What is Salesforce Einstein?

Salesforce Einstein leverages AI technology to augment its CRM capability in the Cloud Computing world. Salesforce Einstein is the result of the foresight of Salesforce which sees AI and cloud to be the frontrunners among the emerging technologies.

What brews in Salesforce AI platform?

It’s a known fact that Salesforce online training is the top CRM service provider in the world. It has not stopped at CRM only and has also deployed marketing automation very successfully. Artificial Intelligence is the hot topic circulating in major scientific newspapers and technical newsletters, recently. Salesforce has used this technology in its Einstein AI product. To make marketing and sales departments aware of the latest views of customers, Salesforce Einstein is leaving no stone unturned. The company has made a few acquisitions like PredictionIO, MetaMind, and RelateIQ and has used the expertise of 175 Data Scientists to create Salesforce Einstein.

Salesforce being crowned with the title of world’s smartest CRM is justified when advanced AI capabilities are brought into the Salesforce Einstein platform.

Go through this introductory video on Salesforce Einstein:

Salesforce Einstein is powered by Deep Learning, predictive analytics, natural language processing, Machine Learning, and smart data discovery. Models of Einstein are customized for each customer. The model learns, self-tunes, and gets prudent with every interaction and data. This intelligence component of Einstein is now embedded into the business context by predicting future behavior, discovering relevant insights, and even automating tasks.

Various Deployments in Salesforce Einstein

Let’s look into where all Salesforce Einstein Analytics training has been deployed.

Sales Cloud Einstein

It helps you sell your products in a smart way by making prudent predictions and recommendations about your products.

Sales can have three levels and most of the Sales companies are focused on level one. Sales teams in this regard follow scripts, and campaigns are broadcast to their prospects without much regard for individualized preferences.

To personalize their sales and marketing efforts, these companies use signals from their buyers. They interact with the customers and use it to develop product blueprints.

Very few belong to the exceptional companies that are focused on predicting the future. They can forecast as to which leads will turn to customers. They can also predict which customer shall become a loyal consumer of the service or products. If however, a prospect is falling out, then they can convince the concerned person to get back on track.

Salesforce is suitable for all these types of companies. For the first level of companies, Einstein AI is a CRM of a one-dimensional system of records. Salesforce Einstein AI provides a system of engagements to the second level of companies. For the third level of companies, the CRM acts as a predictive system of intelligence.

Productivity is increased and predictive capabilities are enhanced across all they do as AI gives teams more intelligence. Sales personnel can forge a lasting relationship with their clients through this.

Predictions and alerts let you know how your opportunities are trending and whether your forecasted deals are likely to close. These sorts of predictive analytics are actually built on AI. Receive recommendations that have the optimal chance of winning you a deal. You can access these insights from anywhere on any device you want.
Watch this video on Salesforce by Intellipaat:

Service Cloud Einstein

Contact centers can get customer insights in real-time to give excellent customer service experience.

1. Einstein Supervisor: 

By combining prudent data discovery and operational insights in real-time, managers are empowered by Salesforce Einstein Supervisor with real-time data like queues and wait times and agent availability which enables them to pursue smarter actions. It can also predict the satisfaction of customers and make particular recommendations to enhance the customer experience.

2. Einstein Case Management:

 Cases will be escalated and classified when they come, using Machine Learning. Knowledge articles or informative videos which are required to solve cases are made available to agents saving valuable time.

3. Intelligent Mobile Service: 

With a service app on Android and iOS mobile, employees of a company can deliver personalized service to customers. The app uses sophisticated algorithms to optimize routing and scheduling and makes entire CRM data available to mobile employees in real-time.

Marketing Cloud Einstein

It is used to create market journeys that can be predicted. It delivers relevant content on the appropriate channel to the right audience at the required time. Marketers can make use of:

1. Predictive Scores: This process enables us to estimate how a customer engages with an email or makes a web purchase. Marketing firms can get to know what the factor is for true engagement which can lead to better anticipation of customer needs.
2. Predictive Audiences: Marketers can build audience groups that show common behavior. This is helpful in the effective engagement of customers. Again, Salesforce predictive intelligence is based on AI technology.
3. Automated Send Time Optimization: Marketers using this feature are able to optimally increase their return on investment in email marketing by delivering the message in the exact time at which the customers are most likely to engage with it.

