Retail golden quarter: how AI can boost sales success for retailers

Retail golden quarter: how AI can boost sales success for retailers

New DeepL white paper underscores how Language AI will enable retailers to reduce costs and grow revenue through better internal and external communication

With the ‘golden quarter’ approaching for retailers, DeepL, a leading global Language AI company, has released its newest white paper on how retailers can make the most of AI to drive their sales during the festive shopping season.

Effective multilingual communication is a central tenet of successful retail strategies, from global supply chains, to an increasingly international customer base, assuming English as a global lingua-franca is no longer enough for retailers.

Whether to pave the way for expansion or to accelerate existing global business, AI is rapidly rising to the top of the technologies enabling retailers to do so efficiently. In fact, DeepL’s newest white paper entitled ‘The executive guide to AI-enabled communication and global retail‘ has found that AI for retailers can:

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  • Improve operational processes, for instance by scaling communications between headquarters and international offices
  • Boost employee productivity by ensuring core systems and tools (such as customer service and human resources) support employees in their local language
  • Reduce the cost and workload required to translate and localize their communications and content

David Parry-Jones, Chief Revenue Officer at DeepL commented: “The last couple of years have shown the volatility that many retailers face in their day to day operations and AI can go a long way to improving these, especially in the end of year crunch. While language can often be overseen in this context, being able to more efficiently communicate with suppliers globally can help resolve a supply chain disruption more quickly through more effective interactions. Beyond the internal wins, research shows that 75%1 of shoppers want to communicate in their native language when making purchases online, further driving home the need for effective translation options at every stage of the retail experience.”

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According to DeepL research, the top use cases for Language AI are creating content in multiple languages (46%) and communicating in languages with little to no proficiency (36%). The top translated content is external communication (57%), internal communication (39%), and marketing/advertising materials (32%). These translation needs are further demonstrated in the following scenarios where retailers most often require Language AI:

  • Translating emails, customer support tickets, and chatbot interactions to serve multilingual customers
  • Creating marketing assets in multiple languages for new collections or for specific times of year, including holiday shopping
  • Translating internal systems for international operations, such as customer service of back-end workflow tools, as well as external resources such as product information and website
  • Enabling international expansion through instant regionalization of in-store and online content

Jakob Kalina, Head of Localization at Alza further contextualized this: “The DeepL API has revolutionized our approach to managing massive amounts of user reviews at Alza. Translated reviews have enhanced customer trust in our online shopping experience. Translating hundreds of thousands of reviews from Czech to German and Hungarian has noticeably increased our conversion rates. This strategy has not only improved our customer service, but also solidified our position in the competitive e-commerce market.”

With the busiest time of the year for many retailers fast approaching, there’s still time to implement AI tools to help them gain in productivity and positively impact their bottom line. A 2024 Forrester study revealed that implementing DeepL delivered a 345% return on investment for global companies, reducing translation time by 90% while driving a 50% reduction in workload—underscoring the platform’s potential for businesses seeking to grow revenue and enter new markets faster and at scale.

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