Salesforce - DataTools Pro

Process hacking Gmail and Salesforce with Zapier And OpenAI

Posted on 2024-12-05 - 12:53 am by Ryan Goodman

My desire to have a simple, streamlined GMail and Salesforce flow goes back 12 years. One of my guilty pleasures as a tech and data geek is automating repetitive, mundane tasks. However, as a business operator with limited hours in a day, there are two conditions I evaluate to determine if a problem is worth automating:

Impact of addressing the problem: If I want to make an impact through automation, I need to see a 3x return on time per month. In other words, if I invest 10 hours tinkering and automating something, it should generate 30 hours of time savings per month per person. This is a high barrier that prevents me from solving the wrong problems.

Pain the problem causes: If can’t get my desired return on time, I rate how much pain the problem causes? By “pain” I refer to mental or even emotional pains that you experience at work… Stress, frustration, cognitive overload, and context switching. It accumulates and manifests as friction between people and process.

When GMail and Salesforce friction reached a level 5 pain…

On a busy day with 20 plus email threads, I found myself fumbling around GMail, Excel and Salesforce rather than communicating and advancing my business. I decided to vent on Linked-In wondering if anyone else in my immediate network has the same pain point.

The root of the problem

When I get an email from someone who does not exist in my CRM, I have not found a simple mechanism to get someone from email into Salesforce as a contact or lead. After 30 minutes of research I found that this problem may be solved with an Einstein tool.

To Salesforce credit, once someone exists as a lead or contact in my CRM, the native extension from Salesforce is extremely useful.

My Zapier and OpenAI solution explained

How does the GMail extension, Zapier and ChatGPT work together?

Process the email signature and determine name, email, phone, geography, company, title.
Enrich the data by classifying the title to role or group (seniority)
Check to see if the person exists in the CRM comparing the email to contact
- If the email exists as a contact, is it the same person (first name / last name) or “something close”. I put this in quotes because historically this was a human judgement call, but in 2025 it is an LLM judgement call for me.
Check to see if the person exists in the CRM as a lead using the same process
Insert the new record if it does not exist
Append only missing data points if they are missing

Creating my first Chrome Extension with ChatGPT

With no working knowledge of how to build a chrome extension, I opened chat GPT and provided the following prompt. An hour of tinkering with 25 iterations back and forth with ChatGPT and the solution was complete.

Building my Zap for GMail and Salesforce

I have been working with Zapier for at least 10 years now. I am drawing from lots of experience automating my data flows in Salesforce . I put that experience to work creating a zap that achieved most of my solution design.

Letting the LLM do the heavy lifting

Zapier has a great interface to use ChatGPT to process data to produce a consistently structured output. If you have built wrapper apps with ChatGPT like I have, you know this was challenging in the early days. Now, I have ChatGTP process the email and with specific instructions, process and produce the output.

The Results

The result of my tinkering is complete removal of pain communicating in Gmail. I use my simple chrome extension with Zapier and OpenAI every day to handle intelligent additions of contacts into Salesforce.

Day-to-day, this tool has been incredible. At this point I am saving 2-3 hours a month entering data as I have continued to scale my outreach efforts with DataTools Pro. I have not expanded on my MVP or shared it until recent demos raised interests.

For now, if you want to test the solution or need help setting it up or want to explore adapting this for other scenarios like creating service tickets or Outlook integration, feel free to contact me or better yet email me so I can show you how your email flowed into my CRM! ryan@datatoolspro.com

New Azure DataFactory template makes Salesforce to Snowflake Pipelines fast and cost-effective

Posted on 2024-12-04 - 1:29 am by Ryan Goodman

Azure DataFactory for Snowflake and Salesforce

We built our free Azure DataFactory template to help you build your data pipelines from Salesforce to Snowflake in 5-30 minutes. The value of data is not realized by collecting and moving it. The value of data is realized when you transform it into information. Analytics insights and attributes for automation is the objective and reason why you invest in a data warehouse like Snowflake. That is why we have built our free data pipeline templates to reduce the level of effort to get your data ready for analysis up to 90%! View our documentation to lean how

In 2023, we launched the first version of our template tagging it as a “5 min data lake with Azure DataFactory”. Adoption and feedback led us to close 2024 with an upgraded version of our template alongside our new DataTools doctor service and our revised Snowflake rapid adoption service to help our customers extract value from data faster.

Download our Azure DataFactory Template Now

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Why we build Salesforce to Snowflake pipelines with Azure DataFactory?

Fast, cheap and easy rarely happens in technology, but the Azure team, without a massive marketing blitz or fanfare created a very solid product for moving data between enterprise data sources in to Microsoft data platform and Snowflake.

We use Azure DataFactory pipelines to move massive volumes of data daily for customers who have invested in Azure. They save thousands of dollars per month while getting enterprise grade data extraction and migration.

When do we turn to other solutions than DataFactory?

We stick to technology tools that are flexible, practical, and well adopted. DataFactory in particular we like deploying with customers who are running MS SQL or Snowflake in Azure. When it comes to data transformation and ETL patterns, DataFactory does offer a no/low code Spark based Flow builder. However, depending on customer needs, scale, and team makeup, we do recommend alternative solutions that is catered to the existing processes, investments, team makeup and roadmap. We are always on the lookout for new, streamlined data pipeline solutions.

What’s Next for our Azure DataFactory template?

