Salesforce AI – powered technology to connect better with your customers
Einstein AI is a powerful software that can turn your customer data into powerful business insights
Salesforce is a solution on the cloud which allows clients to better manage their relationships with customers to make sure all their needs are met. Nowadays businesses put more focus on improving their customer service, and for that reason AI is a tool that companies can leverage to improve customer loyalty and reputation of their brands. Salesforce AI allows businesses to serve their customers smarter by leveraging Einstein, the AI tool for CRM. Einstein helps modernize current corporate processes by enabling businesses to incorporate intelligent customer service.
With the development of Einstein, Salesforce makes a commitment to improving customer experience by providing a solution with visualization options and valuable insights.
The birth of Einstein AI
Salesforce Einstein was launched in 2017 to help CRM users get a better understanding of customers and their actions in a broad context, it promotes action rather than just usual analysis. The tool is able to decrease the number of clicks usually needed to go through frequent tasks and has made the Salesforce platform easier to use by leveraging machine learning technology.
How does Einstein work?
The platform allows users to focus on managing more complex processes by implementing intelligent bots that answer the most common customer questions. The tool can also provide knowledge, recommendations, and common replies useful to manage difficult cases.
AutoML allows users to analyze data to detect errors and promotes better understanding of the customers’ purchasing decisions and helps in making predictions about what customers value the most.
Support for corporate decisions
Users can try Einstein Predictive Intelligence to understand what drives closing sales and what does not. With the support of Einstein, the sales forecasts are more accurate, allowing managers to create better commercial strategies based on those predictions.
Natural language processing (NLP) helps extract linguistic patterns that help answering questions, it identifies communication on the internet related with the company’s brand and allows reply to certain requests.
Enhance marketing efforts
Einstein AI can be used to get relevant insights about how to optimize marketing efforts and run better campaigns. The tool helps improve communications across all marketing channels.
Components of Artificial Intelligence
Einstein AI incorporates the following segments:
1. Machine learning
Leverages big data, historical data and statistical models to predict future outcomes and improve decision making. Einstein Prediction Builder assists in constructing prediction models in a codeless platform, retrieving results that help enhance and improve business decisions. Another relevant functionality is Einstein Next Action, in which the user can input series of requirements and the tool will help deliver recommendations at the right time. Finally, Einstein Discovery leverages AI to better understand analysis models. The tool identifies useful patterns in data to create better forecasts and suggestions.
2. Natural Language Processing
Einstein language helps you understand your audience better by studying the text-based customer feedback or their interactions and extracting the text intent. Also, Einstein Chatbot helps improve customer service by giving timely responses and manages all client request with virtual assistance.
3. Computer vision
The intelligent image identification (Einstein Vision) is used to identify visual patterns and recognize text in photos, allowing users to also track brand content on social media and other platforms.
Tools that enable Salesforce AI
- Internet of things: a great amount of data is generated from linked devices and processed in the system to provide valuable insight.
- Graphical processing units: is the power which enables computers to process data repetitively, specially needed to train neural networks.
- Advanced algorithms: these were developed to analyze large amounts of data at different levels, helping to understand complex systems and identifying rare events.
- APIs – application programming interfaces: these are code packages which allow the AI technology to be linked to current products and software functionalities.
Salesforce AI facts
1. Exceeding expectations after challenges in 2020
Global business is constantly increasing, with around $21 billion USD revenues in 2021 and $26 billion USD expected revenue in 2022. This is a demonstration that companies are investing in technology automation, allowing at the same time the creation of 4 million new jobs in the country.
2. Einstein Automate
The tool helps businesses automate workflows with the MuleSoft Composer, allowing the connection across different applications and enabling data flows.
3. Tableau CRM
In 2017 Einstein Analytics was introduced to allow CRM users to analyze data using AI-powered advanced analytics. This solution decreased the need users had to develop mathematical models or write long algorithms to process and understand data, with the tool the task of analyzing data was automated. In 2019 Salesforce acquired Tableau CRM, with plans to combine the newly acquired functionality with Einstein Analytics under the name Tableau CRM.
4. Voice and AI
The combination of cloud services with voice integration allows real-time voice transcription. AI will eventually allow the software to generate reports based on understanding of the query language. The division of Salesforce Research created a program to analyze the calls from call centers to help representatives act on specific moments of the conversation with customers. The tool is able to create prefilled fields resulting from the content of the live calls and helps streamline the work for people who are in roles requiring customer facing.
5. Preventing duplicate work
With the help of machine learning, you can automate the cleanse of data. Whenever two records are recognized as duplicated, the software will make the proper detection and apply the logic to records analyzed in the future. Whenever duplicates are created, the user can train the machine to learn the thought process to identify these records and clean your data as you go in a timely manner. As the data and the platform gets more sophisticated, machine learning is able to better optimize the tasks to keep data and all the internal records clean, questioning the future and making the right decisions to secure maintenance of clean data.