1. The document provides an introduction to formulas in Salesforce, breaking them down into three parts: data in, business logic, and value out.
2. It demonstrates how to use common functions like IF, AND, OR, and CASE to build formulas based on different use cases.
3. Examples show how to create formulas to calculate opportunity age, display priority flags for cases, and identify strategic opportunities.
The document discusses using predictive analytics and a decision tree classification algorithm to determine which companies in a customer relationship management (CRM) system are likely or not likely to accept offers for cross-selling cash management services. The authors extracted data from the CRM system, cleaned and prepared the data, selected important attributes, built a J48 decision tree model using the Weka data mining tool, and appended the model's predictions back to the CRM system to guide sales teams. The model achieved good accuracy and ROC metrics despite not using all supplied attributes.
Big Data That Drives Marketing ROI Across All Channels & Campaigns-A Case Stu...Vivastream
The document discusses how Workday, a leading HR and financial software company, improved their digital marketing performance through closing the loop on data and attribution modeling.
Workday faced challenges with their complex B2B sales cycle that involved multiple decision makers over long periods of time. They sought to improve lead generation, close more business faster, and measure ROI.
The strategy started with closing the data loop to attribute the success of different marketing programs from awareness to engagement to conversion and sales. Analytics tools were connected to business tools like CRM to analyze multi-source data and gain insights to optimize performance.
Attribution modeling helped understand what was happening with the customer journey, why, and what actions to take as a
This document appears to be an advertisement for wedding services from Weis Markets grocery stores. It promotes their floral design and wedding cake services. It states they specialize in beautiful bridal bouquets and decadent wedding cakes. Brides can choose from popular options or work with their designers to create custom arrangements and cakes. The ad encourages readers to visit their local Weis store to start wedding planning. It provides additional information on store locations for different services.
A young boy watches a horror movie alone at home. He sees strange figures in the darkness when he turns lights on and off. When he goes to his bedroom, the light goes out and his door opens on its own. He sees the figure of a young boy in the darkness who walks towards his bed. When he turns on the light, the boy disappears. Someone then taps him from behind, and he sees the boy again with blood on his hands.
This document contains the resume of Pratap Narayan. It summarizes his professional experience working as a Team Leader at AFORESERVE.COM.LTD in Bangalore since January 2016 and prior roles as a Research and Development Engineer. It also lists his qualifications including a B.Tech in Electronics and Communication Engineering, training and internship experiences, roles and responsibilities, an academic project on an automatic vehicle braking system, and skills. Personal details like name, date of birth, addresses are also provided.
Balakrishna Gurugubelli has over 12 years of experience in environmental management, safety, and CSR activities. He currently works as the Deputy Manager of Environment at My Home Industries, where he manages environmental compliance, implements sustainability initiatives, and leads safety programs. He has a PhD in analytical chemistry and experience developing environmental impact reports, auditing sites for compliance, and coordinating CSR activities.
The document provides an overview of McDermott's DLV2000 press event held in Singapore on April 13, 2016. It includes forward-looking statements and cautions that actual performance may differ. The agenda covers introductions of leadership, an overview of McDermott, and a focus on the DLV2000 vessel. It discusses strategic themes around early engagement, customer alignment, and integrated solutions. It also reviews McDermott's financial performance in 2015, including increased backlog and revenue, and outlook for 2016 with 81% of expected revenue in backlog.
The document discusses using predictive analytics and a decision tree classification algorithm to determine which companies in a customer relationship management (CRM) system are likely or not likely to accept offers for cross-selling cash management services. The authors extracted data from the CRM system, cleaned and prepared the data, selected important attributes, built a J48 decision tree model using the Weka data mining tool, and appended the model's predictions back to the CRM system to guide sales teams. The model achieved good accuracy and ROC metrics despite not using all supplied attributes.
Big Data That Drives Marketing ROI Across All Channels & Campaigns-A Case Stu...Vivastream
The document discusses how Workday, a leading HR and financial software company, improved their digital marketing performance through closing the loop on data and attribution modeling.
Workday faced challenges with their complex B2B sales cycle that involved multiple decision makers over long periods of time. They sought to improve lead generation, close more business faster, and measure ROI.
The strategy started with closing the data loop to attribute the success of different marketing programs from awareness to engagement to conversion and sales. Analytics tools were connected to business tools like CRM to analyze multi-source data and gain insights to optimize performance.
Attribution modeling helped understand what was happening with the customer journey, why, and what actions to take as a
This document appears to be an advertisement for wedding services from Weis Markets grocery stores. It promotes their floral design and wedding cake services. It states they specialize in beautiful bridal bouquets and decadent wedding cakes. Brides can choose from popular options or work with their designers to create custom arrangements and cakes. The ad encourages readers to visit their local Weis store to start wedding planning. It provides additional information on store locations for different services.
