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Table of contents
1.
Introduction
2.
Capabilities of Recommendation AI
3.
Retail API 
4.
Uses of Retail API
5.
Implementation of Retail API with Google Tools
6.
Implementation of Retail API without additional Google Tools
7.
Frequently Asked Questions
7.1.
What is Google Scheduler Service?
7.2.
What is Google App Engine?
7.3.
How well do you know to Google Cloud APIs?
8.
Conclusion
Last Updated: Mar 27, 2024

Recommendations AI

Author Ayush Mishra
1 upvote
Leveraging ChatGPT - GenAI as a Microsoft Data Expert
Speaker
Prerita Agarwal
Data Specialist @
23 Jul, 2024 @ 01:30 PM

Introduction

AI is the simulation of human intelligence in devices designed to behave and think like humans. The phrase can also refer to any machine that demonstrates characteristics of the human mind, like learning and problem-solving.

In this blog, we will discuss Recommendations AI in deep detail. The series of Recommendations AI consists of three parts. This is the introductory part; for the other two parts, you may refer to Basics of Recommendations AI and Advanced Concepts of Recommendations AI. Let’s start going!

Recommendation AI

Capabilities of Recommendation AI

Recommendation AI capabilities are:-

🦾 Custom Models: Each model is trained specifically for your data based on sequence-based ML models and transformers.

🦾 Personalized Result: These are produced as a result of suggestions based on user behavior and activities like views, clicks, in-store purchases, and online activity.

🦾 Real-time predictions: Each Suggestion served considers previous user activity such as click, view, and purchase events, resulting in real-time suggestions.

🦾 Automatic Model Training and Tuning: Every day, model retraining ensures that all models accurately capture user behavior.

🦾 Optimization Objectives: You can more precisely optimize for your business goal with the help of conversion rate, click-through rate, and revenue optimization goals.

🦾 Omnichannel Suggestions: With the API model, you can personalize your entire shopper journey, from website suggestions to suggestions on mobile apps, personalized email suggestions, store kiosks, or call center applications.

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Retail API 

The Retail API ingests user event and catalog data to serve predictions or search results on your site when you use AI or Retail Search.

It uses the same data for AI and Retail Search, so you don't have to ingest the same data twice if you use both. Its integration time is typically in the order of weeks. Regardless of whether you use other Google tools, you can use the Retail API to get personalized results for your website.

Uses of Retail API

Retail requires two sets of data in order to build ML models for searches:

🚀 Product Catalog: Information on the items that are highlighted for customers. This includes the name of the product, its description, whether it is in stock, and cost.

🚀 User events: Information on the goods that are being suggested to customers. This includes the name of the item, its description, whether it is in stock, and cost.

Implementation of Retail API with Google Tools

The steps to implement the Retail API with Google tools are as follows:-

1️⃣  Create a project in Google Cloud.

2️⃣ Utilizing Merchant Center, import your product catalog.

3️⃣ Set up Tag Manager so that user events are recorded.

4️⃣ Importing previous user events.

5️⃣ Create your serving model, controls, and configuration.

6️⃣ Give the model tuning time.

7️⃣ View a sample of your serving arrangement.

8️⃣ Establish an A/B test. It is an optional step.

9️⃣ Analyze the configuration you have.

Implementation of Retail API without additional Google Tools

The steps to implement the Retail API without additional Google tools are as follows:-

1️⃣ Create a project in Google Cloud.

2️⃣ Import your product catalog.

3️⃣ Capture user events.

4️⃣ Importing previous user events.

5️⃣ Create your serving model, controls, and configuration.

6️⃣ Invest time in training.

7️⃣ View a sample of your serving arrangement.

8️⃣ Establish an A/B test. It is an optional step.

9️⃣ Analyze the configuration you have.

Frequently Asked Questions

What is Google Scheduler Service?

Almost any work, including batch jobs, big data activities, cloud infrastructure operations, and more, can be scheduled using Google Scheduler Service.

What is Google App Engine?

Google App Engine provides scalable services for companies and web application developers as a part of Platform as a Service. The developers can use this to create and deploy a fully managed platform and scale it as necessary.

How well do you know to Google Cloud APIs?

The main purpose of APIs is to automate the workflow using the language of your choice. APIs make it possible to communicate with different Google services and make it easier for them to integrate with other services. It can also be described as a gateway that gives consumers access to different software services and direct and indirect cloud infrastructure.

Conclusion

Congratulations on finishing the blog! We have studied Recommendation AI. We further looked at the Retail API, its implementation, and its use of retail API.

We hope this blog has helped you enhance your knowledge regarding Recommendation AI, and if you want to learn more, then you can check articles on:

 

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