This piece is written by Casey Paxton, Content Marketing Manager at Akeneo.
Generative AI isn’t a magical, cure-all elixir for all your content needs (yet), despite what some tech visionaries say. But it can still be incredibly beneficial when leveraged correctly.
For example, generative AI truly excels in the automation of manual and repetitive tasks, like running data quality control checks. It can also enable your teams to generate more descriptive, SEO-friendly product information, getting products to market quicker in an increasingly competitive environment. This is all while freeing up your internal teams to focus on high-value, productive work.
Let’s reveal three ways you can use generative AI to support product discovery efforts, following along with fictional fashion brand “ZiggyGlam” as we go.
1. Automate Translation and Localization Processes
Generative AI flips the script on translating and localizing content, introducing a streamlined and efficient approach to the previously time-consuming, human resource-heavy task.
By leveraging powerful large language models (LLMs) and machine learning (ML) algorithms, generative AI can automatically translate a brand’s product descriptions, marketing materials, and customer support resources into different languages.
This ensures clarity and comprehension while also paving the way for increased sales. When customers can effortlessly navigate and understand product information in their own language, they feel more confident in making purchasing decisions.
And recent research backs this, showing that over 75% of global online shoppers prefer to buy products with information in their native language.
So imagine a fashion enthusiast in Tokyo browsing through ZiggyGlam’s website and reading detailed product information about a coat in their native Japanese. Or envision a fashionista in Paris scrolling through the customer reviews on ZiggyGlam’s website and reading comments translated into French that claim that the skirt runs small.
Thanks to ZiggyGlam’s dedication to providing an inclusive and personalized experience via generative AI, those international customers no longer feel isolated, which fosters a strong connection, enhances brand loyalty, and leads to repeat business and positive recommendations.
2. Generative AI for Product Discovery Can Ensure High-Quality, Complete Product Information Everywhere
In the vast realm of ecommerce, where countless products vie for attention, providing comprehensive and accurate product information across all channels is crucial. But as the product catalog expands, maintaining consistency and completeness becomes a daunting task. This is where generative AI steps in.
By analyzing existing product descriptions and identifying missing attributes, the AI system generates intelligent suggestions that can seamlessly fill those gaps, elevating the quality and completeness of the product information across the board.
Let’s say ZiggyGlam introduces a new line of dresses. The team uploads product listings, but they realize that a few crucial attributes are missing.
Armed with its analytical prowess, generative AI analyzes similar dresses and their attributes across ZiggyGlam’s existing catalog. It can then create accurate suggestions for the missing information, such as describing the fabric composition or offering care instructions that align with similar items.
Or imagine ZiggyGlam expands its product offerings to include accessories like handbags, shoes, and jewelry. Each new category has its own unique set of attributes, and manually updating and maintaining consistency across thousands of product listings would be a Herculean effort. But generative AI can help streamline and fast-track this process, ensuring that all products within a category share consistent attributes and information.
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3. Provide Hyper-Personalized Product Recommendations
In the era of abundant choices, customers crave personalized experiences that cater to their unique tastes and preferences. Brands that use advanced ML algorithms to analyze customer data and generate personalized product recommendations will have a competitive edge.
Imagine a scenario where a frequent ZiggyGlam customer, Emma, visits their website after clicking on an email she received offering free shipping for a limited time.
Emma has a penchant for vintage-inspired fashion and often shops for retro-style dresses. AI comes into play here, meticulously analyzing Emma’s browsing history, purchase behavior, and interactions with the platform. It gains a deep understanding of her preferences, creating a profile that captures her unique fashion style.
So armed with knowledge about Emma’s browsing history, purchase behavior, and interactions with the platform, the AI works its magic.
The first thing she sees on ZiggyGlam’s website is a section titled “Recommended for You” or possibly “Emma’s Picks.” Within this personalized zone, ZiggyGlam generated a curated selection of vintage-inspired dresses, accessories, and complementary items that align with Emma’s individual style preferences. The “generative” AI part of the equation comes in as the page content explicitly calls out Emma’s preference for retro looks. And everything qualifies for Emma’s free shipping coupon.
But wait! Did Emma just add a certain vintage skirt to her cart?
ZiggyGlam’s AI technology can analyze what items other customers who purchased the same skirt also bought and suggest them to Emma as she checks out.
By presenting customers with products that align with their individual preferences, ZiggyGlam increases the likelihood of conversions and repeat purchases. And customers feel a sense of connection with the brand, fostering loyalty and advocacy. (See a trend?)
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As the competition continues to intensify in the market, leveraging generative AI as part of a comprehensive Product Experience (PX) strategy becomes crucial for businesses to stay ahead.
And though generative AI is not a band-aid solution for immediate results, it does provide organizations an opportunity to streamline internal processes by reducing redundant work and automating manual processes.
Particularly in product discovery, generative AI can enable organizations to overcome language barriers, improve product information completeness, and provide personalized recommendations, all of which enhance the product discovery process and maximize customer satisfaction.
To learn more about how you can generate real business benefits from AI today, check out this recorded LinkedIn Live session, “Is ChatGPT Right For You?”
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