Salesforce Einstein: use cases, benefits, and challenges

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Salesforce.com has finally announced Einstein during Dreamforce ’16, after more than 1 year of rumors. For readers who have never heard about Einstein, it is the new artificial intelligence (AI) built into the core of the Salesforce Platform. It delivers advanced AI capabilities to sales, service, and marketing and enables anyone to use clicks or code to build AI-powered apps that get smarter with every interaction.

Do you think it is science-fiction? Well, the first time I heard about AI was in Terminator (great movie) and I didn’t believe it would ever have been possible to bridge the gap between our technology and the robot played by Arnold. Actually, I was wrong and even if we do not have our personal human-robot yet, there are a lot of features, based on basic Machine Learning and AI algorithms, that we use daily on our devices (i.e. Siri on apple devices). In the wake of these events and of a 16,9$ bln expected market for AI in 2019, Mark Benioff shapes Einstein, the first CRM AI module.

It is still at the beginning, but what are the use cases, the benefits and the challenges of this cutting-edge engine?

Use cases

Sales Cloud

AI will enable sales reps to increase productivity thanks to predictive capabilities across everything they do. They will have more time to focus on their prospects and to create opportunities. Einstein sends automatic reminder tasks (recommended Follow-Ups) to the user in order to follow back up with customers who haven’t responded to emails. Sales reps never have to worry about losing touch with important prospects.

Service Cloud

A new predictive customer service will improve the customer satisfaction reducing the time to successfully close a case.

  • Case classification algorithm: based on user histories and trends, a case can be routed with instructions to agents on how to address the issue
  • Recommended responses: based on case context and history, Salesforce provides recommended answers, ensuring customers can quickly get the right way to their questions
  • Predictive close time: it helps your support team route, escalate and prioritize work by predicting the time needed to resolve an issue

Marketing and Analytics Cloud

Thanks to analytics tools that predict the optimal timing, channel, content and audience for any marketing message, marketers can leverage:

  • Predictive scoring: gauge when a customer will engage  with an email, unsubscribe from an email list, or make a web purchase
  • Predictive audiences: cluster customers based on Predictive Scoring in order to drive customers to the next level of engagement or conversion
  • Automated send-time optimization: maximize email marketing ROI by automatically delivering their messages exactly when subscribers are most likely to engage
  • Language insights: detect and classify what language a post was authored in, giving marketers the ability to harness all conversations about a particular topic

In addition, Analytics Cloud Einstein will help users answer these core questions: what happened, why it happened, what will happen, and what I should do thanks to these exciting features:

  • Intelligent wave apps: it will uncover future patterns for every business process, pointing out which key findings are important to examine, why they are significant and what to do next
  • Smart data discovery: it will help users find and explain insights from millions of data combinations
  • Automated storytelling: it will automate and prioritize the next insight users need to know with smart charts and widgets, as well as narrate it with natural language support

Community Cloud

Customer experience has been enhanced thanks to:

  • Topics recommendation: suggested posts, articles, and topic pages to the customer
  • Automated service escalation: Automatic case creation for customer posts that don’t receive a timely response or that contain specific words (i.e. “broken”)

Commerce Cloud

With the Commerce Cloud platform, Salesforce can provide shopping recommendations, relevant products, and customized search:

  • Product Recommendations: Unique, personalized recommendations throughout the shopper journey, based on previous interactions with the e-commerce or the shop
  • Predictive Email: tailored content with products of interest for individual emails

Benefits

Although Einstein is still in a start-up phase, we can already guess the benefits:

  • No need to hire Data Scientist: a homemade AI software requires an equip of data scientist. They are professional figures difficult to find on the market and very expensive. Einstein itself will be the Data Scientist
  • No need to design your own predictive models: Einstein will do it for you, providing the model that most fits your needs
  • Your CRM will be increasingly accurate: Data is the main fuel for the AI. It means your CRM will learn and will be more accurate every time it receives new Data
  • It will simplify your daily work: it will not perform the work on your behalf, but it will propose possible solutions and alternatives, speeding up your daily work. It’s like when Google notifies you the total time to go to your job place. It does not really know you are going there, but it predicts based on your daily movements
  • Your customer will be enthusiastic (for consultants): it’s the future! How can’t you customer be enthusiastic?

Challenges

How to be ready for Einstein?

  • Understand if your business is right for Einstein. The AI tool requires a large amount of data to be effective and if you can’t collect them you don’t probably need it
  • Identify the channels at your disposal to gather data
  • Consider to use IoT to have additional channels
  • Users provide important data by interacting with in-shore devices (i.e. Proximity sensors). Consider to use them, especially if your business is Retail

References: Trailhead

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