A young boy watches a horror movie alone at home. He sees strange figures in the darkness when he turns lights on and off. When he goes to his bedroom, the light goes out and his door opens on its own. He sees the figure of a young boy in the darkness who walks towards his bed. When he turns on the light, the boy disappears. Someone then taps him from behind, and he sees the boy again with blood on his hands.
This document contains the resume of Pratap Narayan. It summarizes his professional experience working as a Team Leader at AFORESERVE.COM.LTD in Bangalore since January 2016 and prior roles as a Research and Development Engineer. It also lists his qualifications including a B.Tech in Electronics and Communication Engineering, training and internship experiences, roles and responsibilities, an academic project on an automatic vehicle braking system, and skills. Personal details like name, date of birth, addresses are also provided.
Balakrishna Gurugubelli has over 12 years of experience in environmental management, safety, and CSR activities. He currently works as the Deputy Manager of Environment at My Home Industries, where he manages environmental compliance, implements sustainability initiatives, and leads safety programs. He has a PhD in analytical chemistry and experience developing environmental impact reports, auditing sites for compliance, and coordinating CSR activities.
The document provides an overview of McDermott's DLV2000 press event held in Singapore on April 13, 2016. It includes forward-looking statements and cautions that actual performance may differ. The agenda covers introductions of leadership, an overview of McDermott, and a focus on the DLV2000 vessel. It discusses strategic themes around early engagement, customer alignment, and integrated solutions. It also reviews McDermott's financial performance in 2015, including increased backlog and revenue, and outlook for 2016 with 81% of expected revenue in backlog.
Pratap Narayan R & D Engineer In ProductionPRATAP NARAYAN
Pratap Narayan is seeking a position that allows him to maximize his skills and serve an organization loyally. He has over 3 years of experience in testing, production, quality assurance, and team management. He is currently working as a team leader at AFORESERVE.COM.LTD. in Bangalore. Previously he held research and development roles at two other companies. Pratap has a Bachelor's degree in electronics and communication engineering and specialized training in areas like mobile communication, auditing, and information security. He has strong communication, problem-solving, and technical skills.
The document outlines the shot list for a film called "Dollz" that follows a character who is fired from his job. He takes the train home and finds a voodoo doll of himself sitting in his seat. The doll appears in different locations around the character and he becomes increasingly disturbed. At home, the character finds his girlfriend dead on the kitchen floor and breaks down in tears, realizing the doll may be responsible for her death.
The document provides location recce details for three potential filming locations - Europa Trading Estate, Canary Wharf, and 11 Wellington Ave in Sidcup. For each location, contact details are given as well as information on permissions, availability, amenities, possible shots, suitability, and any safety issues. The purpose of filming at each location is also stated, such as getting a character in a suitable working area or filming them at home.
The document outlines the shots planned for 3 scenes of a film. Scene 1 takes place in an office and includes 6 shots showing a character's arrival at their desk and interaction with a voodoo doll. Scene 2 is set at a train station with 6 shots of the character traveling through and looking for where the doll was left. Scene 3 cuts between close-ups of a knife and doll being stabbed and damaged, along with shots of the character moving between their bedroom and kitchen.
This call sheet is for a 1 minute short film produced by Micheal Oladokun on February 27, 2016. It lists the production crew including the producer, assistant producer, director, and director of photography. The call sheet also includes a production checklist noting that the camera, lighting kit, microphone kit, and tripod are ready. It provides the shooting locations of Europa Trading Estate, Canary Wharf, and 11 Wellington Avenue in Sidcup. Contact information is given for the producer and assistant producer.
The document provides information about the roles and responsibilities of various crew members for a film production. It discusses the roles of the producer, director, director of photography, assistant producer, and actors. For each role, it outlines the key responsibilities and why the specific individuals were chosen for those roles in the production team. It emphasizes that the producer oversees all aspects of production, the director brings the script to life visually, and the other roles all support the director and producer in specialized areas like camerawork, budget, and acting.
This document summarizes an article from the February 2016 issue of Inside Pennsylvania magazine about Euell Gibbons, a famous forager and author known as the "guru of wild foods" who lived in central Pennsylvania in the 1960s-70s. It discusses his background of living off the land from a young age, his knowledge of edible wild plants, and how he shared this knowledge through books and wild food dinners near Troxelville. Local residents provide anecdotes about interacting with Gibbons and recall details about his personality and expertise with wild foods.
Onur Air is a low-cost airline established in 1992 that is based in Istanbul, Turkey. It operates 29 aircraft serving over 14 domestic routes within Turkey and over 110 international routes to 25 countries. The airline has grown to 1,500 employees and has safely carried over 85 million passengers since 1992, flying to destinations across Turkey as well as in Azerbaijan, Northern Cyprus, Iran, Norway, Ukraine, Denmark, the Netherlands, Austria and Germany.
