Science Services
Cloud Planning, Design & Implementation Services

About The Customer

amaysim is a leading Australian online-led Mobile Services Provider (MSP) that has grown from a startup to the fourth largest independent MSP in Australia by number of subscribers. The company has a business model built on innovative technology and has garnered over 700,000 subscribers in less than five years. Such fast growth presented challenges as the organization moved to analyze and obtain insights from all the data it collected. amaysim has over 10 billion call data records, and this number grows by more than 20 million call data records daily. The data it stores is complex and comes from multiple sources including Livechat, Zendesk, call data records, Google Analytics and more.

The Challenge

amaysim, a leading Australian online-led Mobile Services Provider (MSP), faced challenges in analyzing and obtaining insights from the vast amount of data it collected. The company had over 10 billion call data records, with this number growing by more than 20 million call data records daily. The data was complex and came from multiple sources including Livechat, Zendesk, call data records, Google Analytics and more. The previous BI methodology required coding which could not easily scale to business users. Insights could only be sought by one or two individuals within the organization, limiting business gains due to resource constraints and the time-intensive process. The low productivity levels of the current solution prevented the team from fully realizing the value of their data.

The Solution

Adrian Loong, who joined amaysim in 2014, was tasked with developing a BI strategy that suited amaysim and its needs. He sought a solution that could provide senior executives with the ability to make data-driven decisions with real-time intelligence. It also needed to enable other business people in the organization to seek data insights, rather than rely on highly skilled technicians to do all of the analysis. Having used Tableau at two previous organizations, it was easy for Loong to recommend Tableau. With one Tableau Desktop license, Loong did short proof of concepts (POC) with the new tools based on current business pain points. As an example, Loong used technology from Alteryx to combine disparate data sources before using Tableau to visualize the results in a dashboard to management. By continuously delivering results and insights to the management team, it was a straightforward decision for amaysim to adopt the Tableau solution. amaysim undertook an end-to-end replacement of their technology stack and now uses Amazon Redshift as their database, Alteryx to combine the data, and Tableau to visualize it.

Operational Impact

amaysim has seen vast improvements in workplace productivity and is able to make better educated business decisions, faster.
No longer is it a two to three month process to get the answers they’re searching for. Visualising the data allows any user to immediate identify the trends occurring within our business so we can act on it.
amaysim now has a three person analytics team covering a wide span of functions including finance; customer acquisition and retention marketing; plus retail and online sales. It is able to get the data it needs faster; projects that would have taken over two weeks now take a few hours.
amaysim is also empowering its business users to ask their own questions using Tableau’s selfservice data sources which significantly increase workplace productivity.

Quantitative Benefit

Projects that would have taken over two weeks now take a few hours.
Visualising the data allows any user to immediate identify the trends occurring within our business so we can act on it.