Generative AI for retailers, first use case: deep dive with AI-generated product descriptions and translations.

The retail landscape is on the brink of a revolution, thanks to Generative AI. With its ability to drastically reduce time to publication and content creation costs, retailers are looking at a future where their brands can truly speak in their unique voice without the limitations of human bandwidth. In this guide, we dive into why and how retailers should implement Generative AI for generating and localizing product descriptions, drawing from Newtone’s innovative approach to this AI application.

The first retail-focused use-case: the impact of using Generative AI for product descriptions

Time and Cost Efficiency

The first and most palpable benefit of using Generative AI is the significant reduction in time and costs associated with producing product descriptions. The traditional method of manually crafting these necessitates a considerable amount of human effort and time, factors that are directly proportional to the costs involved. Newtone's application of Generative AI has successfully reduced the time to publication on the web by 100x and slashed direct costs tied to copywriting and translation by 4x to 8x. This paradigm shift also mitigates indirect costs, which can sometimes be up to 10x the direct costs, encompassing product stockpile without online listing, pressure on copywriters, and the consequent neglect of other marketing priorities.

Enhancing Copywriter Satisfaction

An often-overlooked aspect is the morale and satisfaction of copywriters. As Generative AI can be perceived as a threat by some of them, most of them see it as a true copilote of their day-to-day work: “Generative AI lifts the burden of mundane product description tasks from our copywriters, allowing them to focus on creating engaging and high-quality content,” a marketing specialist observed. By automating the repetitive and less creative aspect of their workload, Newtone helps maintain a happier, more productive creative team.

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Keeping Brand Consistency

A common concern among retailers is the potential loss of brand consistency and tone-of-voice with automated content generation. However, specialized tools like Newtone are designed to address this issue head-on by training AI models on the client’s brand guidelines and tone-of-voice. This ensures that the AI-generated content “sounds and feels like your brand,” maintaining a seamless brand identity across all product descriptions.

SEO Performance

Another significant advantage of AI-generated product descriptions is their SEO performance. “Unlike humans, AI doesn’t succumb to the pressures of high-volume writing within tight deadlines, allowing it to consistently produce SEO-optimized content,” explains a SEO specialist. This is a stark reminder of the efficiency AI brings, not just in the quantity of content produced but also in its quality.

Convincing the CMO

Getting buy-in from the top is crucial for the adoption of new technologies. Highlighting the key benefits such as preserved brand consistency, improved publication timelines, and the cost-efficiency of using Generative AI for product descriptions can be persuasive arguments. “The potential for reallocating saved resources towards refining our content strategy is a compelling proposition for any CMO,” says a seasoned marketing executive.

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Cost and Integration Ease

Understanding the cost implications and the ease of integration is vital. Starting with Generative AI shouldn’t require hefty integration projects. “A simple exchange of excel files or a CSV integration may suffice for quality testing on a meaningful scale with no upfront integration costs,” explained our CEO during a Retail Tech event. Compatibility with existing tools, like major PIM solutions, underscores the importance of selecting a provider that understands the retailer's ecosystem, reducing potential integration costs significantly.At Newtone for example, our integration with Akeneo, the leader in Product Information Management (PIM), allows a two-clicks integration to deploy Newtone AI in a PIM.

Testing on a Significant Scale

To accurately gauge the effectiveness of Generative AI in your retail operations, we recommend testing on at least 100 to 200 products across various categories and languages. “This scale ensures that the test is representative and provides a clear view of what the AI can achieve for your brand,” states Richard Knudsen, CTO and co-founder of Newtone. Such thorough testing underlines the potential of AI in transforming product description processes across the retail industry.

Conclusion

The implementation of Generative AI in the creation and localization of product descriptions presents an exciting opportunity for retailers. It promises not only to enhance efficiency and reduce costs but also to maintain, if not enhance, the quality of content. With tailored solutions like Newtone, retailers can embark on this journey with confidence, knowing their brand identity and SEO performance are in capable hands. As the retail world evolves, those who leverage the power of Generative AI in their content creation strategies will undoubtedly stand out in the crowded marketplace.