Community Cloud Einstein

The finding of resource members is easy with this feature as there are automatic suggestions of groups, needs, relevant experts, and behavior from social activities. By finding out and promoting popular content, members are kept engaged in the community. Certified experts can be found by the community members who can answer their questions faster. For every customer, an optimal community can be created by Salesforce Einstein Analytics online training. If customers need urgent attention, then Salesforce Einstein creates a case on Service Cloud. To boost results, community managers can train Einstein with keywords. Customers get those content which they are looking for, and this is a unique feature of Salesforce Einstein. By highlighting the most relevant content for a topic, useful information is delivered to each user. When ‘Top Questions’ are generated by Salesforce Einstein, it usually lists them into what’s most important to each subject like the relevance of likes, comments, and views.

Analytics Cloud Einstein

This is used to find hidden data insights. The best sales, marketing, or service activities can be derived by finding patterns in your data. Insights are derived by analyzing all variable combinations from huge data, unlike the hypothesis-driven analysis.

App Cloud Einstein

In every stage of the building process of an app, you can embed intelligence. This has given rise to create predictive apps for both employees and customers. You can rapidly build AI-powered apps which possess the feature of image recognition. Suitable for various use cases, these apps use pre-trained classifiers, or you can train your own classifiers.

Salesforce Einstein has enabled businesses to build AI-first apps. It has essentially converged data science, data management, and modern app development into sets of platform services through which anyone can build the next-generation apps backed by AI. Let’s see how enterprise apps can be developed by App Cloud Einstein.

1. Including AI in Lightning and Force.com Apps: Speed is critical across enterprises. Business users have a huge problem with manual, repetitive tasks as they don’t have developer support to automate those tasks. Building both point-and-click and complete code apps are enabled by the App Cloud. The AI-generated results from core Salesforce apps can be taken and embedded into Lightning apps by business users and admins.

2. PredictionIO in Heroku Private Spaces: Being compatible with Salesforce’s Heroku Enterprise PredictionIO allows developers to build custom-intelligent applications using advanced Machine Learning frameworks. Predictive features can be built from scratch or calls can be sent to include a recommendation, classification, and lead scoring.

3. Predictive Vision Services: This cloud has launched APIs that bring Deep Learning to developers where unstructured images can be classified against a library of pre-trained classifiers. Custom classifiers can be trained to solve special image recommendation use cases like brand logos, medical imaging, product recognition, and much more.

Commerce Cloud Einstein

If you want to make customer shopping personal and more predictive, then this feature is for you. Get time-saving automation of tasks, predictive insights, and tools to give unique recommendations to every customer who is shopping in your store. By visualizing customer interaction, you can offer the best and most relevant products and deals. In every email, you can personalize recommendations of products. Across mobile and desktop devices, you can form unique customer experiences and thereby increase revenue per site visitor. Handling a vast amount of interactions requires sophisticated expertise of AI algorithms which Salesforce Einstein provides very aptly.

IoT Cloud Einstein

Needless to say, how connected devices are pervading everywhere, there is now the need for developments in IoT technology more than ever. Soon, our homes will be getting smart and connected through IoT. This is already happening, and the large-scale adoption of IoT technology in making smart homes a reality is imminent. Salesforce unveiled IoT Cloud Einstein where their customers are able to track innovation for IoT by merging their IoT data with Salesforce’s Artificial Intelligence platform. Let’s see what all features IoT Cloud Einstein has to offer:

1. PredictionIO: The IoT cloud, along with PredictionIO, runs on open-source Apache frameworks like Spark, Storm, and Kafka. These two services, when combined, will enable developers to build intelligent applications that can connect with IoT data and logic.
2. Predictive Scoring: One can stream data to AI algorithms when services like PredictionIO and IoT cloud come together. These algorithms can be trained to provide scoring data that indicates the way a connected device works.
3. Recommending the Next Best Action: As IoT cloud is connected directly with Salesforce CRM products, it doesn’t just specify as to how to ingest IoT data. It also specifies the scenarios where connected device data requires actions for employees or customers. This setup can, therefore, recommend the next best action. This may be realized when a representative is routed with a type of call which he/she has handled before.
4. Optimizing IoT Device Journeys: Suggestive corrective action is good from IoT, but Salesforce Einstein online training Hyderabad helps customers optimize the journeys which they have built for their devices. Updating the rules that govern the IoT device interactions based on desired states can be automated by feeding the data about the device journey into the IoT cloud. Customers can, therefore, get to business value faster and iterate on use cases.