This presentation provided an overview of how to build datasets, dashboards, and dataflows in Einstein Analytics. It demonstrated how to create a dataset from Salesforce data, build a recipe to bucket and format fields, design a templated dashboard with charts and lists, embed the dashboard on the home page, and create a compute expression in the dataflow. The presentation encouraged attendees to access additional learning resources and provide feedback in a survey.
Get the Analytic Edge, Learn Einstein Analyticsrikkehovgaard
The document provides instructions on how to build an Einstein Analytics dashboard and dataset using an opportunity dataset. It outlines steps to create a recipe, modify fields, build a smart dashboard with charts and filters, add actions, and embed the dashboard on a home page. It also describes creating a compute expression to classify deal sizes and resources for additional learning.
Improving Enterprise Findability: Presented by Jayesh Govindarajan, SalesforceLucidworks
1) Jayesh Govindarajan presented on improving enterprise search and findability at Salesforce. He discussed how enterprise search differs from consumer search, challenges with enterprise findability, and machine learning algorithms like LETOR that can be used.
2) Govindarajan explained that diversity of data, intentions, and customers makes enterprise search more complex than consumer search. Most enterprise search relies on simple ranking functions that may not reflect relevance well.
3) Machine learning algorithms like logistic regression and learning to rank can learn relevance from user behavior data like clicks and views. These algorithms output ranking models that can be deployed to search engines like Solr.
The document discusses controls and technical features in Salesforce, including S-Controls and formula fields. It provides examples of how Kaplan Financial and Tacpoint Technologies used custom objects, formula fields, roll-up summaries, and custom links to build automated sales reports and improve their lead conversion processes. The key lessons are to be careful with master-detail relationships and formula size, and that technical features can enhance users' experience and make processes more efficient.
This document provides information about learning Einstein Analytics including getting a developer org and creating analytics apps and dashboards. It outlines steps to create a dataset from an opportunity object, build a recipe to bucket deal sizes and stages, develop a dashboard with charts showing period over period and YTD metrics, and add actions to records from the dashboard. It also demonstrates adding a compute expression to classify deal sizes in a dataflow. The document aims to help users learn and get started with Einstein Analytics capabilities.
Get the analytics edge, learn Einstein Analytics, Rikke HovgaardCzechDreamin
This document provides information about an Einstein Analytics presentation on getting started with Einstein Analytics, including how to get a developer org, create datasets and recipes, build dashboards, and add compute expressions. The presentation covers the basics of the Einstein Analytics user interface and demonstrates how to create apps, datasets, recipes, dashboards, and compute expressions to analyze and visualize opportunity data.
How do you get people to adopt? How do you make them happy? What about writing flows to capture data for events (like volunteers, event, presentations, etc.)? Join us to learn how you can incorporate search before add, automate related record creation and updating, and more that will bring cheers throughout your org! You should have beginner knowledge of Flow and intermediate knowledge of the Salesforce data architecture to fully enjoy this session.
The document provides guidance on developing an effective job plan that will help efficiently identify and select qualified candidates. It explains that a well-written job plan consists of three main parts: a compelling job description, screening questions, and open-ended questions. It outlines the key elements and sections of the job description, including a creative title, "hook," company overview, and keys to success. Keywords and screening questions should also be included to attract qualified applicants.
Introduction to A.I in Sales Cloud and Sales Cloud Einstein (April 27, 2017)Salesforce Partners
This document provides an introduction to artificial intelligence capabilities in Salesforce's Sales Cloud and Sales Cloud Einstein product. It outlines the agenda which includes an overview of Salesforce and AI, a demonstration of Sales Cloud Einstein, and next steps. The demonstration shows how Einstein Lead Scoring, Einstein Account Insights, and Einstein Opportunity Insights can help sales teams by automatically scoring leads, surfacing key insights on customer accounts, and providing predictions to help close deals. The document encourages partners to register for upcoming webinars on applying AI to key sales processes and implementing Sales Cloud Einstein.
Bootstrap, Angel or Venture: Determining the Right Financing Strategy for You...Judy Loehr
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Template for submitting Business Plan in AKTU Parikrama Competition.Engineers inc
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This will likely be the only document a prospective investor reads initially, and hence brevity, conciseness, and clarity are of the utmost importance.This document is designed to guide you on the creation of the critical components of this document,and provide examples of appropriate content for each section.
Go through the slides carefully and then produce your document accordingly.
