From Four Weeks to 12 Days: How Acclaro Helped Awin Accelerate Localization by 57% with Lokalise

Awin, one of the world’s largest affiliate marketing networks, was held back by a messy, manual localization process. Acclaro, through its partnership with Lokalise, enabled Awin to bring all localization workflows onto one platform. The solution combined AI-powered translation with expert post-editing, automated GitHub integration, and standardized processes across marketing, product, and engineering teams. The teams worked together to build translation memories and glossaries that keep every message consistent and efficient.

About the Client

Awin is a major player in the affiliate marketing world, connecting more than 30,000 advertisers with over one million publishers across 17 offices worldwide. Their 1,400-person team supports brands with technology, tracking capabilities, and partnership insights that make performance marketing work at scale.

With such a broad global footprint, Awin needs accurate, consistent content in every language to give customers and partners a high-quality experience in every market.

The Challenge

Awin’s localization work included six different teams producing large volumes of content in eight languages. Together, they managed more than 1.5 million source words, which were translated into roughly 12 million words of localized content annually.

None of the processes were standardized, and collaboration was limited between teams. The result was a mixed bag of tools like Asana, DeepL, ChatGPT, spreadsheets and more, all used differently by the different departments.

For example:

• Marketing produced nearly half of all content using a mix of unconnected tools.
• Platform services managed advertiser-facing content through their own systems
• Engineering localized platform code using Lokalise, but did so separately from everyone else.
• UX and product teams created user-facing content with independent workflows.

This scattershot approach created several pain points:

• Quality varied from team to team
• Work was duplicated because no translation memory was shared
• Turnarounds dragged, often taking four weeks
• Manual reviews took too much time across already busy teams
• No one had visibility into what was already translated or in progress

Awin couldn’t increase their budget and needed a solution, fast.

The Solution

Awin needed a localization workflow that could scale with their teams, support faster releases, and bring more consistency to their global content.

They were also seeking a language partner who already knew how to work inside Lokalise and could support a company operating at their scale. They had tried other agencies in the past, but those teams struggled with the niche terminology and industry-specific requirements Awin relies on.

With Acclaro, Awin was able to tap into the following advantages:

• Deep experience with Lokalise.
• Enterprise-level expertise, backed by work with global brands across complex, high-volume programs including Netflix, Meta and Amazon.
• A flexible approach that adapted easily to Awin’s niche terminology, industry nuances, and internal processes.

With Lokalise, Awin was able to access new technical capabilities, including API support and integrations, built-in task management, collaborative commenting, and AI features designed for human-in-the-loop review. Because Acclaro’s teams already work comfortably with these tools, we were able to help Awin take full advantage of these features from day one.

Our solution included the following elements:

One Centralized Workflow

With Lokalise as the central hub for every translation request, Awin now has one organized place to submit, track, and review content. This moved work out of spreadsheets, emails, and various tools and into a shared process everyone could follow. Translation requests now move faster—and with far less friction.

A Shared Playbook for AI-powered Translation

Acclaro developed key reference materials—including glossaries and style guides—and imported Awin’s existing glossaries, style guidelines, and past translations into Lokalise to provide the system with essential context. This significantly improved linguistic consistency and reduced the amount of editing required by linguists and reviewers.

Lokalise also selected the best large language model based on Awin’s terminology and style, improving machine-generated output before human review.

Automated Routing and Smarter Handoffs

We connected Lokalise to Awin’s existing systems, including GitHub, so updates could move through localization without extra steps. We also helped Awin standardize intake using Asana forms, which fed directly into Lokalise and reduced confusion around where and how requests should be submitted. Automated routing sent tasks to the right linguists and reviewers, reducing delays and manual handoffs.

A Human-in-the-Loop Quality Assurance Process

Acclaro’s linguists handled machine translation post-editing inside Lokalise with full context of the content. This kept turnaround times fast while protecting accuracy and tone. Automated task sequencing alerted Awin’s teams the moment the content was ready for review.

Once translations were finalized, Lokalise delivered content automatically, either as document files for marketing materials or directly through the GitHub integration for engineering updates.

More Efficient Internal Reviews

We configured Lokalise to match how Awin’s reviewers prefer to work, giving them clear visibility into source content, comments, and previous translations. This shortened review cycles and helped teams stay aligned across markets.

A Workflow That Can Scale, Globally

Together, these improvements replaced Awin’s disjointed workflows with a centralized, tech-driven localization process—one built for speed, consistency, and future growth.

Outcome and Results Achieved

Awin saw immediate gains once the new workflow was in place.

• Faster releases across marketing, product and engineering, after turnaround times improved by 57%.
• Regional teams regained valuable time as translation review cycles dropped by up to 80%.
• Future international releases were easier to plan after a long-standing localization backlog was cleared.
• Awin was able to hire a dedicated translation manager and remove translation work from seven team members’ plates, thanks to automation that saved the equivalent workload of 3–5 full-time employees.
• Quality became more consistent across eight languages, supported by shared standards and clearer context in Lokalise.
• All teams gained visibility into ongoing work, making it easier to plan releases and keep everyone aligned.

And they achieved all of this without increasing the budget.

What’s Next

Awin now has the foundation they need to keep improving their localization program. Next on their roadmap is deeper automation, stronger API integrations, and even faster internal reviews. As part of this evolution, they plan to remove internal review altogether for lower-risk content — a key step toward their goal of turning translations around in two to five days.

As their glossary, style guidance, and translation memory continue to grow, machine-assisted output will become even more accurate, reducing the amount of human editing required. The workflow will keep getting lighter, faster, and easier to maintain across markets.

Acclaro continues to support Awin as they move toward a fully streamlined model built for speed, clarity, and global scale. Our model supports faster releases without increasing the workload on their teams.