Feb 5, 2024
In just a few months, these tools have transformed the online landscape as we know it. But for all of the excitement, brands and retailers have reservations, too.
What do LLMs mean for ecommerce? Can LLM-generated content ever be good enough to benefit enterprise retailers, with well-known brand names to uphold?
Today, we’re exploring these questions by breaking down:
What LLMs are and how they work
How they’re already being used for retail
The next big way to leverage them for ecommerce
Let’s dive in.
What are Large Language Models?
LLMs generate written content by analyzing massive data sets of text. Based on user input, or prompts, they use neural networks to predict the next most likely word in a sentence.
When prompted correctly, these models generate coherent-sounding text — but that’s actually part of a larger issue. LLM output usually appears plausible, but in reality, it’s highly generic and often full of inaccuracies.
When used straight out of the box, these models won’t create writing that supports most retailers’ goals. Basic LLM output isn’t engaging, persuasive, or tailored enough to capture customers’ interest (or purchases).
But LLMs can be a good foundation to build custom tools for highly specific use cases — including ecommerce.
How LLMs create personalized ecommerce experiences
Many exciting LLM applications for ecommerce are already being explored.
These tools work by analyzing a customer’s interactions with a brand, or analyzing customer behavior in broad cohorts (like first-time visitors). Then, the predictive tools generate content that’s likely to meet these customers’ needs.
Excellent existing use cases for LLMs in ecommerce include:
Customer support: LLMs can detect common customer questions, and generate helpful answers in a more dynamic, human-like way than a conventional chatbot.
Data analysis: Analyze content like customer reviews, return data, and customer support tickets to find insights that can be used to improve products and services.
Personalized recommendations: Recommend products a shopper might like based on past brand interactions and purchases.
Interactive LLM-powered chatbots: Analyze shopper behavior to guide them through unique, personalized buying experiences.
LLMs have already made great strides in these areas and started to transform how we shop online. But we believe these use cases are just the tip of the iceberg.
The next wave of LLMs for retail: Branded product content
The next value-add opportunity for LLMs in retail is the ability to rewrite boilerplate product copy into on-brand, differentiated content.
Brands typically create a single version of their product copy and share it with all of their retail partners. Unfortunately, few retailers have the time or resources to edit that content and bring it in line with their unique brand voice and style guidelines. For example, product descriptions for a Swiffer mop are likely identical wherever it’s sold, from Target to Walmart.
That’s a glaring issue because retailers invest a lot of time and money into these guidelines.
From your FAQs to the titles of your PDPs to your social media captions, on-brand content is the foundation of a differentiated brand identity that resonates with your target customers. Without it, there’s no reason for shoppers to choose you over the competition.
Plus, unique product content can improve a retailer’s search rankings. For example, Google prefers original content to the same boilerplate copy across dozens of websites. It’s a foundational principle of the search engine’s guidelines on creating helpful, reliable, people-first content.
On-brand product content across thousands of SKUs
Better search rankings get more customers to your site. After they land on your homepage, fresh, on-brand product copy speaks directly to your target customer.
The end result? More traffic, conversions, and sales.
Most retailers already understand the power of branding. But before LLMs, achieving it across an entire catalog’s worth of product content was a pipe dream. Now, it’s possible to quickly rewrite thousands of descriptions, titles, and FAQs in your brand’s voice.
To be clear, LLMs don’t have this capability out of the box — they need to be built into custom tools.
But LLM-based content tools for retail, like Optiversal, can be trained on brand voice, style guidelines, and other parameters to rewrite product content in a way that’s unique to each retailer.
Optiversal: LLM-powered product content at scale
Unique product copy drives site traffic, conversions, and revenue. Now, Optiversal is bringing it within reach at an enterprise scale. We create product content that’s personalized to your website and ideal customer profile, even across thousands of SKUs.
This isn’t generic AI content either. We use custom models built for ecommerce, trained on your brand's product catalog, voice, and style guide to produce:
Unique, on-brand descriptions
Helpful product Q&As
Search-optimized product titles
That’s just one reason why some of the world’s best retailers use Optiversal. One top pet retailer saw CTR boosts up to 28% using our differentiated Product Content.
Ready to have AI-powered product content supercharge your search rankings, traffic, and revenue? Book a demo today.