How can you balance the needs of different user languages in a product roadmap?

1 Define your target markets

The first step is to identify and segment your target markets based on the languages they speak, the regions they live in, and the problems they face. You can use data from your analytics, user research, and feedback to understand who your users are, what languages they use, and what pain points they have. This will help you define your user personas, value propositions, and market fit for each language segment.

3 Prioritize your language segments

The third step is to prioritize your language segments based on their potential impact, value, and demand. To do this, you can use a prioritization framework such as the RICE score. This score is based on four criteria: Reach (how many users will benefit), Impact (the improvement in user satisfaction, retention, and revenue), Confidence (your estimates of reach and impact), and Effort (time, money, and resources required). You can visualize your language segments using a matrix or chart to compare their RICE scores. This will help you decide which ones to focus on first, which ones to defer or deprioritize, and which ones to drop or eliminate.

4 Plan your language features

The fourth step is to plan your language features based on your localization strategy and your language segment priorities. You can use a product roadmap tool, such as Asana, Trello, or Productboard, to create and manage your language features as tasks, cards, or items. You can also use a language tag or label to filter and group your language features by segment. You can then assign your language features to your team members, set deadlines and dependencies, and track progress and status.

5 Deliver your language features

The fifth step is to deliver your language features according to your roadmap plan. You can use an agile methodology, such as Scrum or Kanban, to break down your language features into smaller and manageable units, such as user stories, epics, or sprints. You can also use a localization platform, such as Transifex, Crowdin, or Lokalise, to automate and streamline your translation and localization workflows. You can then test, validate, and launch your language features to your users, and measure their feedback and results.

6 Iterate and improve your language features

The sixth step is to iterate and improve your language features based on your user feedback and data. You can use a feedback tool, such as UserTesting, SurveyMonkey, or Hotjar, to collect and analyze user feedback from different language segments. You can also use an analytics tool, such as Google Analytics, Mixpanel, or Amplitude, to track and evaluate user behavior, engagement, and conversion from different language segments. You can then use these insights to identify and prioritize improvements, enhancements, or new features for your language segments, and update your roadmap accordingly.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?