GETTING STARTED
SearchAssist Overview
SearchAssist Introduction
Onboarding SearchAssist
Build your first App
Glossary
Release Notes
What's new in SearchAssist
Previous Versions

CONCEPTS
Managing Sources
Introduction
Files
Web Pages
FAQs
Structured Data 
Connectors
Introduction to Connectors
Azure Storage Connector
Confluence Cloud Connector
Confluence Server Connector
Custom Connector
DotCMS Connector
Dropbox Connector
Google Drive Connector
Oracle Knowledge Connector
Salesforce Connector
ServiceNow Connector
SharePoint Connector
Zendesk Connector
RACL
Virtual Assistants
Managing Indices
Introduction
Index Fields
Traits
Workbench
Introduction to Workbench
Field Mapping
Entity Extraction
Traits Extraction
Keyword Extraction
Exclude Document
Semantic Meaning
Snippet Extraction
Custom LLM Prompts
Index Settings
Index Languages
Managing Chunks
Chunk Browser
Managing Relevance
Introduction
Weights
Highlighting
Presentable
Synonyms
Stop Words
Search Relevance
Spell Correction
Prefix Search
Custom Configurations
Personalizing Results
Introduction
Answer Snippets
Introduction
Extractive Model
Generative Model
Enabling Both Models
Simulation and Testing
Debugging
Best Practices and Points to Remember
Troubleshooting Answers
Answer Snippets Support Across Content Sources
Result Ranking
Facets
Business Rules
Introduction
Contextual Rules
NLP Rules
Engagement
Small Talk
Bot Actions
Designing Search Experience
Introduction
Search Interface
Result Templates
Testing
Preview and Test
Debug Tool
Running Experiments
Introduction
Experiments
Analyzing Search Performance
Overview
Dashboard
User Engagement
Search Insights
Result Insights
Answer Insights

ADMINISTRATION
General Settings
Credentials
Channels
Team
Collaboration
Integrations
OpenAI Integration
Azure OpenAI Integration
Custom Integration
Billing and Usage
Plan Details
Usage Logs
Order and Invoices
Smart Hibernation

SearchAssist APIs
API Introduction
API List

SearchAssist SDK

HOW TOs
Use Custom Fields to Filter Search Results and Answers
Add Custom Metadata to Ingested Content
Write Painless Scripts
Configure Business Rules for Generative Answers

Search for E-commerce and Retail

Having a good e-commerce search experience for your business enables your customers to quickly discover more relevant products thereby increasing the conversion rate on your website. With SearchAssist you could build a solid search experience for your customers that offers personalized recommendations and increase customer engagement in your Website

Features

Facets

Makes it easier for your customers to filter or narrow down their product search using categories and sub-categories. Offer site admin to easily configure the product facets and customize them as per the shopping domain. SearchAssist automatically creates facet categories and subcategories based on the indexed data.

Contextual Search

SearchAssist uses the context of the page, past product searches, and visitor demographic, to bring the most relevant results. Whether they are looking for a specific product of a brand or a price range, or if they are filtering a subcategory within a chosen category, SearchAssist makes it super easy for you to provide contextual results.

Recommendations

Provide contextual personalized search results that are tailor-made for your shoppers. Analyze the user profile, search pattern, and search history to predict and provide personalized or contextual recommendations, proactively.

Fine Tune Relevance

Improve the relevancy of the results by tuning the search results. SearchAssist lets you easily adjust the relevancy score of products based on various parameters like click-through rates and popularity or boost the ranking.

Experiments

SearchAssist provides you with the option to run experiments between your different search experiences among your customers to test the effectiveness of the search experience and make incremental changes as required to provide the best performing option 

Challenges and Limitations of Conventional Search

The following are the key challenges and limitations faced by businesses in implementing traditional search in their eCommerce channels namely websites or mobile apps:

  • Maintaining dedicated resources in the non-core areas of Search and Conversational technologies
  • Reactive and passive user engagement limited to information link pointing and snippets 
  • Customizing  search experiences 
  • Analyzing performance and Experimentation

SearchAssist Solutions

SearchAssist addresses each of the aforementioned challenges with the following key features:  

  • a Platform as a Service (PaaS) approach to subscribe, configure and use to streamline search costs effectively
  • proactive user engagement transforming traditional eCommerce into a Conversational commerce experience presenting both information and call-to-actions. 
  • designing custom search experiences and personalizing results
  • presenting insights on user engagement, queries, results for feedback, and defining experiments. 