RingLead Chief Product Officer Michael Farrington teamed up with RingLead power-user Jason Paquette to give an overview on implementing long-standing data quality processes
This document provides guidance on developing an effective customer success program. It recommends defining the customer's value proposition, organizing relevant customer data, and communicating the program internally and externally. The case study of Optimus Solutions describes how they implemented a customer success plan on Salesforce to better understand customers, act proactively, and increase business. Measuring the program's success showed improved customer solutions, strategic partnerships, and proactive business drives.
Linked in data to power sales - dreamforce nov 18 2013 - vfinal w. appendixAndres Bang
LinkedIn developed a data-driven approach to sales that blends account lens, analytics, and automation. They focus on understanding accounts at a high level by considering size of opportunity and likelihood. Analytics models assign scores to prioritize accounts. Automation uses triggers from user behavior and signals to proactively engage customers. Key learnings include the need for cross-functional partnerships and an experiment-measure approach to continuously improve the system. The goal is to leverage LinkedIn's data to power the most effective sales and marketing.
Pratap Narayan R & D Engineer In ProductionPRATAP NARAYAN
Pratap Narayan is seeking a position that allows him to maximize his skills and serve an organization loyally. He has over 3 years of experience in testing, production, quality assurance, and team management. He is currently working as a team leader at AFORESERVE.COM.LTD. in Bangalore. Previously he held research and development roles at two other companies. Pratap has a Bachelor's degree in electronics and communication engineering and specialized training in areas like mobile communication, auditing, and information security. He has strong communication, problem-solving, and technical skills.
The document outlines the shot list for a film called "Dollz" that follows a character who is fired from his job. He takes the train home and finds a voodoo doll of himself sitting in his seat. The doll appears in different locations around the character and he becomes increasingly disturbed. At home, the character finds his girlfriend dead on the kitchen floor and breaks down in tears, realizing the doll may be responsible for her death.
The document provides location recce details for three potential filming locations - Europa Trading Estate, Canary Wharf, and 11 Wellington Ave in Sidcup. For each location, contact details are given as well as information on permissions, availability, amenities, possible shots, suitability, and any safety issues. The purpose of filming at each location is also stated, such as getting a character in a suitable working area or filming them at home.
The document outlines the shots planned for 3 scenes of a film. Scene 1 takes place in an office and includes 6 shots showing a character's arrival at their desk and interaction with a voodoo doll. Scene 2 is set at a train station with 6 shots of the character traveling through and looking for where the doll was left. Scene 3 cuts between close-ups of a knife and doll being stabbed and damaged, along with shots of the character moving between their bedroom and kitchen.
This call sheet is for a 1 minute short film produced by Micheal Oladokun on February 27, 2016. It lists the production crew including the producer, assistant producer, director, and director of photography. The call sheet also includes a production checklist noting that the camera, lighting kit, microphone kit, and tripod are ready. It provides the shooting locations of Europa Trading Estate, Canary Wharf, and 11 Wellington Avenue in Sidcup. Contact information is given for the producer and assistant producer.
The document provides information about the roles and responsibilities of various crew members for a film production. It discusses the roles of the producer, director, director of photography, assistant producer, and actors. For each role, it outlines the key responsibilities and why the specific individuals were chosen for those roles in the production team. It emphasizes that the producer oversees all aspects of production, the director brings the script to life visually, and the other roles all support the director and producer in specialized areas like camerawork, budget, and acting.
This document summarizes an article from the February 2016 issue of Inside Pennsylvania magazine about Euell Gibbons, a famous forager and author known as the "guru of wild foods" who lived in central Pennsylvania in the 1960s-70s. It discusses his background of living off the land from a young age, his knowledge of edible wild plants, and how he shared this knowledge through books and wild food dinners near Troxelville. Local residents provide anecdotes about interacting with Gibbons and recall details about his personality and expertise with wild foods.
Onur Air is a low-cost airline established in 1992 that is based in Istanbul, Turkey. It operates 29 aircraft serving over 14 domestic routes within Turkey and over 110 international routes to 25 countries. The airline has grown to 1,500 employees and has safely carried over 85 million passengers since 1992, flying to destinations across Turkey as well as in Azerbaijan, Northern Cyprus, Iran, Norway, Ukraine, Denmark, the Netherlands, Austria and Germany.
This presentation provided an overview of how to build datasets, dashboards, and dataflows in Einstein Analytics. It demonstrated how to create a dataset from Salesforce data, build a recipe to bucket and format fields, design a templated dashboard with charts and lists, embed the dashboard on the home page, and create a compute expression in the dataflow. The presentation encouraged attendees to access additional learning resources and provide feedback in a survey.
Get the Analytic Edge, Learn Einstein Analyticsrikkehovgaard
The document provides instructions on how to build an Einstein Analytics dashboard and dataset using an opportunity dataset. It outlines steps to create a recipe, modify fields, build a smart dashboard with charts and filters, add actions, and embed the dashboard on a home page. It also describes creating a compute expression to classify deal sizes and resources for additional learning.
