The following page may contain information related to upcoming products, features and functionality. It is important to note that the information presented is for informational purposes only, so please do not rely on the information for purchasing or planning purposes. Just like with all projects, the items mentioned on the page are subject to change or delay, and the development, release, and timing of any products, features or functionality remain at the sole discretion of GitLab Inc.
As part of our overall 3 year Strategy GitLab is striving to build a Customer Centric DevOps platform through Strong Data Insights. In order to empower our customers to achieve their goals, and ultimately enable GitLab to ship a world class DevOps product, we must provide the necessary data and reporting so all teams within the business can identify opportunities, mitigate risks, and make the right decisions. By providing robust and accurate reporting we can reduce the cycle time from when we release a change, to when we know its impact to overall product usage, and customer experience, helping all of GitLab reach our goals through operational efficiencies, R&D allocation/investment, development priority, etc.
To accomplish this, we aim to leverage our deep expertise, tied with investments in a strong technical foundation to enable all teams within GitLab to produce, analyze, and report on product data by FY23-Q4. Like many top software/SaaS companies we are moving to be a product-led and data-driven organization. Through a partnership with our Data Team and collaboration with Product and Engineering we are cultivating a strong data focused culture within GitLab, driving to support our 30 year BHAG company goal of "becoming the most popular collaboration tool for knowledge workers in any industry".
In order to build the best DevOps product we can, and provide the most value for our customers, we need to collect and analyze usage data across the entire platform so we can investigate trends, patterns, and opportunities. Insights generated from our Product Intelligence program enable GitLab to identify the best place to invest people and resources, what categories to push to maturity faster, where our UI experience can be improved and how product changes effect the business.
We understand that usage tracking is a sensitive subject, and we respect and acknowledge our customers' concerns around what we track, how we track it, and what we use it for. We will always be transparent about what we track and how we track it. In line with our company's value of transparency, and our commitment to individual user privacy, our tracking source code and documentation will always be public.
GitLab's single application approach to DevOps creates a product that is both wide and deep, encompassing a large collection of features used by many teams within an organization, which are composed of different types of users.
|12 Month Vision||3 Year Vision|
|Build reliable and scalable data instrumentation, collection and delivery tools across platforms,which enable developers and product teams to glean insights from their development efforts.||Build a product usage data framework which sits at the core of how we build product at GitLab; powered by intelligent instrumentation, exhaustive events collection, reliable and understandable data outputs with self-serve discovery and analysis capability.|
Business Outcome. In rapid development environment GitLab team members needs as broad data available as possible in order to flexibly adapt to new features, stages and use cases emerging without need to manually instrument tracking. Teams Involved. Product Intelligence, Data, Infrastructure
Problems to Solve.
Business Outcome. GitLab team members needs trust worthy data to build analysis upon. Whenever data is lost it causes distortion and reduce trust. Teams Involved. Product Intelligence, Data, Infrastructure
Problems to Solve.
Business Outcome. Increase product usage data coverage. Comprehensive product usage data will allow us to make better product decisions. Teams Involved. Product Intelligence, Data, Product, Product Data Analysts
Problems to Solve.
Business Outcome. GitLab team members need the ability to measure product usage using a common method for customers on both self-managed and SaaS platforms. Teams Involved. Product Intelligence, Data, Customer Success
Problems to Solve.
For more information on Product Intelligence, you can checkout our Product Intelligence Guide which details a high-level overview of how we make data usable, the Collection Frameworks we leverage, our Metrics Dictionary, and much more!
Product Intelligence provides the necessary frameworks, tooling, and expertise to help us build a better GitLab. Naturally we sit in the middle of many projects, initiatives and OKRs at GitLab. In order to provide clarity and realistic expectations to our stakeholders and customers we practice ruthless prioritization(per Product Principle #6), identifying what is above the line, what is below, and what is unfunded and not possible for us to action on in a given timeline.
|GTM Product Usage Data Working Group||Weekly||Sync||Fulfillment PMs, Product Intelligence, Data, Customer Success, Sales|
|Data & Analytics Program for R&D Teams||Every 2 Weeks||Sync||Fulfillment PMs, Product Intelligence, Growth, Data|
|Product ARR Drivers Sync||Monthly||Sync||Customer Success, Sales, Product Leadership|
|Product Intelligence Guide||A guide to Product Intelligence|
|Service Ping Guide||An implementation guide for Usage Ping|
|Snowplow Guide||An implementation guide for Snowplow|
|Metrics Dictionary||A SSoT for all collected metrics from Usage Ping|
|Implementing Product Performance Indicators||The workflow for putting product performance indicators in place|
|Product Intelligence Direction||The roadmap for Product Intelligence at GitLab|
|Product Intelligence Development Process||The development process for the Product Intelligence groups|