Here’s a list of topics we’re going to discuss in this blog:
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Salesforce Einstein Overview
It’s a known fact that Salesforce is the top CRM service provider in the world. It has not stopped at CRM only and has also deployed marketing automation very successfully.
Salesforce has used AI technology in its Einstein 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 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.
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Various Deployments in Salesforce Einstein
Let’s look into where all Salesforce Einstein 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 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 exceptional companies that are focused on predicting the future. They can forecast which leads will turn into customers. They can also predict which customer shall become a loyal consumer of the service or products. However, if a prospect is falling out, 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, 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 relationships 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 types 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.
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Salesforce Service Cloud Einstein
Contact centers can get customer insights in real-time to give an excellent customer service experience.
1. Einstein Supervisor: By combining prudent data discovery and operational insights in real-time, managers are empowered through 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 customer experience.
2. Einstein Case Management: Cases will be evaluated 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.
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Salesforce Marketing Cloud Einstein
Salesforce Marketing Cloud Einstein 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:
- 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.
- Predictive Audiences: Marketers can build audience groups that show common behavior. This is helpful in the effective engagement of customers. Again, Salesforce’s predictive intelligence is based on AI technology.
- 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.
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Finding 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 quickly. For every customer, an optimal community can be created by Salesforce Einstein.
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 the content 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.
Salesforce Einstein Analytics
Salesforce analytics 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 hypothesis-driven analysis.
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App Cloud Einstein
In every stage of the building process of an app, you can embed intelligence. This has given rise to the creation of 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 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 is 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.
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Salesforce Commerce Cloud Einstein
If you want to make customer shopping personal and more predictive, then salesforce commerce cloud einstein 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 in AI algorithms which Salesforce Einstein provides very aptly.
IoT Cloud Einstein
Needless to say, how connected devices pervading everywhere, there is now a 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 features IoT Cloud Einstein has to offer:
- 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.
- 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.
- Recommending the Next Best Action: As the IoT cloud is connected directly with Salesforce CRM products, it doesn’t just specify 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 that he/she has handled before.
- Optimizing IoT Device Journeys: Suggestive corrective action is good for IoT, but Salesforce Einstein 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.
How to get started with Salesforce Einstein?
Einstein is already embedded into the Salesforce platform and it can be integrated with a lot of the products available on the platform. You still need to consider a lot of things to make sure it’s efficient while also making sure there is no room for false positives or bias.
Check if your company is ready for Salesforce Einstein?
There is a certain question that you need to find the answers of, before your company decides to start with Einstein:
- Analytics – You will have to feed lots of data to the platform because Einstein needs to learn constantly. Only then can it keep making accurate predictions. What this means is, that everyone from the front-line to top-tier employees will need to keep updating data regularly, submit reports, and make decisions accordingly.
- Clean data – You have to make sure that the data you’re feeding onto the platform is clean. While Einstein manages data processing, you still need to make sure that there is good-quality data being fed into it. It should be regularly updated and free from errors or duplicates.
- Use cases – You’ll have to define a proper use case for Einstein, or a way in which Einstein can really benefit your company.
- Budget – There are various costs related to adopting Einstein, like licensing, user training, etc. Even though Einstein will prove to be useful for your company, you have to make sure your company can afford the costs related to it.
Features in Salesforce Einstein
Salesforce being crowned with the title of the world’s smartest CRM is justified when advanced AI capabilities are brought into the Salesforce Einstein platform.
Salesforce releases three major updates in a year, always evolving. Einstein Discovery’s Fast Start Templates are one of the most exciting recent features. They have released new story templates that you can create in the Einstein Analytics Studio. These templates have been designed keeping in mind the user’s need to maximize sales.
After selecting these templates, Salesforce will start analyzing your data, and return valuable insights helping you win sales and reducing your close times.
Einstein Vision and Language is another exciting feature that was released recently. This feature helps users integrate AI into their apps without the need for being an expert in Machine Learning and Data Science. This is done using Image Recognition and Natural Language Processing.
Einstein Opportunity Scoring and Einstein Lead Scoring are two features that help you score sales opportunities and score leads even if you don’t have enough data.
There’s a list of new features that are going to be available in Einstein’s latest release, including:
- Einstein Pilot Consent – Einstein Pilot Consent will let data scientists prototype data, so the work can be done faster. It enables you to keep a track of what your customers pay attention to.
- Einstein Discovery – Einstein Discovery will let you forecast the outcomes with 3-10 possible values. You will be able to segment your data using text clustering, for free. You can also fine-tune the forecast with the help of trending data.
- Intelligent Form Reader – Intelligent Form Reader will let you extract information from individual fields, from a compound form field. You can then use this information to map out data in a template.
- Einstein Engagement Frequency – Einstein Engagement Frequency will scan each individual customer’s behaviour and use the data to forecast the optimal number of emails that should be sent to that particular customer.
Biggest Challenge faced while using Salesforce Einstein
We’ve discussed this before, Einstein needs a defined use case to work its best. There are various Salesforce services that are designed for specific applications which can be used with Einstein AI. But before you purchase these services, you need to define a use case.
For Salesforce Einstein to benefit your company to its utmost degree, you have to figure out what you exactly need Einstein for. Identifying your needs and requirements will give you your use case. Salesforce has acknowledged that this proves to be quite a task and hence, they’ve provided a Guide to AI Use Cases. Users can refer to this site, fill out a questionnaire and it will help them determine the use case that is the most beneficial for them.
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Conclusion
Salesforce has always stayed ahead of other CRM providers in terms of innovation, foresight, and growth. Salesforce had launched AI tools for third-party developers to include Salesforce Einstein intelligence to applications built on top of the Salesforce platform. This is just one of the gestures which prove our point.
Marc Benioff and his team have come a long way in their cloud journey. He would convince clients to use his offerings rather than other big companies’ offerings. He had a vision that the cloud would be the next big thing way back when they were just beginning. Now, the growth and importance of Cloud Computing is a standing witness to his vision becoming a reality.
With the same vision, he has incepted the Salesforce Einstein platform as clearly AI Cloud Computing and IoT are the technologies that will dominate the sphere of technology. Hence, if you learn Salesforce, you have a good chance to enhance your career, and when the Einstein technology grows further in demand you will have an added advantage.