Improving Enterprise Findability: Presented by Jayesh Govindarajan, SalesforceLucidworks
1) Jayesh Govindarajan presented on improving enterprise search and findability at Salesforce. He discussed how enterprise search differs from consumer search, challenges with enterprise findability, and machine learning algorithms like LETOR that can be used.
2) Govindarajan explained that diversity of data, intentions, and customers makes enterprise search more complex than consumer search. Most enterprise search relies on simple ranking functions that may not reflect relevance well.
3) Machine learning algorithms like logistic regression and learning to rank can learn relevance from user behavior data like clicks and views. These algorithms output ranking models that can be deployed to search engines like Solr.
The document discusses controls and technical features in Salesforce, including S-Controls and formula fields. It provides examples of how Kaplan Financial and Tacpoint Technologies used custom objects, formula fields, roll-up summaries, and custom links to build automated sales reports and improve their lead conversion processes. The key lessons are to be careful with master-detail relationships and formula size, and that technical features can enhance users' experience and make processes more efficient.
This document provides information about learning Einstein Analytics including getting a developer org and creating analytics apps and dashboards. It outlines steps to create a dataset from an opportunity object, build a recipe to bucket deal sizes and stages, develop a dashboard with charts showing period over period and YTD metrics, and add actions to records from the dashboard. It also demonstrates adding a compute expression to classify deal sizes in a dataflow. The document aims to help users learn and get started with Einstein Analytics capabilities.
Get the analytics edge, learn Einstein Analytics, Rikke HovgaardCzechDreamin
This document provides information about an Einstein Analytics presentation on getting started with Einstein Analytics, including how to get a developer org, create datasets and recipes, build dashboards, and add compute expressions. The presentation covers the basics of the Einstein Analytics user interface and demonstrates how to create apps, datasets, recipes, dashboards, and compute expressions to analyze and visualize opportunity data.
How do you get people to adopt? How do you make them happy? What about writing flows to capture data for events (like volunteers, event, presentations, etc.)? Join us to learn how you can incorporate search before add, automate related record creation and updating, and more that will bring cheers throughout your org! You should have beginner knowledge of Flow and intermediate knowledge of the Salesforce data architecture to fully enjoy this session.
The document provides guidance on developing an effective job plan that will help efficiently identify and select qualified candidates. It explains that a well-written job plan consists of three main parts: a compelling job description, screening questions, and open-ended questions. It outlines the key elements and sections of the job description, including a creative title, "hook," company overview, and keys to success. Keywords and screening questions should also be included to attract qualified applicants.
Introduction to A.I in Sales Cloud and Sales Cloud Einstein (April 27, 2017)Salesforce Partners
This document provides an introduction to artificial intelligence capabilities in Salesforce's Sales Cloud and Sales Cloud Einstein product. It outlines the agenda which includes an overview of Salesforce and AI, a demonstration of Sales Cloud Einstein, and next steps. The demonstration shows how Einstein Lead Scoring, Einstein Account Insights, and Einstein Opportunity Insights can help sales teams by automatically scoring leads, surfacing key insights on customer accounts, and providing predictions to help close deals. The document encourages partners to register for upcoming webinars on applying AI to key sales processes and implementing Sales Cloud Einstein.
Bootstrap, Angel or Venture: Determining the Right Financing Strategy for You...Judy Loehr
This presentation was shared at Dreamforce 2016 to help early-stage cloud business application startup teams understand how investors will evaluate their markets so they can plan the right financing strategy from the beginning.
Template for submitting Business Plan in AKTU Parikrama Competition.Engineers inc
This is the template for submitting Business Plan in AKTU Parikrama Competition on March 9, 2018 during the E-Summit.
This will likely be the only document a prospective investor reads initially, and hence brevity, conciseness, and clarity are of the utmost importance.This document is designed to guide you on the creation of the critical components of this document,and provide examples of appropriate content for each section.
Go through the slides carefully and then produce your document accordingly.
RingLead Chief Product Officer Michael Farrington teamed up with RingLead power-user Jason Paquette to give an overview on implementing long-standing data quality processes
This document provides guidance on developing an effective customer success program. It recommends defining the customer's value proposition, organizing relevant customer data, and communicating the program internally and externally. The case study of Optimus Solutions describes how they implemented a customer success plan on Salesforce to better understand customers, act proactively, and increase business. Measuring the program's success showed improved customer solutions, strategic partnerships, and proactive business drives.
