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Welcome to the GitLab Analytics section direction. This content is maintained by Kenny Johnston. Please feel free to reach out to Kenny Johnston (GitLab Profile, Email) or submit and MR to this page with suggestions.
Despite the name, the Analytics section doesn't encompass all analytics capabilities in GitLab. Whether categories like Value Stream Analytics, or capabilities like Issue, Release, or CI/CD analytics those are not within the scope of the Analytics section.
The Analytics Section closes the DevOps loop. It provides developers the tools to engage with users so they can move beyond improving their efficiency, to accelerating their effectiveness. Our vision is to continue to extend DevOps across its most painful gap - measuring user value.
The Analytics Section is comprised of a single Stage, the Analyze stage. This stage has two groups:
Given our focus on developers, the software delivery value stream, and DevOps - we will compose our new DevOps stage, Analyze, based on the set of categories we commonly see in User Engagement competitors. Those include (in priority order):
There are a number of existing (or considered) product categories in GitLab that could be considered part of the outer loop that the Analytics section will partner closely with to ensure we provide a cohesive experience. Those include:
We have the right to win in this new Section because:
Our 1 year plan is to:
The Analytics section will further extend GitLab's lead in being the One DevOps platform by consolidating yet another set of existing tools required to deliver software value to users.
All current DevOps platforms define their water's edge at Monitoring - ensuring a deployed idea is available and performant for users. The process of visualizing and learning from usage, collecting and organizing feedback, engaging and enabling users - those are all left to specialist vendors positioning their products at Marketing, Growth and Product teams.
One critical trend in this market is a clear move to first-party data (partially a result of ITP) as the use of third-party SaaS services to store user data increasingly causes data privacy compliance and brand concerns.
From conversations analysts we expect the market definitions to become crisper and to see a new segmentation that includes developer-focused user engagement products called Product Analytics.
The traditional markets for this stage are fragmented across IT Operations, Marketing Automation, and Customer Data Platform markets. The market most closely aligned to our intent is Customer Data Platforms - a market that IDC states was $1.3B in 2020 and expected to grow to $3B by 2025 (18% CAGR).
The market is divided between big tech entrants building on top of complete Marketing Automation platforms marketed towards enterprise marketing orgs and stand-alone tools user engagement tools that are marketed towards Product (and occasionally Development) teams.
Due to the heavy emphasis on SaaS and the high data volumes - most pricing in this market is consumption-based.
We will pursue this opportunity with the following principles:
Our Performance Indicators are TBD.
We are conducting research on critical jobs to be done for the Analytics section.
We will likely need additional personas but the existing personas we serve are (in priority order):
Our tiering plan will leverage our buyer-based model. The Analytics section, as a bridge from Ops to Dev (Plan) is an inherently collaborative stage. As a result, there are significant Paid Tier possibilities. Core will be seen primarily as a developer on-ramp.