Jiffy is a popular online marketplace in Canada that connects homeowners and service professionals. Aziz Kara, Head of Product at Jiffy, shared the case study about their localization strategy.
Jiffy needed to expand from an English-only market into Montreal, which required a full translation of their 200,000+ word platform into Quebec French.
The localization goal was ambitious: launch by Q4 2025 while staying within their existing headcount and budget. Facing a big word count and a tight deadline with only one human proofreader, Jiffy realized a traditional translation model was unworkable.
The Bottleneck of Traditional Localization
The old-school translation workflow, involving manual copy collection in spreadsheets, external context slides, and developers manually copying translations into code, was a significant barrier. Jiffy correctly identified that this method was:
- Slow. It created a bottleneck that would never meet their critical Q4 deadline.
- Unscalable. Impossible to manage 200,000+ words across a constantly changing product with a small team.
- Hard to manage. Difficult to track translations and context across different app sections, and continuous updates.
They needed an automated, modern, and scalable solution for their growing product.
How Jiffy Created a Modern Localization Pipeline
Jiffy chose Crowdin to implement a high-speed, high-quality localization pipeline. For Jiffy, Crowdin was selected for its integrations, including with Figma and Google Workspace, as well as features like a Glossary, Translation Memory, and a strong AI pre-translation engine.
Here is how Crowdin’s platform enabled Jiffy to transform their challenge into a step-by-step workflow:
1. AI-Powered Speed, Human-Controlled Quality
Jiffy’s initial instinct was to use only an LLM like ChatGPT to translate content. However, after testing the production copy, they realised that the translations often leaned toward European French or felt slightly mechanical. They lack the native Quebecois French dialect.
The key was recognizing that AI alone would not be enough. Crowdin’s integrated AI translation feature (OpenAI’s gpt-4o-mini) became the key to acceleration, not translation completion. Approximately 75% of all words were pre-translated instantly by the AI.
This allowed the single proofreader (a native Quebecois French speaker) to focus on reviewing, editing, and quality, ensuring the tone was natural and authentic, rather than translating from scratch.
2. Consistency Over the Project
To maintain its reputation for reliability and quality (Jiffy boasts a 96% perfect rating on over 500,000 jobs), consistency in the content was highly important.
- Jiffy created a central glossary of key brand terms and their approved French translations.
- Every approved translation was automatically saved in translation memory and reused whenever a similar phrase appeared across the platform. This ensured consistency across the entire 200,000-word scope.
3. Proofreading with Visual Context
One of the main pitfalls of traditional translation is the lack of context. Jiffy solved this critical issue by using the Crowdin Figma plugin. This tool automatically linked text strings to app screenshots.
Visual context allowed the proofreader to see exactly how the text would appear on the screen, catching layout issues (like text being too long or breaking the UI) and eliminating the need for manual checks.
The Bottom Line: On-Time, On-Budget Localization
By adopting Crowdin’s modern workflow, Jiffy successfully localized over 200,000 words across their platform in just six months.
Jiffy successfully launched in the Montreal market in Q4 2025, on time and without exceeding their budget or required headcount. Their experience demonstrates the massive impact of adopting an automated, platform-based localization solution that leverages AI for quick drafts and human expertise for final quality and cultural nuance. Book a demo to discover what localization strategy suits your business needs.