Case Study

How Rev automated thousands of qualifying questions and reduced live chat cost by 90%

About Rev

Rev’s software enables freelancers to seamlessly transcribe, caption, subtitle, and translate content in one simple interface. With years of accurate transcription data, Rev’s industry-leading speech recognition engine transcribes speech to text in minutes. Rev’s professional freelancers, advanced software, and proprietary artificial intelligence allows them to offer exceptional accuracy and the fastest turnaround at the lowest prices.

Website Characteristics

  • 2+ million monthly visitors
  • Preference for self serve customer experience
  • Hundreds of pages in the form of landing pages, blog posts, and help articles
  • No site search

Scaling self-serve business with a large user base

The Who

Barron Caster is the Director of Growth at Rev, where he is responsible for the self-serve product lines. An essential aspect of his work is to ensure that customers can efficiently and effectively purchase Rev’s services. He’s also tasked with making sure that the thousands of  freelancers (which Rev contracts for translation and transcription work) that visit the Rev site each month are able to easily access what they need to begin a business relationship with Rev.

The Problem

With such high volumes of active, curious, and engaged website visitors, there was a need to provide real-time answers to their questions. However, the costs of managing a live chat team capable of handling 2 million monthly site visitors would be astronomical and difficult to scale.

What’s more, content and SEO had also become an integral part of Barron’s responsibilities, and a vital aspect of Rev’s low-touch lead generation model. Rev’s blog is the leading content hub for all things video captions and transcription, which brings thousands of leads to the website every day.

So a fundamental problem emerged: how could Rev capture leads, provide a good customer experience, and improve SEO without breaking the bank?

The Solution

Rev implemented the Frase Answer Assistant, which began capitalizing on strong website content to answer 80% of site visitor questions instantly. What’s more, the tool provided valuable insight into the types of questions that Rev didn’t have content capable of answering, and helped them build a comprehensive plan around creating content that could fill those gaps. As a result, their Frase Answer Assistant gets more powerful, their content becomes more comprehensive, and their customer experience becomes more seamless every day.

"We replaced live chat with Frase to automatically answer thousands of visitor questions every month. Frase eliminates live chat costs without compromising the customer experience. In the backend, Frase helps us create content that effectively addresses our customers’ problems."

Why Frase?

Breaking away from live chat

While live chat provides a meaningful connection with your visitors, Rev was looking for a more scalable solution without sacrificing user experience.

Focus on understanding visitor needs

Instead of attempting to manage live chat, Rev wanted to deeply understand what their visitors needed, so they could optimize their website content accordingly.

Maximize content ROI

Instead of content playing a passive role in the back of the website, Rev wanted to use it to deliver answers to their visitors.

Effective content creation

By understanding user intent, Rev can effectively create new Answer Content that meets expectations.


Every month, Frase:

  • Automatically answers an average of 2,000 questions
  • Provides correct or related answers to +80% of the questions
  • Cuts down costs associated with maintaining live chat by 90%
  • Identifies dozens of topic gaps that help marketers create new content
  • Completes 100+ answer funnels that generate new successful pageviews

All in all, Frase is helping Rev make its self-serve business more scalable by automatically answering their visitor questions. In the back end, marketers reap the benefits with insightful user intent data.

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