In the vast and competitive landscape of eCommerce, standing out and delivering exceptional customer experiences is paramount to success. One of the key challenges for online retailers is ensuring that customers can easily discover relevant products from their vast catalog. This is where AI-powered product discovery comes into play.
As technology continues to evolve, AI-powered product discovery is becoming more sophisticated and more prevalent in the eCommerce industry. Advancements in search technology, natural language processing and deep learning are helping businesses deliver even more accurate and context-aware search results and recommendations. This allows businesses to leverage sophisticated algorithms to enhance search results, improve conversions, and ultimately revolutionize the way customers navigate their online shopping experiences while also reaping incredible back-end benefits.
The continuous integration of AI into product discovery is transforming the way customers discover and engage with products, creating immersive and personalized shopping experiences.
Product discovery is the process by which customers find and explore relevant products that match their needs and preferences. Traditionally, this has relied on search bars and filters, which often lead to subpar results. AI-powered product discovery takes this concept to the next level, utilizing advanced algorithms and data analysis to provide customers with more accurate and personalized recommendations.
In an eCommerce business, the success of product discovery directly impacts customer satisfaction, conversions, and ultimately, revenue. When customers can easily find what they're looking for, they are more likely to make a purchase, resulting in higher sales. Additionally, a positive product discovery experience enhances customer loyalty and encourages repeat purchases.
Product discovery and product findability is deeply impacted by the technology used, and retailers are repeatedly choosing AI to power their product discovery experience. However, before we dive into how AI is revolutionizing eCommerce, there are a few terms we need to clarify.
Phrases like "AI-powered" or "AI-driven" or "AI-first" get bandied about a lot on the internet, and in marketing claims. However, there are some key differences between them.
AI-Driven and AI-Powered are largely interchangeable, and are used to describe a process that is powered by the capabilities of artificial intelligence. A product discovery process that is powered by or driven by AI, might rely on AI or Machine Learning algorithms to power a portion of their process, such as personalization, but the whole process does not rely on AI.
AI-First technologies, on the other hand, are completely powered by AI. In the case of eCommerce search and product discovery, an AI-first platform uses a search engine that, instead of layering AI over legacy keyword-matching technology, has been completely rebuilt from the ground up to be AI-first. It is then trained on vast arrays of data -- far more than legacy systems -- and is continually refining output based on user data. It also possesses a superior understanding of user intent and context -- even when compared to AI-powered or AI-driven platforms.
You should pay attention to which phrases are being used to describe a product discovery platform, as it can tell you a lot about how that platform functions.
- Compile and Enrich Your Data
The foundation of all search is data. And bad data leads to bad search. This is why GroupBy's AI-first eCommerce Search and Product Discovery platform powered by Google Cloud Vertex AI Search for Retail, starts the product discovery process by compiling data from all of your sources. Be it in-store data, offline data, clickstream data or even your product catalog data, we compile and normalize it all before starting the enrichment process.
Enriching product data is extremely important to product discovery. If a customer searches for a specific attribute and that attribute isn't a searchable part of your product description, the search engine cannot bring back the customer's ideal product. This is why the accuracy of product data is so important: it directly impacts search performance. And according to Google Cloud's research, each sale lost to search abandonment costs, on average, $72!
Even an AI-first engine needs great data to deliver good results, which is why this is the first step in the process.
- Leverage Artificial Intelligence and Machine Learning
Once your data has been normalized and uploaded, the AI takes over. AI-first product discovery utilizes artificial intelligence and machine learning techniques to understand customer preferences and behavior patterns. By analyzing vast amounts of data, including customer interactions, previous purchases and browsing history, these algorithms can provide highly relevant and personalized product recommendations.
The AI-first search engine powering the GroupBy's entire product discovery platform automatically uses this data to deliver search results that are relevant, buyable, personalized and optimized for revenue. By displaying products in revenue maximizing order, retailers boost conversion and click-through rates, and sales.
- Deliver Relevant, Personalized, Buyable Search Results & Product Recommendations
With AI-first product discovery, customers can expect to see more relevant and tailored search results, yes. They no longer have to sift through endless pages of irrelevant products that don't match their stage of the customer journey because AI-first solutions can deliver individually personalized search results. The AI takes into account various factors such as individual preferences, browsing history, and purchasing behavior to display the most suitable and enticing items.
This applies to product recommendations as well. AI-first product recommendations are also based on individual customer profiles. They consider factors like previous purchases, wish lists, and demographic data, and then leverage machine learning algorithms to provide a more curated and engaging shopping experience. By leveraging the superior understanding of user intent and content that AI-first search engines possess, retailers can deliver complimentary product recommendations, not just more of the same item.
