Artificial Intelligence (AI) is a mechanism for a machine to “think like humans” — i.e., the machine can perform tasks with the planning, reasoning, learning, and understanding language. While no one is being equal to human intelligence nowadays or in future. The concept behind artificial intelligence is called machine learning, which is used to make our jobs easier, efficient and more productive. Advantage of Artificial Intelligence:-
- Data processing will improve at an amazing rate — Data processing performance will increase. The cost of data processing will become more affordable.
- There are more data that needs to be analysed because businesses are getting more data from customer conversation.
- AI will be improved consumer apps — now customers expect to provide same improvements across all their experiences
Most of us using AI who has a computer, smartphone, or other smart devices. We are already using Artificial Intelligence to make their life easier:-
- Siri (an integral part of iOS) and Cortana (Operating system-oriented voice assistant) act as your personal assistants using read your emails, track your location, voice processing and support more third-party integration.
- In Facebook, we use photo tag using image recognition.
- Amazon uses products using machine learning concept or algorithms.
- Traffic and navigation app like Waze uses optimal driving routes using a combination of forecasting, predictive models, and optimisation techniques.
AI is already increasing your customers’ expectations. When your customer comes to you like in Uber, Google, and Amazon you can think your customer’s expectations. If he comes into a store to buy a suit, you could suggest him according to his details of size, growth and previous choice?
The seller should know his customer size and preferences based on the basis of his purchase history. And Seller should be able to suggest the perfect pair of products to go with which will suit his customer.
The same concept applies to every business. Customers know that you have their details. They know that everything you can do with their details. And customers expect you to use your details to provide faster, smarter, personalised engagement during each visit.
AI supports data scientists and engineers for large amounts of data, data extraction and preparation of all data, and technology infrastructure.
It takes some specialised team of data scientists and developers who will access the correct data, prepare the same data, build the correct models, and then they will integrate the predictions back to the end-user experience such as CRM.
Salesforce has designed Salesforce Einstein so that all those challenges will be at Salesforce end instead of end users. i.e. everyone can use easily and more effectively to work with AI in a smarter way in their CRM.
After getting an AI project, it can be a long and painful experience. First of all, you have to analyze the business problem. Then you need to figure out the data that will be available to solve the problem. Then you need to assign appropriate resources or developer and infrastructure to gear it.
The use of Einstein is that all the Artificial Intelligence technology, which you need is built into your CRM apps. You will get the same result which you will get with your AI team, but without any challenges.
There are three type of most-used outcomes you would get from the AI as below:-
When Einstein analyzes and gives you a score, it will also give you the reason that how it was arrived at. For instance, prediction of lead scoring represents sales lead a score representing that will convert into an opportunity. You can also get the reasons for the lead score — for instance, the lead industry, the source, or some other factors are a strong indicator that the same lead will or won’t convert.
AI hasn’t only limitation to scoring; they can also be used for prediction of the future value of something, like a stock or a real estate investment. If your profile is a sales manager, AI can predict your quarterly sale and let you know that your team can meet their target.
Recommendations:- If anyone who will shop online and AI makes suggestions for product purchases, but it can also be a smarter way for recommendations for any other product or services from business software. And AI can also recommend some other products.
Before now, AI was so complex and cost-effective that only a select few things to use it in a meaningful way. Salesforce Einstein changes the complexity of AI. Now everyone or organisation can easily use AI nowadays to analyse their data, predict and plan for next steps, and automate their tasks with Einstein’s AI for CRM:
- Sales can get the idea for next opportunities and fulfil customer expectations by knowing what a customer needs before the customer explanation.
- Service can deliver effective service by foretasting cases and resolve issues before they converted in a problem.
- Marketing can also create journeys with some prediction and effective customer experiences like never before.
- IT can embed AI everywhere and create smarter apps for employees and customers.
If you have data scientists, Einstein gives them AI technology that can help them even more productive. If you don’t have any data scientists, then no issue. Einstein has AI technology which makes it easy for everyone to use in their CRM. Salesforce has world’s leading data scientists working with them — and that means they’re working for you.
Machine learning is working with structured data in the specific patterns that provide insight. In the financial company, machine learning predicts finds risky for the applicants with the bad loan and generates credit scores. Sales — Sales team can analyse some information from email, calendars, and CRM data to effectively actions like the best email response to move a deal forward.
Service — Service team can automatically split cases and intelligently suggest them to the right service agent.
Marketing — Marketing team can intelligently score of a customer to subscribe to a newsletter, open an email, or make a purchase. While there are lots of experimentation happening with machine deep learning, most applications you’re familiar with are based on the image analysis. With the image analysis, a computer learns to split random images by analysing multiple images and their data points. For instance, clients apps like Google Photos and Facebook use machine deep learning for face recognition in photos.
Sales — Sales team can analyse product pictures or images and use the same information to suggest or analyse the best upsell and cross-sell opportunities.
Service — Service team can analyse pictures or images of a product to a service case and use the same information to split the case and assign it to the right agent.
Marketing — Marketing team can analyse pictures or images on Twitter or Facebook to suggest or analyze the best visuals for an upcoming advertising or campaign. It can also identify brands in the images that are mentioned in the text or not.