Linked in data to power sales - dreamforce nov 18 2013 - vfinal w. appendixAndres Bang
LinkedIn developed a data-driven approach to sales that blends account lens, analytics, and automation. They focus on understanding accounts at a high level by considering size of opportunity and likelihood. Analytics models assign scores to prioritize accounts. Automation uses triggers from user behavior and signals to proactively engage customers. Key learnings include the need for cross-functional partnerships and an experiment-measure approach to continuously improve the system. The goal is to leverage LinkedIn's data to power the most effective sales and marketing.
How to Choose the Right Automation Tool by Jonathan Hackworth Salesforce Admins
This document discusses various automation tools in Salesforce and provides examples of how to apply them. It introduces the Salesforce automation suite, which includes Workflow, Approvals, Process Builder, and Visual Workflow. Examples are given such as using Workflow to assign an account owner based on opportunity criteria, using Process Builder to automate a multi-step approval process, and using Workflow or Process Builder to trigger actions like sending a lead record to an external system or posting to Chatter. Tips are provided like starting with Process Builder, testing in sandbox, and keeping automation names descriptive.
Build an AI Roadmap and Win the Consumer Goods Intelligence RaceGib Bassett
My presentation from Salesforce Connections 2018. In it, I describe why it's important to think about a use case driven strategy for advanced analytics and AI.
Planet Technology Group is implementing Microsoft Dynamics CRM to improve their inefficient business processes and systems. The implementation will enhance the customer experience by streamlining the sales and marketing processes in CRM. This includes configuring leads, opportunities, activities, cases, marketing lists, campaigns, and integrating Outlook for email marketing. The project scope covers sales management, marketing functions, and data management within CRM.
For over a decade, ExactTarget has offered a comprehensive set of APIs that enable our customers to automate their email campaigns and seamlessly integrate their marketing, analytics, and other business software. Join us as we introduce core Marketing Cloud concepts, including the importance of permission and the value of relevancy, as well as the core technologies that make up the ExactTarget platform, including lists, data extensions, and AMPscript.
Demystifying salesforce predictions ea user group brightgenrikkehovgaard
Einstein Analytics Stories and Prediction Builder both provide predictive capabilities within Salesforce, but have some key differences:
- Einstein Analytics Stories allows for more in-depth data insights and model visibility, while Prediction Builder focuses on rapid predictions within Salesforce objects.
- Einstein Analytics Stories supports both numeric and classification predictions across internal and external data, while Prediction Builder is limited to Salesforce data.
- Einstein Analytics Stories provides predictive stories and insights into why predictions were made, while Prediction Builder only shows high-level accuracy metrics and impacting factors.
- Einstein Analytics Stories is configured by data analysts, while Prediction Builder is aimed at Salesforce administrators for simple setup.
Process Builder and Flow: An Admin's Trigger by Rich EnglhardSalesforce Admins
This document discusses Process Builder and Flow in Salesforce and how they can be used to automate workflows and processes. It provides examples of how Process Builder allows updating related records through lookup fields and child objects, and how Flow enables more complex conditional logic and processes that can be triggered by button clicks. The document recommends Process Builder and Flow as an admin's tools to create automated workflows and processes without code, acting as a stepping stone to becoming a developer.
Similar to DF16 Imprivata - Getting Started with Formulas (20)
Process Builder and Flow: An Admin's Trigger by Rich Englhard
DF16 Imprivata - Getting Started with Formulas
1. Chris Duncombe
Manager, Business Applications
Imprivata
cduncombe@imprivata.com
@sfdc_ninja
Getting Started with Formulas
They aren’t scary…..
Chris Rustici
Sr. Salesforce Analyst
Imprivata
crustici@imprivata.com
@ChrisRustici
2. Forward-Looking Statements
Statement under the Private Securities Litigation Reform Act of 1995:
This presentation may contain forward-looking statements that involve risks, uncertainties, and assumptions. If any such uncertainties materialize or
if any of the assumptions proves incorrect, the results of salesforce.com, inc. could differ materially from the results expressed or implied by the
forward-looking statements we make. All statements other than statements of historical fact could be deemed forward-looking, including any
projections of product or service availability, subscriber growth, earnings, revenues, or other financial items and any statements regarding strategies
or plans of management for future operations, statements of belief, any statements concerning new, planned, or upgraded services or technology
developments and customer contracts or use of our services.
The risks and uncertainties referred to above include – but are not limited to – risks associated with developing and delivering new functionality for
our service, new products and services, our new business model, our past operating losses, possible fluctuations in our operating results and rate of
growth, interruptions or delays in our Web hosting, breach of our security measures, the outcome of any litigation, risks associated with completed
and any possible mergers and acquisitions, the immature market in which we operate, our relatively limited operating history, our ability to expand,
retain, and motivate our employees and manage our growth, new releases of our service and successful customer deployment, our limited history
reselling non-salesforce.com products, and utilization and selling to larger enterprise customers. Further information on potential factors that could
affect the financial results of salesforce.com, inc. is included in our annual report on Form 10-K for the most recent fiscal year and in our quarterly
report on Form 10-Q for the most recent fiscal quarter. These documents and others containing important disclosures are available on the SEC
Filings section of the Investor Information section of our Web site.
