Is Salesforce Einstein Analytics for me ?
Salesforce Einstein Benefits: Eliminates time-consuming busywork such as logging sales activities
Provides information to help prioritize leads and opportunities better
Offers recommendations to help close deals faster
Finds important news and data that affect specified customers
Makes predictions about how sales teams are doing
Salesforce Einstein
Is Einstein any good for me
Google paid $600 million for an AI solution called DeepMind, which beat a human world champion at the board game Go
Twitter paid $150 million for Magic Pony, an image-processing platform
Microsoft paid $200 million for Equivio, a machine learning start-up
Splunk paid $190 million for Caspida, a cybersecurity AI firm
Apple paid $30 million for MapSense, an AI mapping company
Lead scores and their predictive factors are visible in list views,and on detail pages.
Einstein Lead Scoring includes both an operational dashboard and Einstein Analytics dashboard with reports that show you your conversion rates by lead
score and average lead score by lead source. And you can even see the distribution of lead scores among your
converted and lost leads. So it’s easy to see how lead scores are correlating to your bottom line.
Einstein Opportunity Scoring:works a lot like Lead Scoring. Einstein looks at sales teams’ past opportunities and related information to create a predictive model. From that model, Einstein gives each opportunity a score, which is available on opportunity records and list views. And for each opportunity score, Einstein backs up its claim with the top factors that contributed to the score.
You can add the Opportunity Score field to opportunity list views (2). In Lightning Experience, reps simply hover over the score in the list view to see the factors.
In Salesforce Classic, the contributing factors aren’t available from the list views. Instead, reps need to navigate to the opportunity record detail page.
Einstein Opportunity Insights:
After reps decide which deal to work on, in comes Einstein Opportunity Insights, which uses machine learning and sentiment analysis to help sales reps close more deals.
Einstein Opportunity Insights offers smart predictions and follow-ups about different opportunities precisely when they’re needed. The insights are specific to your organization and team, and they appear on the Home page, opportunity records, and in list views.
On an opportunity record, reps can see all insights related to an opportunity. Admins can also customize list views to show insights.
Three Types of Insights:
Deal Predictions—Your reps see predictions based on recent activity and existing opportunity data. For example, whether a deal is more or less likely to close, or if a deal seems unlikely to close in time.
Follow-Up Reminders—Reps get reminders to follow up when a contact hasn’t responded in a while. They also get reminders if there hasn’t been any communication related to an important opportunity for a significant period of time.
Key Moments—Reps are notified at key moments related to a deal, such as when a contact mentions a competitor or is leaving their company.
Einstein Account Insights:
Einstein Account Insights helps your sales team maintain their relationships with customers by keeping the team informed about key business developments that affect customers. Knowing what’s impacting your customers’ companies gives your sales team an edge when deciding whether customers are open to sales and how to proceed. Is the company expanding? Changing executive leadership? Acquiring competitors? Einstein Account Insights provides news articles from reputable sources that give your sales team the complete picture.
Einstein Account Insights also includes newsworthy developments about company expansion.
Improve Sales Predictions
What is one challenge sales managers face when it comes to tracking their sales teams?
Seeing info at one place that shows how sales team is doing.
What Einstein Forecasting do:
A predicted value that shows how much her sales team is likely to sell this month.
(*)How this value relates to other metrics, such as the team’s sales quota or committed deals
(*)A detailed breakdown across teams and sales reps to see where things can be improved.
(*)get predictions about her sales team’s opportunities. A prediction graph shows her team’s past opportunities and forecasts about future performance.can see the top key performance indicators, including:
(*)Einstein Prediction: Einstein’s forecast prediction for your sales team’s deals this month
(*)Einstein Prediction to Quota Gap: The difference between Einstein’s prediction and your current sales quota
(*)Closed to Quota Gap: The difference between your closed deals and current sales quota
“AI doesn’t replace sales teams. It makes them more productive.“
Einstein BOTS
Improve Customer Service Using Artificial Intelligence
Natural language understanding (NLU) refers to systems that handle communication between people and machines.
Natural language processing (NLP) is distinct from NLU and describes a machine’s ability to understand what humans mean when they speak as they naturally would to another human.
Named entity recognition (NER) labels sequences of words and picks out the important things like names, dates, and times. NER involves breaking apart a sentence into segments that a computer can understand and respond to quickly.
Deep learning refers to artificial neural networks being developed between data points in large databases. Just like our human mind connects the dots to give us insights, deep learning uses algorithms to sift through data, draw conclusions, and enhance performance.
By using AI and machine learning—in real time—the following features make everyone in the contact center smarter and more effective.
Einstein Bots automatically resolve top customer issues, collect qualified customer information, and seamlessly hand off the customers to agents, meaning increased case deflection in the contact center and reduced handle times for agents.
Einstein Agent drives agent productivity across the contact center. Through intelligent case routing, automatic triaging, and case field prediction, Einstein Agent significantly accelerates issue resolution and enhances efficiency.
Einstein Discovery helps managers take action with predictive service KPIs. By serving up real-time analysis of drivers that impact KPIs, like churn or CSAT and suggested recommendations and explanations, managers are empowered to make more strategic decisions for their business.You can get data into Einstein Discovery by using Einstein Analytics dataset.
Einstein Vision for Field Service automates image classification to resolve issues faster on-site. Just by taking a picture of the object, Einstein Vision can instantly identify the part, ensuring accuracy for the technician and boosting first-time fix rates.
Einstein Language brings the power of deep learning to developers. They can use pretrained models to classify text by the sentiment as either positive, neutral, or negative, and then be able to classify the underlying intent in a body of text. Put it all together, and you have the ability to process language across unstructured data in any app.
Einstein Language contains two NLP services: Einstein Intent and Einstein Sentiment.
Einstein Intent—The Einstein Intent API categorizes unstructured text into user-defined labels to better understand what users are trying to accomplish. Use this API to analyze text from emails, chats, or web forms to:
Determine which products prospects are interested in, and send customer inquiries to the appropriate sales person.
Route service cases to the correct agents or departments, or provide self-service options.
Understand customer posts to provide personalized self-service in your communities.
Einstein Sentiment—The Einstein Sentiment API classifies text into positive, negative, and neutral classes to understand what the words people use can tell us about how they’re feeling. Use this API to analyze emails, social media, and text from chat to:
Identify the sentiment or emotion in a prospect’s emails to trend a lead or opportunity up or down.
Provide proactive service by helping dissatisfied customers first or extending promotional offers to satisfied customers.
Monitor how people perceive your brand across social media channels, identify brand evangelists, and note customer satisfaction.