Automated G2 review and testimonial collection for SaaS

How to build an automated system that invites your happiest customers to leave a testimonial?
6.8%
Conversion from email to testimonial
4.8
stars on average
48
reviews in 2 months

Problem

Getting your happiest customers to give testimonials is difficult and knowing who to ask is even harder.

Solution

It’s a well known fact that regardless of product or service, most people like to research and decide themselves without being influenced by sales reps and marketeers. For this reason you see many businesses put significant effort into collecting reviews and testimonials.

For product businesses this is fairly straightforward, but for SaaS companies where the relationship between software usage and making public claims about the product is far less amicable and emotional. Your users might like your software but they don’t care enough to leave you public testimonials.

To overcome some of these challenges we worked on setting up an automated testimonials collection process for a well known software company. We chose G2.com for collecting the reviews as being successfully rated on the platform can be a significant boost for reputation.

The traditional way of approaching users with email campaigns did not sound appealing and such campaigns often lead to your burning valuable contacts. We wanted to create something that would provide the users with a personal experience and maximized conversion from request to review.

The solution was an automated testimonial collector with these capabilities:

  • Utilize app user data: The system was using real data from the software usage patterns to detect users that have been active for long enough to collect experience.
  • Key events as triggers: We connected multiple key events – like a positive interaction with customer support or sending product feedback – as these could indicate higher activity levels. We used AI to interpret feedback and support tickets to identify users that were communicating about positive experiences.
  • Personalisation: By using actual user statistic we could us AI to write a personal message in the users native language.
  • Human touch: We didn’t send out messages automatically and we generally don’t advocate for using AI bots to message on your behalf. Instead we placed the ready testimonial request emails in the outbox of an actual support agent who would read the message before sending. Sending hundreds of messages took only a few hours of work, but we were able to ensure messages were spot on.

We saw a 6.8% conversion from sent email to a successful testimonial. In just two months this resulted in 50 reviews with an average score of 4.8 out 5 stars, which lifted the company to a category leader in multiple categories on G2.

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