Let’s assume that your Business Science team has created a great Einstein Discovery model and has deployed it for consumption. As an admin, you are responsible for utilizing this model in your Salesforce instance. In this blog, we are going to go over a specific use case discussing embedding Machine Learning generated predictions inside validation ...
A key pillar in the CRM landscape is pipeline management, where sales representatives track sales opportunities that progress through various stages until closure. This process results in either winning the specific sales opportunity or closing the opportunity without winning the business. The latter may be because the opportunity was lost to a competitor, because the ...
What if there was a system that could use all the accumulated knowledge of your company’s data and language, and in turn use that to learn how you ask questions, to give you the right answers? With Ask Data for Salesforce in Tableau CRM, we democratize analytics by empowering CRM users to easily discover data insights via ...
Einstein Discovery empowers businesses to explore patterns, trends, and correlations in their historical data with the help of auto-generated machine learning models. While understanding the past is helpful, Einstein Discovery machine learning models can be deployed and operationalized to predict future outcomes – all without ever writing a single line of code. Starting with the ...
Einstein Discovery drives business value for companies by eliminating friction in using machine learning, and maximizing its time-to-value. It is designed to facilitate every step of the journey towards operationalizing Machine Learning in the workspace, in a safe, ethical and most of all practical and easy way. This applies training the model and interpreting the Story, but it ...
The Revenue Operations Analytics template helps you uncover key insights for your Sales Leaders and Sales Reps for a more accurate forecast and better visibility into your pipeline and activity trends. Build up your team with the help of key metrics such as quota attainment, a projected forecast, and account reach to boost your team ...
🇯🇵 Read in Japanese Einstein Discovery allows the business scientist to explore patterns, trends and correlations in business data using Stories. The Story answers various questions, depending on the data it was trained on. Examples include Opportunity win-rate analysis, proprensity-to-buy (PTB) and Case average handling-time (AHT) or satisfaction (CSAT) in customer service. One particularly useful component that results automatically from ...
There is a good chance that you want to create a Machine Learning model for your business to aid decisions, but you are not sure where to begin. Einstein Discovery, located in Tableau CRM (Formerly Einstein Analytics), will enable you to do just that with clicks, not code. Unfortunately, “Machine Learning” and the fancy terms ...
Since the launch of Einstein Analytics over 5 years ago, we’ve been working hard to make the authoring experience richer and more declarative with “clicks, not code”. We hope this has empowered more of you to become dashboard builders and helped you build powerful analytics apps faster for your entire organization. We’ll be taking the ...
🇯🇵 Read in Japanese (Updated 2/10/21) The primary goal of this blog post is to provide technical information on the addition of tree-based machine learning (ML) algorithms to Einstein Discovery. This article helps readers understand the capabilities, benefits, and details of ensemble (tree-based) algorithms in Einstein Discovery. Tree-based algorithms go beyond Einstein Discovery’s traditional focus ...
