Fivetran > Case Studies > Super Dispatch Enhances Revenue Impact with Fivetran and Modern Data Stack

Super Dispatch Enhances Revenue Impact with Fivetran and Modern Data Stack

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Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
  • Buildings
  • Construction & Infrastructure
Applicable Functions
  • Logistics & Transportation
  • Sales & Marketing
Use Cases
  • Autonomous Transport Systems
  • Time Sensitive Networking
  • Training
About The Customer
Super Dispatch is a growth-stage startup that provides an online platform for auto transport. It serves as a one-stop-shop for everything carriers and shippers need to move cars faster, smarter, and easier. Backed by cutting-edge technology and best-in-class software, the Super Dispatch platform offers advanced carrier and shipper experiences that save time, money, and resources, enabling customers to focus on moving more cars in less time using fewer resources. The company aims to onboard as many new users and optimize the experiences for active users as fast as possible to gain momentum.
The Challenge
Super Dispatch, an online platform for auto transport, was facing challenges in onboarding new users and optimizing experiences for active users. The company's data was decentralized and scattered across various digital properties, business systems, and marketing tools. Employees were relying on spreadsheets shared around the company for different purposes such as marketing, billing, and sales. The data was downloaded from business systems or Software as a Service (SaaS) platforms individually and analyzed in Excel. This posed a significant challenge for Aman Malhotra, a veteran in the marketing, sales, and operations analysis industry, who was hired to improve user activation, retention, and monetization through the use of data.
The Solution
Aman Malhotra set out to build a new data architecture for Super Dispatch from scratch. She aimed to create a data pipeline that provided a single source of truth, was simple, accessible to users across the company with varying data analytics backgrounds, and stored in a single location. A key component of this new architecture was Fivetran, a data integration service with an extensive library of connectors to SaaS platforms. Fivetran automatically pulled data from Salesforce, MailChimp, Sendgrid, Intercom, Webhooks, and Braintree in near-real time, loading it into an Amazon Redshift data warehouse. The company's business intelligence tool, Tableau, was then used to analyze the data and present it to business users in an easily understandable format with real-time dashboards, charts, graphs, and other visualizations. The insights derived from this data were used to make data-driven decisions and inform ongoing campaigns, optimizing outcomes and driving customer behavior.
Operational Impact
  • The implementation of the new data architecture and the use of Fivetran, Amazon Redshift, and Tableau have significantly improved Super Dispatch's operational efficiency. The insights derived from the data collected by Fivetran have enabled the team to deliver measurable value to every department across the company. A product engagement project provided the product team with a snapshot of how users are interacting with Super Dispatch’s digital assets, enabling them to experiment with A/B testing across promotional emails and push notifications to turn dormant users into active users. Another project focused on user activation, where insights into how 'super users' behave allowed the product team to push other users into taking certain actions that lead to richer engagement. The success of the analytics and growth program has led to an increased demand for actionable data across the company.
Quantitative Benefit
  • A successful product engagement project that increased lift by 6 percent
  • A successful user activation project that improved activation rate by 13 percent
  • Real-time data integration and analysis with Fivetran, Amazon Redshift, and Tableau

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