Sift Case Studies How an email marketing platform reduced manual review time by over 90%

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	How an email marketing platform reduced manual review time by over 90% Sift

How an email marketing platform reduced manual review time by over 90%

Sift

Technology Category	Analytics & Modeling - Machine Learning Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Functions	Sales & Marketing
Use Cases	Automated Disease Diagnosis Fraud Detection
Services	Data Science Services
Challenge	The email marketing platform was facing a significant challenge due to the susceptibility of the marketing technology industry to fraud attacks. The scale and severity of spam and scams were increasing, putting the onus on sending providers to protect the health of their network. As the company began to scale their business faster than their manual vetting processes would allow, they needed a solution that could keep up. They were looking for a solution that offered uptime, affordability at scale, model customization, data sharing and app integrations, and the ability to automate common support tasks such as account disablement. Read More
About Customer	The customer is a growing email marketing platform that aims to help businesses connect with their valued customers. The platform enables messaging, which is generally trusted by consumers but can be leveraged to send fraudulent messages. As the company began to scale, they found their manual vetting processes insufficient to keep up with the pace of growth. They needed a solution that could prevent fraud attacks from reaching end users and consumers, who could fall victim to fraud unknowingly enabled by the platform. Read More
Solution	The company chose Sift for its positive experience using Sift during a prior working relationship and the ease of integration. The customization of the Sift model was a major factor, as the model learns based on trends specific to the company’s user base and unique fraud signals to more accurately detect abuse. Sift also gives them the ability to observe user-level risk as well as content-level risk to get a clearer picture of fraud on their platform. They began using Sift Content Integrity to identify the full scope of their fraud problem, and to help automatically squash abuse before it starts. The content model implementation makes it simple to integrate data and understand which actions trigger workflows. They’re now able to identify groups of fraudsters and associated accounts to keep fraud rings from compromising their ecosystem. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Application Infrastructure & Middleware - Data Exchange & Integration

Applicable Functions

Sales & Marketing

Use Cases

Automated Disease Diagnosis

Fraud Detection

Services

Data Science Services

Challenge

The email marketing platform was facing a significant challenge due to the susceptibility of the marketing technology industry to fraud attacks. The scale and severity of spam and scams were increasing, putting the onus on sending providers to protect the health of their network. As the company began to scale their business faster than their manual vetting processes would allow, they needed a solution that could keep up. They were looking for a solution that offered uptime, affordability at scale, model customization, data sharing and app integrations, and the ability to automate common support tasks such as account disablement.

About Customer

The customer is a growing email marketing platform that aims to help businesses connect with their valued customers. The platform enables messaging, which is generally trusted by consumers but can be leveraged to send fraudulent messages. As the company began to scale, they found their manual vetting processes insufficient to keep up with the pace of growth. They needed a solution that could prevent fraud attacks from reaching end users and consumers, who could fall victim to fraud unknowingly enabled by the platform.

Solution

The company chose Sift for its positive experience using Sift during a prior working relationship and the ease of integration. The customization of the Sift model was a major factor, as the model learns based on trends specific to the company’s user base and unique fraud signals to more accurately detect abuse. Sift also gives them the ability to observe user-level risk as well as content-level risk to get a clearer picture of fraud on their platform. They began using Sift Content Integrity to identify the full scope of their fraud problem, and to help automatically squash abuse before it starts. The content model implementation makes it simple to integrate data and understand which actions trigger workflows. They’re now able to identify groups of fraudsters and associated accounts to keep fraud rings from compromising their ecosystem.

Impact #1	The company has been able to remove a considerable amount of manual validation of all new customer accounts as a result of Sift’s solution.
Impact #2	By automating common support tasks, such as account disablement, they’ve eliminated thousands of hours of work doing manual account vetting, as well as time spent by customers waiting for their accounts to be validated.
Impact #3	Leveraging Sift has also enabled them to eliminate 200,000 hours of wait time for customers’ flagged accounts to be validated, resulting in a reduction of 20,000 support tickets annually and a superior onboarding experience.

Impact #1

The company has been able to remove a considerable amount of manual validation of all new customer accounts as a result of Sift’s solution.

Impact #2

By automating common support tasks, such as account disablement, they’ve eliminated thousands of hours of work doing manual account vetting, as well as time spent by customers waiting for their accounts to be validated.

Impact #3

Leveraging Sift has also enabled them to eliminate 200,000 hours of wait time for customers’ flagged accounts to be validated, resulting in a reduction of 20,000 support tickets annually and a superior onboarding experience.

Benefit #1	Reduced manual review time by over 90%
Benefit #2	Eliminated 200,000 hours of account verification
Benefit #3	Slashed 20,000 support tickets annually

Benefit #1

Reduced manual review time by over 90%

Benefit #2

Eliminated 200,000 hours of account verification

Benefit #3

Slashed 20,000 support tickets annually

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Overview

How an email marketing platform reduced manual review time by over 90%

Operational Impact

Quantitative Benefit