AI has superior pattern recognition to humans and can identify not just what products go together, but which products are most likely to be purchased next. This is what allows it to deliver data-driven suggestions that are statistically likely to be purchased. These smart and personalized recommendations create a sense of connection and make customers feel understood, leading to increased satisfaction and loyalty.
Improving Conversions and Sales
By leveraging AI-powered product discovery, eCommerce businesses can significantly improve their conversion rates. When customers find the products they desire quickly and easily, they are more likely to make a purchase. In fact, according to research by Google, 92% of consumers will purchase an item after a successful search for that particular item. In addition, over three-quarters of shoppers will buy at least one additional item, and on average three (!) additional items are purchased.
Great search streamlines the user experience, reduces friction in the buying process, and increases customer satisfaction, ultimately leading to higher sales and revenue.
Expanding Product Catalog Discoverability
eCommerce businesses often struggle to showcase their extensive product catalogs effectively. AI-powered product discovery enables businesses to overcome this challenge by enhancing the visibility of a broader range of products. By improving data quality to fix search problems at the core, and leveraging a best-in-class next-generation search engine custom built for retail applications, retailers can effortlessly recommend relevant items that online shoppers may not have discovered otherwise, effectively expanding the reach and potential sales of the entire catalog.
Productivity and Efficiency Boosts
AI comes with a whole host of benefits, and AI-first eCommerce search and product discovery is no different. Traditional eCommerce merchandising relied on platforms adding more and more product features to compensate for the shortcomings of legacy technology. Merchandisers today spend as much as 60% of their time manually tuning and curating search rules -- however, AI-first solutions almost completely eliminate the need for this repetitive task.
Since the AI is dynamic, it sorts products in revenue maximizing order, and it can boost and bury products when, for example, an item goes out of stock. The AI can also prioritize specific business goals and key eCommerce metrics such as conversion rate and average order value. This leaves the merchandising team free to focus on strategic, revenue-generating activities and other initiatives that stimulate business growth, which the AI cannot do.
Implementing an AI-powered product discovery platform can be done relatively quickly if you're using a composable commerce approach. However, despite the quickness of some implementations -- GroupBy's platform can be implemented in as little as 7 to 12 weeks! -- there are a few questions you should ask when selecting your solution.
- What Are Your Needs and Goals?
Before implementing an AI-first product discovery solution, it's crucial to assess your specific needs and goals. What business impact do you want this piece of your tech stack to have?
Consider factors such as the size of your product catalog, the complexity of your customer data, and the level of personalization you aim to achieve. Assessing platform features, scalability, and integration options to ensure they seamlessly integrate into your existing eCommerce platform is also important. Most legacy solutions can be assessed on a feature/function basis, but AI-first search and product recommendation engines work differently. While they contain all of the controls of their legacy counterparts, how the AI functions provides additional benefits that can provide a competitive edge for eCommerce retailers.
This evaluation will help you choose the right AI tools and solutions that align with your desired business outcomes.
- Is It AI-Driven, AI-Powered, or AI-First?
As noted above, AI-Driven, AI-Powered and AI-First mean different things. An AI-first platform is the most powerful and dynamic, and will serve most retailers who've adopted a composable commerce approach well. However, if your company prefers to keep merchandising as a manual task, an AI-first platform may not be the right choice for you.
When selecting your platform It's important to consider case studies and customer reviews, and make data-driven decisions whenever possible. If you can run a split test between your legacy solution and a next-generation one, do it! Numbers don't like and seeing the impact a new platform would have on your sales and revenue is the most objective criteria.
As technology continues to advance, it is essential for eCommerce businesses to embrace AI-powered product discovery to stay ahead in the competitive digital landscape and meet the evolving expectations of their customers. Personalized offers, discounts, and promotions based on customer preferences are now the norm -- and AI-first platforms deliver them easily, and with less effort on the backend.
By harnessing the power of true artificial intelligence and machine learning, businesses can unlock new possibilities for their online shopping experiences, significantly increasing customer engagement and driving conversions.
With an AI-first eCommerce search and product discovery platform, you can provide online shoppers with a streamlined and intuitive search experience that increases customer loyalty and boosts sales and revenue. These solutions possess an unmatched understanding of user intent and include smart search features such as auto-suggestions, spell-check, and semantic understanding to help customers find what they're looking for quickly and easily. By reducing search effort and presenting relevant results, you can improve customer satisfaction, engagement, and most importantly -- sales.
