Salesforce Einstein AI - Artificial Intelligence For CRMs

Salesforce Einstein AI - Artificial Intelligence For CRMs

Salesforce.com (SFDC) is investing in its already market-leading Customer Relationship Management (CRM) platform by focusing on data analytics and artificial intelligence. In 2016, Salesforce became one of the first vendors to make AI-based capabilities available to its customers when it introduced Einstein Analytics.  Since then, SFDC has expanded the available features of Einstein Analytics and improved the integration of those features into everyday work scenarios for users across marketing, sales and customer service.
 
The Einstein platform includes a variety of analytics and AI features, including tools for both end-users and analysts/developers. While it includes a number of pre-built dashboards and ready-made analytics, Einstein really endeavors to inject AI directly into user's workflows. Some of the integrated technologies include social data capture, Einstein language processing, machine learning, predictive analytics and smart chatbots, all of which work together to provide to a more productive end-user experience. Einstein is a great example of making AI more user-friendly and useful.
 

Below is a summary of key benefits of some of the core Einstein products (from Salesforce.com):

 

Einstein Sales Marketing Cloud

  • Give your marketers the tools to make every customer journey and interaction effective

  • ​Know your customers better with Einstein prediction builder insights drawn from their marketing engagements, brand interactions, and even images and conversations across social

  • Create personalized messages and content based on customer preferences and intent

  • Engage more effectively with suggestions on when to reach out to each customer, on which channels, and for the products that resonate the most

 

Einstein for Sales Cloud: Close more deals – Einstein does the busywork, you focus on selling

  • Prioritize next best steps by leveraging sales history to generate scores that identify which leads and opportunities are likely to convert

  • Analyze your opportunity engagement activity and external news to ensure reps never miss a critical business development

  • Save on data entry time by automatically syncing email and calendar to SF, and automating the creation of new contacts

  • Uncover historical pipeline information, business trends, whitespace, and other advanced analytics to drive sales

  • Use automated machine learning to predict your forecast and share intuitive insights behind the prediction

 

Einstein AI Salesforce for Service Cloud

  • Turn your customer service organization into a growth engine

  • ​Instantly help customers find answers and eliminate hold time with custom chatbots on digital channels
  • Assist agents by using predicted case fields, automatic triage, and routing so they can spend more time with customers

  • Improve customer experience with intelligent conversation suggestions and in-context content recommendations

  • Gain visibility with prebuilt dashboards, and see case volumes, worker activity, chatbot performance, etc.

 
All of this and more, on any device!
 
Of course, any solutions based primarily on user-captured data has the potential to run into the age-old rule of 'garbage in, garbage out'. It is important to have a solid plan for ensuring that the quality of your CRM data is high, and that it remains that way over time. Fortunately, Salesforce and their AI make great tools for maintaining data quality, and there a variety of other services and solutions that can also be utilized to facilitate validating, cleansing, pruning and merging your data.
 
Of course, BDO Digital has a lot of experience helping clients clarify needs, identify and envision solutions, then implement, adopt and embrace those solutions, to deliver maximum value. We are truly excited by the potential of Salesforce's Einstein AI capabilities to transform our clients' business processes, and to fuel their future growth and success!

Updated from originally published article: July 28, 2020