« View all customer stories


Recommend articles and email content based on customers’ recent behavior and likelihood to respond to certain topics

Atlassian — a leader in enterprise collaboration software including Jira, Confluence, and Trello— serves more than 60,000 customers globally, including 85 of the Fortune 100. To continue to fuel user growth and retention, the software-as-a-service (SaaS) company wanted to increase engagement through in-product messaging, deliver personalized and educational email campaigns, and identify strategic upsell and cross-sell opportunities. That's where a partnership with Lytics came into play.

To execute on their personalized marketing and growth initiatives, Atlassian turned to Lytics to help them integrate disparate customer engagement data sources, create audience segments based on customers attributes, and integrate with Atlassian’s systems and third-party tools as those user profiles or audience segments change.

Personalized in-app messaging increases user engagement

User experience is key to creating loyal SaaS customers. Atlassian, like other software companies, was under-informed as to which app features their customers were using and at what point they may become disengaged along the way, creating higher abandonment rates and fewer upsell opportunities. Atlassian turned to Lytics to track user engagement so that they could:

• Present personalized in-app “help” messages based on what each customer has experienced in the app up to that point.

• Integrate seamlessly with helpdesk articles and recommend relevant articles for each visitor, both in the app, and via follow up email messages.

• Increase engagement with feature notifications as well as advanced app tips and workarounds.

Personalized content in email messaging increases open and CLR

Gaining mindshare can be a challenge when your customers and prospects receive hundreds of emails per day. Atlassian looked to Lytics to integrate with their email service provider (Sendgrid) to create one-to-one personalized messages that delivered the right content for that person at the right time. With this strategy, they were able to:

• Reduce email fatigue: Atlassian uses Lytics’ data science-based customer scoring to determine with what frequency they should trigger emails to customers. Users showing less interest received fewer messages while users displaying more interest received additional relevant emails.

• Personalize email content: The Lytics Content Affinity Engine allowed Atlassian to display certain articles and email content based on customers’ recent behavior as well as their likelihood to respond to certain topics.

• Increase open and click rates: With more relevant email content, Atlassian can now rise above the clutter and actually drive increased email engagement from their subscribers.

Suggest in-app educational content to increase user success and reduce support resources

Atlassian’s feature rich apps are great for power users but can leave some new users feeling overwhelmed. Atlassian turned to Lytics to help them increase user adoption on an individual level:

• Progressively show/hide features: Using Lytics predictive scores and persistent user behavior profiling, Atlassian can deliver a user experience that adapts to the individual, displaying features based on their momentum and app interactions.

• Suggest relevant educational content: Lytics stores content affinity for every user and keeps track of what help desk and blog articles they have read. This allows Atlassian to fine tune what articles they recommended for each app visitor.

• Reduce help desk tickets: Investing in more personalized in-app experiences will continue to pay off for Atlassian as they are able to conserve help-desk resources and reduce customer abandonment.

Use data science to predict who will buy and increase revenue

Atlassian has various SKUs and getting someone to try a free or low-cost tool is just the beginning of the lifetime value of that customer. Atlassian worked with Lytics to leverage data science to sell the right products to the right customers at the right time.

• Predictive insights: Using Lytics segments and machine learning, Atlassian can now identify which users are most likely to enter target segments (e.g., “Likely to Buy”)

• Identify common attributes: With Lytics, Atlassian can see the shared criteria that contribute the most to converted opportunities. Attributes such as: time in app, key features used, knowledge base articles read, and other factors can all be measured for how much they influence behavior.

• Increase revenue: Lytics machine learning algorithms let Atlassian identify potential high-value customers, focus marketing efforts and ultimately increase sales.

“With Lytics, we were able to quickly get up and running with increasing ROI, testing new in-app experiences and personalized messaging programs within a few weeks.”

Fast ROI that scales across multiple product portfolios

With Lytics, Atlassian was able to quickly get up and running with increasing ROI, testing new in-app experiences and personalized messaging programs within a few weeks. With up to 5,000 user events per second, Atlassian found in Lytics a partner with the right technical architecture, APIs, and expertise to get to market quickly and at scale.

Explore data-driven marketing with us

Sign up for Lytics news, events and product updates straight to your inbox