Few growth levers move revenue like localization. Brands that localize can achieve higher website traffic, stronger conversion, and product experiences that retain customers once they arrive. Yet when the CFO asks for proof of return, many teams still cannot answer basic questions about their localization program.
In interviews with nine enterprise customers, Lokalise found that seven still ran parallel systems across Notion, spreadsheets, and language service provider reports because the reporting they had was neither complete nor trusted. The monthly cycle will sound familiar: hours spent exporting and reconciling data, vendor invoices checked by hand, and the case for AI translation resting on a general sense that work is moving faster.
Lokalise Analytics provides a holistic view of localization performance, with dashboards that span teams and projects, detailed data, and report filters that make progress easier to share with leadership.
Localization analytics is essential for reporting on return on investment and improving efficiency. Without reliable data, localization risks being perceived as a cost alone. Budgets are harder to defend, and teams investing in AI translation struggle to show the impact on time, quality, and savings.
Analytics brings three core benefits, each connected to the bottom line:
This turns localization from a line item into a growth investment leaders can defend. For a broader business-case framework, see how to calculate and communicate localization ROI.
Localization metrics show how much content a program produces, how efficiently work moves, and how good the output is when it reaches customers. The main areas to monitor are:
These metrics complement the wider set of localization metrics that connect operations to business goals.
The Translation Quality dashboard shows how much effort it takes to produce high-quality translations. Teams can compare results across workflows, languages, translators, reviewers, projects, tasks, and translation methods.
Several metrics reveal how much work a translation required. Post-edit rate shows the share of reviewed translations that a reviewer changed. Average edit distance shows how far the text moved, separating a minor correction from a substantial rewrite. Review effort then groups reviewed content by the amount of editing required. Quality trends plot these metrics over time so teams can see whether their improvements are working.
Translation quality often varies by language pair. A higher post-edit rate or edit distance can point to a language, workflow, or translation method that needs attention. Contributor-level reporting adds context so teams can distinguish language-specific patterns from differences in review behavior.
Budget, deadlines, and accountability often sit at project level. Project and task detail reports make it possible to determine whether a quality issue affects the entire program or is contained within a particular workflow, language pair, contributor, or task.
AI Scoring is included in Analytics, allowing teams to compare model confidence and detected issues with post-edit rates, edit distance, and actual review activity. The Translation Quality dashboard documentation explains the available reports and metrics in more detail.
Localization measurement often stops when content is published. For mobile and app teams, that leaves out whether translated content reached the device and how much of it customers downloaded.
Over-the-air data is available in Analytics alongside processed words, translation methods, users, and translation memory leverage. Teams can monitor traffic and downloads by platform and review project-level usage in one place.
The Tasks dashboard shows pending and overdue work, task volume, completion time, workload, and contributor activity across projects. Teams can compare performance by language, project, contributor, and task size, then use task detail reports to investigate slowdowns.
It also includes translation memory coverage at task creation, helping teams estimate how much content could be covered by existing translation memory before work begins. See the Tasks dashboard guide for a full breakdown.
Shared filters make it easier to move between analytics dashboards without rebuilding the same view. Teams can start with a summary number, then narrow the results by date, language, project, translation method, task type, contributor, or other available dimensions.
Configured views can be shared by URL, allowing a colleague or stakeholder to open the relevant slice of data without recreating the filters. This is useful for recurring program reviews, vendor conversations, and leadership reporting.
Lokalise Analytics is out of beta and available on all paid plans. Dashboards update every 24 hours, making them suitable for weekly, monthly, and quarterly program reviews.
Teams can use one workspace to assess translation quality, understand review effort, monitor usage and tasks, compare AI quality signals with reviewer behavior, and share evidence of progress with leadership.
Localization has always produced evidence of its own value. Analytics makes that evidence easier to find, understand, and act on.
What is Lokalise Analytics?
Lokalise Analytics is a reporting workspace for monitoring localization usage, task performance, translation quality, review effort, translation memory, and AI Scoring across projects.
Which localization metrics should teams track?
Teams should track usage and translation volume, task completion and turnaround time, post-edit rate, average edit distance, review effort, translation memory coverage and leverage, and AI quality signals. The right mix depends on the decisions and business outcomes the team needs to support.
How does Lokalise Analytics measure translation quality?
It combines review metrics such as post-edit rate, average edit distance, review effort, and editing activity with filters for language, project, workflow, translation method, translator, and reviewer. AI Scoring adds model confidence and detected issue data for comparison with actual review outcomes.
How often does Lokalise Analytics update?
Lokalise Analytics dashboards update every 24 hours. This cadence supports regular operational reviews, stakeholder reporting, and trend analysis.
Which plans include Lokalise Analytics?
Lokalise Analytics is available on all paid plans. Enterprise plans include additional filtering and export options for deeper analysis. Team administrators can access the dashboards.
Author
Hi, I’m Marta, Senior Product Marketing Manager at Lokalise with 8+ years of experience across SaaS, product marketing, and global communication. I work on product launches, customer storytelling, AI localization initiatives, and go-to-market strategies that help companies connect with international audiences.
I’m especially interested in the intersection of AI, localization, and multilingual product experiences, and I regularly contribute to content and conversations around global growth and modern localization workflows. I’ve also hosted webinars and educational sessions on topics including AI translation, localization strategy, and scaling multilingual content for international teams.
I enjoy exploring creative approaches to storytelling and personal branding in tech — including a viral LinkedIn video campaign that turned my job search into a movie trailer-style product marketing launch.
I studied at Universitat de Barcelona and have worked with international teams throughout my career in tech, combining strategic communication with a strong customer and product focus.
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