Search is undoubtedly one of the first elements by which the users start interacting with an e-commerce store. It plays a key role in the product discovery and helps buyers to navigate to their desired products or services. In the last few years, we have witnessed a rapid penetration of artificial intelligence in the search engine technologies. The AI-based search engines leverage technologies like Natural Language Processing, Machine Learning, and Deep Learning to get inside the mind of the users. The search mechanisms aren’t now limited to the basic keyword matching and rigid algorithms to display results. Advanced AI-based search engines can understand user intent and deliver results that truly resonate with the user.
Recently, the tech giant Google has introduced an AI-powered search platform – Vertex AI Search. This search platform seems to have potential to bring big strides in the AI-based search technologies. While Vertex AI Search offers search, recommendations, and industry-specific offerings, in this article we will primarily focus on Generic Search and Vertex AI search for retail e-commerce stores.
The search function of an e-commerce should be highly robust so that users can easily find products they are looking for. Enhanced product discovery leads to higher conversion rate. Let’s begin by understanding the basics.
What is Google’s Vertex AI Search?
Google’s Vertex AI search is a Search-as-a-Service for retail e-commerce stores. It runs on the same global platform as Google itself. It is a part of the broader Product Discovery tools in Google Cloud and would typically be deployed alongside Autocomplete and Recommendations AI to create a fully engaged product discovery experience. It is capable of going further to include fully integrated image search, voice search, and conversational experiences.
It ultimately means, with Google’s Vertex AI search, the online e-commerce retailers will be able to offer Google-quality search functionality on their own online stores. The term “Google” has been used interchangeably with “search” for more than a decade, and no other tech giant has as much experience and historical search data as Google. Despite being a recent product, Vertex AI Search for Commerce is based on the decades of research and foundations that enable Google.com to process billions of search requests daily.
For a better understanding of differences between Vertex AI Search and other search mechanisms, let’s begin by reviewing what makes e-commerce search so difficult:
• Difficult to understand user intent:
Before attempting to display pertinent products, search engines must comprehend the meaning of a query. It is particularly crucial for tail queries like “high waisted ripped boyfriend jeans,”.
• Difficult to rank relevant products:
Search engines must choose which relevant products to display first, particularly if some are projected to generate more cash than others. This is especially crucial for head queries like “women’s pants.”
• Difficult to personalize and showcase the right products to the right buyers:
Every customer is unique and follows a different way of navigation on the e-commerce store before finding the right products. It is impossible to design a journey for every customer, so AI tools must make us more efficient and fill in the journey gaps as created by individuals.
Google’s Vertex AI search leverages smart search technologies for better product discovery for customers. The advanced models of the platform adjust dynamically as per the customer behaviors and search queries in real-time. It ensures that the product discovery solution evolves alongside your catalog as it changes.
Features of Vertex AI Search:
1. Advanced AI:
The e-commerce retail owners can leverage Google’s expertise in AI for understanding and personalising every advanced query. It will result in better search, browse results along with recommendations from even the broadest queries. Furthermore, you can match product attributes with website content for fast, relevant product discovery with semantic and conversational search.
2. Optimized Results:
Vertex AI leverage user interaction and ranking models to meet specific business requirements. There are features like customize recommendations using page-level optimization, buy-it-again and revenue optimization capabilities for higher engagement, revenue, and conversations. You can apply various business rules to fine-tune what customers see, diversify product displays, and filter by product availability, custom tags, etc.
3. Fully Managed:
You don’t need to preprocess data, train or hyper-tune machine learning models, load balance or manually provision your infrastructure to handle unpredictable traffic spikes. The Vertex AI will do it all for you automatically.
4. Security, Privacy, and Compliance:
In the e-commerce world, the privacy of data is highly important. Vertex AI offers various security and privacy protocols that ensure your data is isolated with strong access controls. It provides support for compliance with the General Data Protection Regulation (GDPR).
Use Cases of Vertex AI Search For Retail E-commerce Stores:
Vertex AI Search for retail is an industry-specific offering curated to meet the requirements of retail e-commerce stores. Its capabilities of semantic search, personalization, extensibility, and availability of connectors with other Google services immensely benefit the online retailers. These capabilities improve search experience, drive engagement, and improve conversions. It also supports multiple languages. There is a pre-defined retail schema in the Vertex AI which can be extended as per business needs.
4. Security, Privacy, and Compliance:
In the e-commerce world, the privacy of data is highly important. Vertex AI offers various security and privacy protocols that ensure your data is isolated with strong access controls. It provides support for compliance with the General Data Protection Regulation (GDPR).
1. Product Ingestion:
You can ingest products into the Vertex AI platform through Merchant Center, BigQuery, Cloud Storage and inline via API. The data quality page in the search console provides an overview of the product data ingested quality.
2. Search Configuration:
You can configure search behavior by serving controls. The boost/bury control allows merchandisers to push certain products up or down the search results orders. They can redirect customers to specific pages based on the search term. For instance, when customers look for policies, etc., they may be sent to the FAQ page. Merchandisers can set up synonyms, disregard, and replace terms with linguistic controls.
3. User Events:
For the improvement in overall search performance, there must be capturing of user events. There is real-time recording of user events like search, product details page view, add to cart, purchase complete, and others. These events provide real-time understanding of overall search trends and personalizing search results. User events also power autocomplete and dynamic faceting features.
4. Dynamic Faceting:
Faceting is a key part of the Vertex AI search and it lets users to filter search results. Generally, in traditional search engines, there is the static configuration of facets or passing them in the search request. The application decides what facets need to be displayed and in what order. Users might not interact with the irrelevant aspects that are presented to them as a result. Vertex AI Search for retail uses dynamic faceting, which incorporates facets into the result based on user behavior and clicks on facets. Additionally, facets and facet values are dynamically determined. This raises the aspects’ rate of engagement. Merchandisers can also remove facets, ignore, merge, or replace facets values using facet controls.
5. Measuring Search Performance:
With search analytics, you can understand the performance of the search engine. An e-commerce retail will definitely want to gauge the performance of the search engine in terms of click-through rates, conversion rates, and other metrics.
Vertex AI search for retail captures user events to generate analytics. It generates an attribute token in each search response which becomes part of subsequent user events. This helps attributing user actions to a particular search and aids in improving search re-ranking and measuring search performance.
There is an analytics dashboard in the Vertex AI Search that lets you view various search metrics. You can easily see the number of searches performed on your e-commerce store, how many of them resulted in a click-through and other metrics.
Wrapping Up:
In this article, we have gone through all the major aspects of the Vertex AI Search powered by Google. It is a relatively newer search platform, and its performance in the market is still in focus.
If you want to implement Google powered search functionality in your e-commerce store, look no further than us. Being a top-notch e-commerce development company, we have expertise in implementing advanced search functionalities in the online e-commerce stores. Let us know your requirements.
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