Generative AI Recommendation Engines – Free Training and Coding Demo

Picture of Lillian Pierson, P.E.

Lillian Pierson, P.E.

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As data professionals, we’re no strangers to the power and potential of recommendation engines. However, the landscape of recommendation technology is undergoing a profound transformation, thanks to generative AI. In today’s post, you’ll learn the differences between ML- and LLM-based recommenders. Access a free training on how-to build generative AI recommendation engines.

Gone are the days when mere collaborative and content-based filtering would suffice.

With generative AI recommendation engines, we’re able to produce real-time, sequence-based, highly personalized product suggestions that detect and predict intricate user behaviors with unparalleled accuracy!

😅 The bar is A LOT higher now with generative AI recommendation engines

From my experience as an ecommerce shop owner myself, I’ve witnessed the bar for personalization getting higher and higher with every passing year. But now, with generative AI on the scene – next-level performance is what all big ecommerce vendors are pushing for, FAST!

Generative AI’s introduction to ecommerce has brought about a paradigm shift, unveiling capabilities that traditional ML-based recommenders could only dream of. Let’s dive deeper into how the two differ and why generative AI is the new game-changer:

the difference between ML-based and generative AI recommendation engines

1. Dynamic Real-time Recommendations

  • Traditional ML-based recommenders: They often rely on batch processing, analyzing user behavior from previous sessions to generate recommendations. This means that if a user’s preference changes during a browsing session, the system might miss it.
  • Generative AI: Generative AI recommendation engines offer LLM-based (Language Model-based) personalization, which means it’s constantly learning and adapting. As customers shop, it can instantly recommend additional, pertinent products, making the shopping experience even more fluid and responsive.

 

2. Sequence-based Recommendations

  • Traditional ML-based recommenders: These systems typically suggest products based on popularity or basic user behavior, often missing the nuanced sequence in which some products should be presented, especially in domains like grocery shopping.
  • Generative AI: Recognizes the importance of sequence in recommendation. It understands that after selecting pasta, a customer might want sauce next, followed by cheese. This sequence modeling ensures the recommendations are not just relevant but also contextually appropriate.

 

3. Hyper-optimized User Experiences

  • Traditional ML-based recommenders: These systems often require manual tuning and regular updates to offer content and recommendations. They might be able to identify best-selling products but can struggle with real-time inventory optimization.
  • Generative AI: Generative AI recommendation engines take optimization to a whole new level. Not only can it fine-tune content and offers on-the-fly, but it can also predict inventory demands by analyzing real-time shopping behaviors, ensuring businesses never miss out on potential sales due to stockouts.

 

In essence, while traditional ML-based recommendation systems have served us well, the dawn of generative AI in ecommerce is ushering in a more adaptive, intuitive, and efficient era.

In essence, while traditional ML-based recommendation systems have served us well, the dawn of generative AI in ecommerce is ushering in a more adaptive, intuitive, and efficient era.

The intricate processes that Generative AI bring to the table might seem intricate, but the enhanced user experience and business outcomes they promise are undeniably transformative.

That’s one reason I’m so excited to be partnering with SingleStore to bring you this free training!

 

📆 FREE TRAINING: Building best-in-breed generative AI recommendation engines with OpenAI & JSON

Visualize yourself being the leader of the pack in this new breed of innovation…

If you’re interested in learning how-to harness the groundbreaking capabilities of generative AI to build hyper-personalized shopping experiences, this is a training event you CANNOT miss.

Get a free training on building Generative AI recommendation engines

** This training on building generative AI recommendation engines was delivered live and is now available here on-demand **

Topic: How to Build a Product Recommendation App Using JSON + Unstructured Data

Save Me A Seat >>

Look, this session is meticulously designed for visionaries like you.

Here’s a glimpse of what you’ll be getting within this free 60-minute session:
  • An immersive demo that shows you what it takes to build real-time interactions with OpenAI for online grocery cart suggestions.
  • An in-depth codeshare session which provides a holistic overview of the development processes that’s involved.
  • Expert-led walkthroughs on leveraging JSON, unstructured data, free-text vector search, and site analytics for use in architecting avant-garde product recommendation systems.

 

What are you waiting for?

The next chapter in ecommerce personalization is being written and you, my friend, are poised to be a key contributor!

 

Sign Me Up >>

 

Dive deep, engage with pioneers, and equip yourself with the expertise you need to craft recommendation apps that will set the gold standard in the industry.

Tap here to reserve your spot for the free training >>

 

The buzz around this transformative technology is palpable.

Secure your place today so that you can position yourself at the cutting-edge of generative AI ecommerce innovation.

 

Pro-tip: If you like this type of training, consider checking out other free AI app development trainings we are offering here, hereherehere, here, and here.

 

 

Yours Truly,

Lillian Pierson

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PS. Don’t miss this chance to get trained for free on how-to build generative AI recommendation engines w/ OpenAI

PPS. If you liked this blog, please consider sending it to a friend!

Disclaimer: This post may include sponsored content or affiliate links and I may possibly earn a small commission if you purchase something after clicking the link. Thank you for supporting small business ♥️.

HI, I’M LILLIAN PIERSON.
I’m a fractional CMO that specializes in go-to-market and product-led growth for B2B tech companies.
If you’re looking for marketing strategy and leadership support with a proven track record of driving breakthrough growth for B2B tech startups and consultancies, you’re in the right place. Over the last decade, I’ve supported the growth of 30% of Fortune 10 companies, and more tech startups than you can shake a stick at. I stay very busy, but I’m currently able to accommodate a handful of select new clients. Visit this page to learn more about how I can help you and to book a time for us to speak directly.

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