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bWith inputs from Prashant Bhargava, Lead Solution Engineer, Salesforce

 

Picture this: you turn up the volume in your favourite music streaming service and set off on your daily drive to work using your favourite web mapping service. All while enjoying a playlist that is auto-curated for you and without having to manually enter where you want to go. These services just seem to know what you would like and where you are going. You probably don’t think about the complex machine learning and analytics that are combining in the background to give you a pleasant commute. Trends in historical drives and your recently played tunes power artificial intelligence (AI) predictions about which song to listen to and which turn to take next.

Whether you are following your favourite commerce portals’ recommendations for your next purchase or your favourite video streaming platform’s evening suggestions or speaking to your smart speaker to get weather information and news, backward-looking analytics and forward-looking AI are a common part of your daily routine. Customers like you and me, have come to expect such seamless anticipatory experiences. Yet not every company is able to provide us with such predictive, connected experiences. Companies need to increasingly bridge this customer experience gap and become more connected.

In addition, the current unprecedented times has pushed industries to adopt new and improved business models – for instance, the adoption of digital channels and contact-less customer experiences. The workforce has evolved in tandem too; with digital ensuring mobile productivity for remote and working-from-home employees.

While companies are collecting data, dealing with governance and building data models for visualisation, not enough focus is given to analyse data to provide actionable insights that drive value for employees and consumers. Insights, so far, have mostly been backward-looking, reserved for executives, and not actionable by frontline employees. There is a growing need to achieve analytics ubiquity; to enable every single employee to make better decisions faster to drive more intelligent and connected customer experiences, and accelerate innovation.

Einstein Analytics follows a unique “power to the people” strategy. It layers on powerful AI predictions to deliver insights and recommendations to employees as they work on their customer interactions. As a result:

  • Frontline employees can be more productive and relevant
  • Customer experiences are personalised, available 24/7, accessible on any device and seamless from top-to-bottom
  • It includes AI-driven sales, service, and commerce interactions with Bots that are contextually aware of the customer, across channels

At Salesforce, Einstein Analytics provides our employees with AI-driven real-time recommendations right within the applications they use. It helps our sales teams with predictions and leading causes for things like win rate and expected close dates, as well as intelligent recommendations for the next steps. 

Using Einstein Voice, our sales teams can talk to Salesforce to:

  • Log activities
  • Plan next steps
  • Understand potential spikes in customer service requests
  • Predict CSAT and provide recommendations on which issues are the highest priority, and their probable resolution
  • Take action based on those recommendations while still in customer interaction.

Beyond the front-office departments like sales, service, and marketing, Salesforce has many essential back-office functions. These operational teams need insights to help make informed decisions about where to invest in new real estate, how to optimise pricing, which employees need extra training, and how specific teams and managers can improve. Einstein Analytics helps these teams to get the answers they need instantly and make better decisions.

Salesforce customers leverage Einstein Analytics to innovate and transform their customer and employee experiences. For example:

  • Predicting forecast by account
  • Identifying where time is best spent
  • Discovering key trends
  • Predicting customers most likely to churn
  • Surfacing intelligent solutions with machine learning from past cases
  • Recommending relevant products, proving bot-based instant contextual service, and many more

 

How businesses around the world use Einstein Analytics

  • Using Einstein Analytics, one of the world's leading suppliers of electrical protection, control, and power management solutions gets insights into leads most likely to convert.
  • A multinational customer in professional services uses AI-driven insights and trends to improve win rates and customer satisfaction. Using Einstein Discovery, it is able to leverage sales data to predict if an opportunity will close, and in how much time, so that it can prioritise more efficiently and identify key trends over time.
  • With Einstein Discovery, a customer in telecommunications is empowering client executives with dynamic and unique recommendations for improving sales outcomes, adjusting product and solution mixes, and managing customer contact throughout the deal cycle.
  • Using Einstein Prediction Builder, a non-profit organisation generated a valuable new data point for counsellors – a risk score assessing each student’s likelihood of dropping out of college. From here, the organisation could use these findings to adjust its strategy and reduce the student dropout rates.
  • With Einstein Analytics, a financial institution that provides residential mortgage solutions, provides sales reps with relevant insights into opportunities – directly embedded right into the system. This provides a holistic view into a customer's likelihood to fund a specific loan and the likelihood for a customer to renew a certain product.
  • With Einstein Analytics, a customer in the electronics industry provides agents with full visibility into case lifecycle and customer interactions across various channels, allowing agents to make data-driven decisions and reduce case resolution time.

Whether interacting through clicks or natural language, customers love to use our analytics, and because our apps can be deployed across any device, everyone can interact with or talk to Salesforce, anywhere. Find out how you can use Einstein Analytics (now called Tableau CRM) here.

 

This post originally appeared on the I.N.-version of the Salesforce blog.