Best Practice Recommendations

In the context of eCommerce, most of the features of SearchAssist can be applied to achieve the best outcomes. The following  pre-requisites and best practices are recommended to help you maximize the benefits of a SearchAssistant deployment:  

  • Maintaining updated product catalogs in structured data files like JSON, or CSV 
  • Maintaining product FAQs in SearchAssist mandated format
  • Having clear localization and marketing promotional offer requirements 
  • Having product image gallery and URLs ready for each product

Practical Guidelines in the eCommerce context 

Consider an example where an eCommerce business that sells smartphones decides to deploy Kore.ai’s SearchAssistant onto its channels namely website or mobile app. Assume they have added the following sources of the content:

  • the product catalog in structured data either in CSV or JSON formats
  • the associated FAQs are all reviewed and approved, 
  • user manuals if applicable etc. 
  • SearchAssistant is linked to a live retail Support virtual assistant called ShopAssistant. 

SearchAssist by default indexes the ingested content with the default index configuration. Additionally, you can create custom index configurations, personalize results, design UIs, and customize the search experience with SearchAssist. 

The following guides give practical pointers on how you can utilize each feature to deliver an advanced search experience to your users and meet your business objectives: 

  • Ingesting Data
  • Managing Idexing Sequence
  • Managing Relevance 
  • Personalizing Results 
  • Designing Search experiences
  • Experimenting with Variants
  • Analyzing Search Performance

 

Search for E-commerce and Retail

Having a good e-commerce search experience for your business enables your customers to quickly discover more relevant products thereby increasing the conversion rate on your website. With SearchAssist you could build a solid search experience for your customers that offers personalized recommendations and increase customer engagement in your Website

Features

Facets

Makes it easier for your customers to filter or narrow down their product search using categories and sub-categories. Offer site admin to easily configure the product facets and customize them as per the shopping domain. SearchAssist automatically creates facet categories and subcategories based on the indexed data.

Contextual Search

SearchAssist uses the context of the page, past product searches, and visitor demographic, to bring the most relevant results. Whether they are looking for a specific product of a brand or a price range, or if they are filtering a subcategory within a chosen category, SearchAssist makes it super easy for you to provide contextual results.

Recommendations

Provide contextual personalized search results that are tailor-made for your shoppers. Analyze the user profile, search pattern, and search history to predict and provide personalized or contextual recommendations, proactively.

Fine Tune Relevance

Improve the relevancy of the results by tuning the search results. SearchAssist lets you easily adjust the relevancy score of products based on various parameters like click-through rates and popularity or boost the ranking.

Experiments

SearchAssist provides you with the option to run experiments between your different search experiences among your customers to test the effectiveness of the search experience and make incremental changes as required to provide the best performing option 

Challenges and Limitations of Conventional Search

The following are the key challenges and limitations faced by businesses in implementing traditional search in their eCommerce channels namely websites or mobile apps:

  • Maintaining dedicated resources in the non-core areas of Search and Conversational technologies
  • Reactive and passive user engagement limited to information link pointing and snippets 
  • Customizing  search experiences 
  • Analyzing performance and Experimentation

SearchAssist Solutions

SearchAssist addresses each of the aforementioned challenges with the following key features:  

  • a Platform as a Service (PaaS) approach to subscribe, configure and use to streamline search costs effectively
  • proactive user engagement transforming traditional eCommerce into a Conversational commerce experience presenting both information and call-to-actions. 
  • designing custom search experiences and personalizing results
  • presenting insights on user engagement, queries, results for feedback, and defining experiments. 

Best Practice Recommendations

In the context of eCommerce, most of the features of SearchAssist can be applied to achieve the best outcomes. The following  pre-requisites and best practices are recommended to help you maximize the benefits of a SearchAssistant deployment:  

  • Maintaining updated product catalogs in structured data files like JSON, or CSV 
  • Maintaining product FAQs in SearchAssist mandated format
  • Having clear localization and marketing promotional offer requirements 
  • Having product image gallery and URLs ready for each product

Practical Guidelines in the eCommerce context 

Consider an example where an eCommerce business that sells smartphones decides to deploy Kore.ai’s SearchAssistant onto its channels namely website or mobile app. Assume they have added the following sources of the content:

  • the product catalog in structured data either in CSV or JSON formats
  • the associated FAQs are all reviewed and approved, 
  • user manuals if applicable etc. 
  • SearchAssistant is linked to a live retail Support virtual assistant called ShopAssistant. 

SearchAssist by default indexes the ingested content with the default index configuration. Additionally, you can create custom index configurations, personalize results, design UIs, and customize the search experience with SearchAssist. 

The following guides give practical pointers on how you can utilize each feature to deliver an advanced search experience to your users and meet your business objectives: 

  • Ingesting Data
  • Managing Idexing Sequence
  • Managing Relevance 
  • Personalizing Results 
  • Designing Search experiences
  • Experimenting with Variants
  • Analyzing Search Performance