Fast and resilient digital customer service is standard, but Einstein Search Answers is emerging as the gold standard. Einstein Search Answers combines Einstein Search and Salesforce AI Research. Salesforce Einstein allows users to add intelligent capabilities to their Salesforce applications. The tool incorporates artificial intelligence (AI) and machine learning (ML) technologies, including predictive analytics, natural language processing, and automation capabilities. Users can automate routine tasks, improve decision-making, and personalize customer interactions.
What is Einstein Search?
Einstein Search Salesforce uses artificial intelligence and machine learning to make search results fast, accurate and relevant. It leverages the power of simplicity to make CRM search easy, hassle-free, fast, powerful, and effective.
The crux of the problem related to CRM search is the diverse user base with various goals and siloed data. Einstein Search comes with advanced machine learning techniques and innovative data mining that takes cognisance of customizations, delivering personalized results for every user.
Einstein search uses natural language processing (NLP) to allow users to seek information using natural language instead of code or even keywords. Einstein understands the user intent behind search queries and provides intelligent search suggestions and results.
Einstein search bar also throws up customizable actions within the search results. For example, in manual mode, the user search for a contact, clicks its record and then attaches the contact to an opportunity. Now, the user can perform all these actions through the enhanced Einstein Search bar. Einstein Search delivers a 50% reduction in clicks and page loads for the most frequently-used tasks.
Einstein Search Salesforce search across multiple objects and data sources within Salesforce. The search extends to knowledge articles, cases, leads, and contacts.
Einstein’s intelligent search capabilities improve the accuracy of predictive search results and suggestions. It also allows users to work up to 50% faster.
What is Salesforce AI Research?
Salesforce AI Research, also known as Salesforce Research, offers built-in intelligence that empowers Salesforce users to leverage the power of AI. The AI tool offers deep insights into customers based on past interactions and relevant environmental cues. Combining AI with mobile makes such real-time contextual information available at the marketer’s fingertips, improving their effectiveness. Businesses can use such insights to prioritize leads, strengthen customer relationships, solve cases, and drive better campaigns. Companies using Salesforce AI have experienced a 20% increase in win rate.
Some recent Salesforce AI research features include:
- AI-powered language translation allows Salesforce users to translate text in real time across multiple languages.
- Image recognition allows users to extract information from images. Users can identify products or detect defects through images without having to type text.
- Voice recognition capabilities transcribe and analyze customer phone calls and other voice recordings.
- Predictive analytics capabilities. Marketers can leverage these capabilities to predict customer behaviour and identify potential sales opportunities.
- Natural Language Processing (NLP). Salesforce can apply NLP easily to extract meaning from customer inquiries. They may, for instance, identify the intent behind a customer’s question, such as if the customer wants to clarify a position before raising a dispute or wants to know how to use the product.
- Sentiment analysis, which makes explicit customer emotions. This feature analyzes feedback from text or voice to detect emotion.
- Recommendation systems that analyze customer-related data to allow marketers to offer personalised products or content recommendations.
The value addition offered by Einstein Search Answers
Salesforce Einstein search answers, the combination of Einstein search and Salesforce AI research, take search within Salesforce to a new level. It enables users to search for relevant answers from a vast trove of structured and unstructured data.
Einstein interactive search answers offer conversational and natural language search capabilities within the Salesforce platform. Users get a more streamlined and efficient way to search for information. They get the answers they seek faster.
The tool provides contextual information and can automate the best course of action. Search answers become more accurate, contextual, and personalized. Users, especially customer support agents and marketers, get work done faster. They get the answers and information they need with the option to automate the best course of action. Using Interactive Einstein Search Answers with Service Cloud Einstein makes customer service effortless.
How users use Einstein search answers to resolve cases
There are several ways to resolve cases quickly using Einstein search answers:
- Use the Einstein search bar to find relevant knowledge articles, cases, and other information fast.
- Use the Einstein search assistant to get suggested answers to customer inquiries.
- Utilize Einstein case classification to categorize and route cases to the appropriate agent. The automated classification process assigns based on the topic and urgency.
- Use the Einstein case recommendations to provide agents with suggested next steps for resolving cases.
- Leverage Einstein case deflection to redirect simple customer inquiries to self-service resources.
- Use the Einstein case insights to offer agents real-time data and analytics on case history and customer interactions.
- Use the Einstein language understanding to parse customer inquiries and extract relevant information.
Key capabilities of Einstein Search Answers
Einstein search answers empower Salesforce users with the following capabilities:
- Intelligent case classification
Einstein AI categorizes and prioritizes incoming case requests based on the context. Such categorizations makes it easier for support teams to handle and resolve the core issue.
Einstein AI uses natural language processing and machine learning algorithms to analyze the case data and make accurate categorizations. For instance, the AI algorithm classifies customer service cases into billing enquiries, technical issues, account management, or product feedback.
The algorithm also prioritizes cases based on urgency, impact, and customer status.
- Automation capabilities
Integrated automation tools reinforce intelligent case classification and help users resolve cases quickly using Einstein search answers. The algorithm:
- Detects common issues and resolves them automatically. In traditional automation, smart bots answer common customer questions. Support agents get more free time to address complex cases. Einstein AI helps agents handle complex cases by providing contextual replies and recommendations.