Any unreleased services or features referenced in this or other presentations, press releases or public statements are not currently available and may
not be delivered on time or at all. Customers who purchase our services should make the purchase decisions based upon features that are currently
available. Salesforce.com, inc. assumes no obligation and does not intend to update these forward-looking statements.
3. Chapter 1
There are tons…
…we’ll show you four
How can I use this?
Does this really work?
Prizes?
Who knows…
Chapter 2 Chapter 3 Chapter 4
What are they?
Is there a trick?
Formulas Functions Use Cases Questions
7. So what is a formula?
Similar to formulas in Excel, formulas derive their value from other fields, values, constants
and other variables present on the record. They can use functions and calculations to derive a
new value of some type.
8. So what does that really mean?
1. What is the data coming in?
2. What is my business logic?
3. How do I want my output to look?
At its most basic level, all formulas can be broken into 3 parts
9. Let’s draw it out…
Data In
Functions
Calculations
Operators
Constants
Etc.
Value Out
Business
Logic
10. Data In Business Logic Value Out
Score From 0 – 6 = Low
Score of 7 - 10 = High
Two Possible Values:
High or Low
Example: Low
Object: Case
Field: C-Sat Score
Example: Score = 6
Customer Satisfaction Example
11. How do I turn my business logic into an actual Formula???
13. Conditions Example Result
Chris D
Chris R
Score = 15
Score = 30
TRUE
FALSE
TRUE
FALSE
Name is Chris, Has Red Hair
Name is Chris, Has Red Hair
Score > 10, Score < 20
Score > 10, Score < 20
AND() Function
If X and Y are True, then True, else False
14. Conditions Example Result
Chris D
Chris R
Open, Expired
Open, Amount = $50,000
TRUE
TRUE
TRUE
FALSE
Name is Chris, Has Red Hair
Name is Chris, Has Red Hair
Closed = true, Expired = true
Lost = true, Amount = $0
OR() Function
If X or Y are True, then True, else False
15. If… Then Else
Eat
“Large”
“In Progress”
Don’t Eat
“Small”
“Past Due”
I am Hungry
X > 10
Due Date > Today
Satisfaction Score > 7
IF() Function
If X, then do Y, else do Z
16. CASE() Function
Look at X, if it’s A, do this, If it’s B, do this, else do this
My Mood
Opportunity Stage
Shipping Cost
Customer Health
Good, Be Nice
Prospecting, “Early”
California, $10
Bad, Be Mean
Negotiating, “Late”
Massachusetts, $15
Be confused
“Mid”
$5
Look at ElseOption 2, Value 2Option 1, Value 1
Good, Poor, Average, 😐
17. Chapter 3: Use Cases
🎵 Is this the real life, or is this just formula fantasy? 🎵
18. Data In Business Logic Value Out
If Open:
Calculate number of days
between current date and
created date
If Closed:
Calculate number of days
between close date and
created date
Integer representing the
age, in days of the
opportunity
A.K.A. just a number
Object: Opportunity
Field(s):
Created Date
Close Date
Stage
Business Case #1: Opportunity Age
Sales wants to determine the overall Age of an Opportunity since it was created. If the Opportunity is
closed, it shouldn’t increase the number of days.
19. Data In Business Logic Value Out
Open
Today - CreatedDate
Closed
CloseDate - CreatedDate
Integer representing the
age, in days of the
opportunity
Object: Opportunity
Field(s) API Names:
CreatedDate
CloseDate
isClosed
Business Case #1: Opportunity Age
Sales wants to determine the overall Age of an Opportunity since it was created. If the Opportunity is
closed, it shouldn’t increase the number of days.
20. Business Case #1: Opportunity Age
IF(
isClosed,
CloseDate – DATEVALUE(CreatedDate),
TODAY() – DATEVALUE(CreatedDate)
)
Sales wants to determine the overall Age of an Opportunity since it was created. If the Opportunity is
closed, it shouldn’t increase the number of days.
One of our Core Functions
Value if condition is True
Value if condition is False (the Else)
The condition…
21. Business Case #1: Opportunity Age
Open Opportunity
Sales wants to determine the overall Age of an Opportunity since it was created. If the Opportunity is
closed, it shouldn’t increase the number of days.
