As any leader will tell you, to build a successful business, it is essential to know your customer. Understanding their challenges, goals, purchasing behaviors, and preferences is crucial to achieving the right product-market fit and developing an effective go-to-market strategy. As customers continue to expect increasingly personalized experiences, in-depth market research and analysis are indispensable business resources. 

For more than 5,000 companies worldwide, Mintel is the global market intelligence and research agency that develops market intelligence to accelerate their business growth. As international experts in what consumers want and why, Mintel’s teams of trend analysts, category specialists, systems developers, and client servicing staff deliver market research, market analysis, product intelligence, and competitive intelligence to inform and empower their clients with information on where to play and how to win. 

With more than 1,300 employees across 13 global offices, Mintel is a truly global company. As the Head of Localization at Mintel, Xiao Xiao is responsible for ensuring that the products and services that Mintel offers reach and resonate with a diverse audience around the world: “My focus is not only adapting content to meet cultural and linguistic needs but also leveraging innovative technologies and industry best practices to drive growth for both the company and each individual team member.”

To enable this global reach, Mintel sought a sophisticated technology partner to support and optimize its localization strategy. However, selecting a vendor that checked all the boxes proved challenging. While there were plenty of tools to choose from in the market, Xiao and her team needed one that could drive process efficiency while delivering the basic functions of a Translation Management System (TMS). After an intensive evaluation of multiple products, LILT, the complete enterprise language platform for multimodal content translation and generation, stood out from the rest. 

First, LILT’s AI solution was able to deliver the essential operational efficiencies that Xiao and her team required from a new tool. “Our team has utilized machine translation in the past, but they frequently faced the mundane task of correcting the same types of errors in the output from generic translation engines. This repetitive manual work was not only time-consuming but also detracted our ability to focus on more strategic aspects of localization,” Xiao shared. With LILT, Mintel’s unique Contextual AI Engine is trained with their specific preferences and continuously adapted over time, improving both output and productivity. 

Next, the LILT Platform offers the key TMS functionalities and integration capabilities that Mintel needed. LILT’s custom API integration and suite of 60+ pre-built Connectors make it easy to adopt a new vendor within an existing tech stack. Having a partner that adapted to their current workflow meant Mintel could take advantage of efficiency gains without the disruptions commonly caused by deploying and learning new systems. 

Finally, return on investment was a key metric in Xiao’s evaluation process. She needed to choose a product that could deliver necessary process efficiencies while staying within budget. Maximizing the impact of Mintel’s localization program required a tool that was cost-effective but could also help reduce labor costs and time to market. LILT’s industry-competitive pricing structure and AI-driven efficiency made it the clear choice.

In partnership with LILT, Mintel has been able to ensure that its diverse suite of products and services is accessible to its global client base in 35 countries. 

To inform their clients and enable them to advance their business strategies, Mintel delivers in-depth research insights in 5 target languages. These dynamic reports, which often contain a substantial amount of text, numerical data infographics, and product images, are crucially important to Mintel clients. With some reports spanning up to 60,000 words, human errors in translation occasionally occur, even among Mintel’s highly talented linguists. Xiao believes the value of LILT’s AI solution is its ability to streamline and augment linguist workflows to improve accuracy and prevent these errors:  “I see it as a tool to quickly process large volumes of text and provide initial translations with increased accuracy and fluency, which allows us human translators to concentrate our expertise on refining and polishing the content, rather than getting bogged down with basic translation tasks.”

In their optimized translation workflow, Mintel’s 20 internal translators work directly in the LILT Platform. In the platform interface, LILT’s Contextual AI Engine analyzes existing translation data to make predictive segment-by-segment translation suggestions. Mintel linguists can then accept or adjust these suggestions to capture any nuances that the AI may have missed. As linguists interact with the translation suggestions, Mintel’s unique Contextual AI Engine learns in real-time and updates future suggestions in the remainder of the document and future projects. These suggestions increase translator accuracy and efficiency, enabling translators to spend their time on new or particularly challenging translation work, while the system handles predictable and repetitive parts automatically. These efficiency gains are further amplified by the collaborative nature of the LILT Platform, allowing multiple translators to collaborate on longer reports simultaneously, accelerating time to market. 

Different content types require different localization workflows to effectively capture varying audience needs, styles, and formats and to optimize outcomes. A sophisticated content production strategy enables unique workflows for each content type. 

LILT allows businesses to easily choose their large language models of choice, unlocking the best models for each unique enterprise use case. Organizations can harness third-party MT, like Amazon Translate, DeepL, or Google Translate, and LLMs, like OpenAI and Amazon Bedrock, right within the LILT Platform. As companies continue to develop bespoke LLM strategies, the LILT Contextual AI Platform enables comprehensive execution of that strategy across workflows and business systems.

While Mintel’s preferred workflow for research insights includes human translators working in the LILT Platform, certain content types only require instant translation without any human intervention or edits. Leveraging the LILT Platform’s model interoperability capabilities, Mintel can use DeepL as an AI Provider for this content. Through a simple API call, Mintel can quickly send content for instant translation in seconds using DeepL’s AI Engine. To ensure accuracy and brand alignment across content types, LILT enables Mintel to opt into sending its glossaries of preferred terminology for instant translation from DeepL’s AI.

LILT has enabled Xiao to maximize the returns from Mintel’s localization program. To comprehensively assess the benefits of working with LILT, Xiao tracks five key metrics: cost savings, revenue generation, time to market, quality improvements, and team satisfaction. Through continuous evaluation, she has found that LILT delivers in all 5 areas. 

The efficiency driven by LILT’s AI solution has reduced labor and project costs for Mintel, allowing their localization dollars to stretch further and yield a greater impact. In addition to the savings, LILT has directly contributed to revenue growth: “LILT has impacted revenue through market expansion because we can translate more content quickly and accurately to enter new markets faster.” In the business of market intelligence and analysis, the faster Mintel can provide information to its clients, the more value it can provide to its clients’ business.

Finally, Xiao also regularly measures qualitative metrics, such as quality improvements across content and overall team satisfaction using the LILT Platform. Overall, LILT has been able to deliver quality and efficiency to Mintel with industry-competitive cost efficiencies. 

As a forward-thinking company with a reputation for continuous innovation, Mintel is committed to exploring and embracing new technology. Their own AI tool Leap has already revolutionized the way that they share insights with their clients. Looking ahead, Xiao and her team are excited to take advantage of new features from LILT to further enhance efficiency and accuracy in localization, including Analytics for analyzing data on model evolution and improvement and the integration of GPT-4 as an AI Engine. 

Even as AI continues to enhance productivity and workflows, Xiao believes that human expertise will always be a crucial element of the translation process: “Moving forward, our approach will continue to blend the strengths of AI technology—such as processing vast amounts of data and handling routine tasks—with the insights and expertise of our talented human translators. This combination ensures that we maintain high standards of quality and cultural relevance in our translations.”