- Routes cases to the appropriate team or agent based on case type, category, and priority.
- Provides real-time insights into case trends and patterns. Consider a spurt in cases related to a specific technical issue caused by an outage. The Einstein AI tool offers agents contextual information that saves them from seeking an answer in the first place. The agent may automate the response. Such insights help support teams resolve customer issues proactively.
- Highlighting relevant results
Einstein Search Answers provides users with relevant search results. The tool searches multiple data sources, including Salesforce records, internal knowledge depositories, and external sources.
Einstein Search Results allow support agents to extract relevant information from the knowledge base. The instant results enable them to take immediate action to resolve the issue. Users no longer have to click on lengthy articles and find suitable solutions by themselves. The backend AI tool extracts specific answers for specific queries. The AI understands the user intent and identifies its most relevant response.
- Actionable results
Einstein Search Answers returns very concise answers, usually three lines or less. Agents may copy-paste the solution and/or the relevant internal links to their clipboard and share it without leaving the page. Without the new functionality, agents had to open the record page and copy an article’s URL and section. This time-consuming action impeded productivity and slowed down the workflow. It also threw up possibilities of user-generated errors.
Consider a search phrase “How do I add an email signature?” or a phrase “login issue with Salesforce iOS.” When users search such queries, Einstein search answers throw up an answer card that displays the most relevant answer. The user can copy and share the answer or the source link without hassles. They also can delve into the knowledge article that contains the answer and get more context.
- Improved search method
Einstein Search answers also mark an improvement to the search method. Previously, the search methods were keyword based. Users typed a word or phrase into a search bar, clicked “enter,” and saw the keyed-in word or phrase highlighted in the search results.
With Einstein search answers, users can phrase their questions in natural language. With traditional search, they had to specify keywords. Users need not take the trouble of understanding domain terms referenced in knowledge articles.
- Question answer capabilities
Einstein Search Answers also enables question-answering capability. Users now receive specific answers to the phrase or question at the top, enhancing the search process. When users ask questions, the tool generates the response as specific answers to such questions.
Natural language processing (NLP) and machine learning algorithms decipher the context and intent behind the user’s question. The tool offers quick answers in FAQ mode without user intervention. It ranks the most relevant results and updates the search results over time to make them more accurate and relevant.
Integration with Salesforce workflows and processes enables users to search for answers without interrupting their work.
How Einstein search answers works
Traditional methods rely on lexical search and look for the exact term or keyword match. Semantic search, powered by machine learning algorithms, deciphers the query and the documents better to identify the correct answer for the user. The algorithm also ensures that the answer is relevant and actionable.
Einstein search answers also structurally deviate from traditional search methods.
Einstein search answers:
- Divide long knowledge articles into smaller semantically coherent passages, and search for shorter texts. This enables the generation of precise answers for queries with user intent.
- Leverage pre-trained language models to enhance the lexical search with deep semantic understanding. The application of matured models enables the construction of a richer contextual meaning of the analyzed text.
- Applying BERT-like pre-trained transformer-based architecture to embed queries and passages into the same latent space and group semantically similar pieces of text.
Consider a hotel-booking site. When the user queries “how to add one more person to the reservation?” the Einstein Search Answers system searches for the content having relevant keywords from the org and extracts all the potential answers. The backend applies the machine learning algorithm to compare the extracted texts with the query. Unlike conventional search, Einstein search answers go beyond the content title and make a comparison at the semantic level. Comparing only the content may not yield the relevant answers since the title may be just “reservation policies” and may not relate to the user’s specific query. Even the keywords associated with the content may not indicate that the article contains the answer to the user’s query.
The algorithm engine may ask users to enter more information, such as resolution reports of cases, to make answers more relevant and contextual. For instance, in the hotel booking example above, the application may ask the user about the information already provided to the customer to ensure accuracy and relevance.
How Einstein Search answers rank answers
Einstein’s AI models learn complex relationships between articles and provide the most relevant articles with the top results.
The AI models analyze the following factors to rank search results:
- The article fields with the most relevant matches for the query terms.
- The article field metadata, including the number of views, votes, references, and freshness of the article.
Agents have the option to customize article details. They can view all articles in the search result, identify their origin, and identify whether an article is relevant to their query. If no article matches their query, they may create a new article to bridge the gap. Agents can attach an article to the case from the search result list. If there are no articles agents can use to solve the case, users can select New Article and create an article to fill the knowledge gap.
Multi-language search capabilities
Several enterprises now have geographically dispersed operations. The knowledge base of such companies reflects diversity. Service agents can get knowledge article results in different languages.
When an agent enters text in the knowledge search bar, Einstein search answers look for articles that match the keywords and apply synonyms. The algorithm matches the agent’s profile language and the knowledge base default language. For instance, if an agent works in Paris, the agent’s default language will be French, and the knowledge base default language will be English. If the agent types in a French phrase at the search bar, the Einstein Search returns an article in French and another in English containing the keywords.
Agents may also search for language-neutral terms, such as product names. Users can change and add languages easily.
Salesforce Einstein Search answers are available in pilot mode for select users in Lightning Experience, and all versions of the Salesforce mobile app in Essentials, Professional, Enterprise, Performance, and unlimited editions with Lightning Knowledge and Einstein Search for Knowledge enabled.