![]() ![]() Then they score each new user and put them into tiers that indicate how likely they are to become successful customers. MadKudu first evaluates CloudApp’s successful customers and then looks for look-a-likes among new users, based on in-app behavior and Clearbit firmographic data like job title, company industry, and company size. MadKudu, a machine learning tool, scores CloudApp’s new users automatically. Scott set up a way to qualify users and route them into different onboarding experiences with different amounts of sales and support attention. But to keep the team lean and effective, they should really be talking only to qualified leads, such as people who could get their team at work into a CloudApp team plan. Talk to them about the features they’d get with the paid version.ĬloudApp has a sales team that can talk to leads about whether upgrading is right for them.Help them use the tool and discover free features.So the overarching onboarding flow passes through three phases: The more active they are, the more likely they are to upgrade to the paid product. The first call to action is “Download the app”:Īfter a user installs the CloudApp desktop app, CloudApp helps them discover features and use the product. Here’s an example of an early message in the series. Customer.io then triggers the email series, stopping it when a user installs. CloudApp’s app data lives in Segment, which tells Customer.io which users have not yet installed the desktop version. So they use a series of emails-five, to be exact-to push people to install. That’s the basis of their product, and without the desktop app, people can’t truly use the product. The first and only thing Scott and the CloudApp team care about for new users is that they download their desktop app. Getting users past the first onboarding milestone All this contributes to faster onboarding with fewer complications for the sales team. “We’re seeing growth in our email replies from people who feel the outreach is real, not automated,” says Scott. ![]() But far from feeling robotic, the emails are so well personalized that they continue to get warm responses. Through the process, Scott added layers of complexity, from machine learning to Clearbit data, all over the course of 13 months. He talked to marketer friends, read blog posts, and listened to users who responded to his onboarding emails to improve each one. This helps them automate part of the sales process for users that only need a self-service product, which reduces overhead while scaling their small team of two people (they act more like a team of 10). Considering that his version-one onboarding emails basically all just said, “here are three things to do, let me know if you want a demo,” his emails have come a long way.ĬloudApp’s onboarding emails now have layers of data manipulation in order to prioritize and personalize each outreach. When Scott Smith, CloudApp’s VP of Sales and all-around good guy, first turned his focus to his user onboarding emails, he had no real direction to follow. It was originally published in the Customer Onboarding chapter of Clearbit’s Data-Driven Marketing ebook. ![]() This blog post will dive into how one such organization, CloudApp, crafted a data-driven and personal onboarding email series that hit all the right notes and made a difference on the bottom line. Emails help welcome new users, get them back into the product during periods of low engagement, and convert them into customers.Ī well-orchestrated email campaign is especially important for products that want to achieve high free trial-to-paid conversion rates and maintain a lean sales organization. While the most crucial parts of the new user experience occur in the product, email is still a valuable channel for onboarding. ![]()
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