Closed Opportunity
22. Data In Business Logic Value Out
Priority of Low is Green
Priority of Medium is
Yellow
Priority of High is Red
One of three images*:
o Green Flag
o Yellow Flag
o Red Flag
*Even though this is an
image. You will return
TEXT
Object: Case
Field(s): Priority
Business Case #2: Case Priority
Cases are given a priority of low, medium or high that the support team uses to rank and prioritize all of
their Cases. They need a visual way to see Low/Medium/High cases
23. Data In Business Logic Value Out
Priority of low
"/img/flag_green.gif”
Priority of medium
"/img/flag_yellow.gif”
Priority of high
"/img/flag_red.gif"
Output one of these three
images
Object: Case
Field(s) API Names:
Priority
Business Case #2: Case Priority
Cases are given a priority of low, medium or high that the support team uses to rank and prioritize all of
their Cases. They need a visual way to see Low/Medium/High cases
24. Business Case #2: Case Priority
IMAGE(
CASE(
Priority,
"Low", "/img/samples/flag_green.gif",
"Medium", "/img/samples/flag_yellow.gif",
"High", "/img/samples/flag_red.gif",
"/s.gif"
), "Priority Flag"
)
Cases are given a priority of low, medium or high that the support team uses to rank and prioritize all of
their Cases. They need a visual way to see Low/Medium/High cases
Function: IMAGE(image url, hover text)
Core Function: CASE(Condition, Option 1, Value 1, Option 2, Value 2, Else Value)
Case condition. Tells the formula to look at the priority field
If Priority is low, use this image URL for the image function
If Priority is medium, use this image URL for the image function
If Priority is high, use this image URL for the image function
If Priority is none of the above, use this image URL for the image function
Hover text. 2nd argument for the image function
25. Business Case #2: Case Priority
Cases are given a priority of low, medium or high that the support team uses to rank and prioritize all of
their Cases. They need a visual way to see Low/Medium/High cases
26. Data In Business Logic Value Out
New Business over $50k
OR
Upgrade over $100k
OR
Renewal over $150k
Display a $$ image when
true, otherwise show
nothing
Object: Opportunity
Field(s):
Amount
Type
Stage
Business Case #3: Strategic Opportunities
Sales needs to see all “strategic” opportunities that haven’t been closed. This is any New Business
Opportunity over $50k, Upgrade Opportunities over $100k, and any Renewal Opportunity over $150k.
27. Data In Business Logic Value Out
Type = "New Business" &
Amount > 50,000
OR
Type = "Upgrade" & Amount
>100,000
OR
Type = "Renewal" & Amount
>150,000
/img/icon/cash24.png
Object: Opportunity
Field(s) API Names:
Amount
Type
isClosed
Business Case #3: Strategic Opportunities
Sales needs to see all “strategic” opportunities that haven’t been closed. This is any New Business
Opportunity over $50k, Upgrade Opportunities over $100k, and any Renewal Opportunity over $150k.
28. Business Case #3: Strategic Opportunities
IF(
AND(
IsClosed = False,
OR(
AND(ISPICKVAL( Type , "New Business"), Amount > 50000),
AND(ISPICKVAL( Type , "Upgrade"), Amount > 100000),
AND(ISPICKVAL( Type , "Renewal"), Amount > 150000)
)
),
IMAGE('/img/icon/cash24.png', 'Strategic Opp'),
Null
)
Sales needs to see all “strategic” opportunities that haven’t been closed. This is any New Business
Opportunity over $50k, Upgrade Opportunities over $100k, and any Renewal Opportunity over $150k.
Core Function #2
The condition…
Yet another Core Function…now we’re showing off!
New Business over $50k
Upgrade over $100k
Renewal over $150k
If above criteria is met, display $$ Image
Core Function #1
If above criteria is not met, display nothing
29. Business Case #3: Strategic Opportunities
Sales needs to see all “strategic” opportunities that haven’t been closed. This is any New Business
Opportunity over $50k, Upgrade Opportunities over $100k, and any Renewal Opportunity over $150k.
30. Data In Business Logic Value Out
Now you know it allWhen you walked in The Chris’s showed some tricks
The formula of this presentation…
31. So what did we learn???
Formulas make us look like Rock Stars (Images, #s, %s….)1
2
3
4
Functions are our friend (IF, AND, OR, CASE…)
Method to the formula madness (Data In, Business Logic, Value Out)
No Code!
35. Additional Resources
1. All icons available to use that are preloaded in your org
1. http://free-121d5f44d20-121d603d1c5-121ee2b8103.force.com/force2b/salesforceicons
2. Trailhead: Formulas & Validations
1. https://trailhead.salesforce.com/module/point_click_business_logic
3. Trailhead: Advanced Formulas
1. https://trailhead.salesforce.com/module/advanced_formulas
4. Chatter: Formulas - Help, Tips and Tricks
1. https://success.salesforce.com/_ui/core/chatter/groups/GroupProfilePage?g=0F9300000001ocs