We are actively working on client projects for MySQL and MS SQL version of our template. Contact us for more details

Salesforce data pipelines to Snowflake free template

Video Tutorial

1. Create Data Connections

Connect Azure Data Factory to Salesforce.com (New 2024)

Connect Azure Data Factory to Snowflake

2. Create Data Sources

Create a Snowflake Data Source in Azure Data Factory

Connect to Salesforce Lead and Account Object with Azure ADF

3. Move Data Between Applications

Create a Data Pipeline to Connect Salesforce to Snowflake

4. Publishing and Administration

Publish your ADF Pipeline, Data Sets, and Triggers

Create an ADF Scheduled Trigger

What’s New in our Salesforce to Snowflake Pipelines

This week, we rolled out a long overdue update for our free Azure DataFactory template that makes extracting Salesforce data into Since 2023, there have been a lot of changes to Azure DataFactory, so we have rolled out a long overdue update and upgrade.

From our version 1.0.1 release notes:

New meta data staging process and table called “SFDC_METADATA_STAGE_TEMP” that feeds SFDC_METADATA_STAGE
Support for new field detection and addition (enable append fields)
New parameter AppendFields will insert new fields when detected
New parameter SnowErrorHandling allows for configurable error handling to skip error rows, skip file, or throw an error.
New MetaData field called “Status” that allows for “Disable” attribute that will ignore fields from being synchronized.
Update to Salesforce metadata request that supports compound fields by default like FirstName, LastName, Street, City, etc.
Pre-install check – End to end flow checks for existence of the metadata object
Added status variables to determine results for each pipeline for easier debugging
Schema insert and updates managed via merge by object.field ID
Changed field from ID to DurableId Salesforce field to Snowflake SFDC_METADATA_STAGE “ID”

New DataTools Pro fights Salesforce zombie reports

Posted on 2024-10-25 - 4:30 pm by Ryan Goodman

Just in time for Halloween, we have new tricks and treats for DataTools Pro. Jam packed with integrations and a brand-new Reporting and Dashboard management tool, you can take control over reports, and clean up Salesforce zombie reports that are clogging up your Salesforce org.

Solving for Salesforce Report Deluge

Our latest DataTools Pro release includes a brand new Salesforce Report and Dashboard management tool. We recognize as data and analytics professionals that Salesforce has an incredible self-service reporting and dashboard function. However, managing and maintaining reports over time is a task that challenges the most experienced admins and analysts. Our team approached this problem with the goal of getting hundreds or even thousands of Salesforce reports under control.

Common Problems with Salesforce Zombie Reports

Aggregating data from different objects for same metric.
Multiple versions of truth.
Redundant copies of reports.
Outdated metric definitions.
Lack of tagging and business context.
No visibility on what reports and dashboards are utilized.
Over-used filters removing data from analysis.
Abandoned reports still accessed and used.
Lack of controls resulting in changes to reports used for key metrics.

Governing Salesforce Reports and Dashboards with DataTools Pro

To combat zombie reports, and make it easier to manage day to day Salesforce report and dashboard lifecycle, we have created a new tool that provides:

1. Relating reports and dashboards to business context. Enhanced tagging and search reports by line of business, topic, and status.

2. Manage Report and Dashboard lifecycle to declutter Salesforce. Bulk disposition reports with a status so you can search and filter your report repository.

3. Provide a lens for admins into Report and dashboard utilization. Search and tag reports dashboards based on last viewed – making deprecating reports easy.

4. Help focus from activities to metrics and goals. Connect relationships between reports, metrics and KPIs using DataTools Metrics Glossary.

New DataTools Pro 3rd Party Integrations

In addition to our new Report and Dashboard management, we have been beefing up our native integrations, making it easier to integrate existing metrics glossaries or push your metrics glossary where you and your colleagues already work.

Zapier

The DataTools Pro Zapier integration provides the ability to stream your metrics glossary. Zapier is the ultimate conduit to connect any cloud application containing metrics into DataTools Pro. Soon, we will offer bi-directional connectivity through Zapier so you can utilize DataTools to help centralize and manage metrics with with hundreds of potential integrations to link and distribute metrics across your enterprise. Our new Zap is currently available in beta.

Coda

The DataTools Pro Coda bundle ensures your Salesforce, data, analytics, and business teams have immediate access to your metrics glossary. Coda is the perfect knowledge and AI brain to deliver metrics and relationships.

Need Help Eliminating Salesforce Zombie Reports?

We will continue to add more DataTools Pro integrations into 2025 including other CRMs like Hubspot. We look forward to getting early feedback and hope to collaborate with you to make zombie reports obsolete! If you need help mapping out your metrics and analytics governance plan, we are always here to help! Schedule a free consultation with us anytime

Why taking a SQL Course still matters in a world with AI

Posted on 2024-08-25 - 11:03 pm by goodmangro2dev

This week, Salesforce Ben released new SQL course for Salesforce that aims to introduce a SQL learning path aimed at professionals who work in Salesforce. My goal for the course was to provide technical training from the perspective where data literacy and translating business questions is the driver to write SQL. In my course, I lean into LLMs, specifically ChatGPT, and even introduce how I use ChatGPT to assist debugging. A the end, anyone who takes the course will learn their way around Snowflake and have a lab built for funnel analytics.

Large Language Models (LLMs), are make it easier than ever to write SQL and Python. Some have made bold claims that learning how to code wont be necessary in the future. Despite advances in LLMs, SQL remains a vital skill in the data-driven world.

View Course

Writing SQL without LLM

Lots of time consumed troubleshooting and debugging SQL
Reverse engineering other’s SQL
Manually typing documentation
Understanding how functions work
Formatting data to use in expressions
Understanding data structure and meta data

Using LLMs while Writing SQL

Paste your code and the error and let LLMs point out syntax issues or how to correct errors
Break down and explain SQL structure and purpose
Auto-document SQL
Relate functions to your existing knowledge
Auto-prepare expressions with correct syntax
Explain meta data structure

What you get out of learning SQL course for Salesforce

1. General understanding – Fundamental SQL skills

AI tools like LLMs can write SQL queries, but without a solid grasp of SQL fundamentals, it’s challenging to evaluate or optimize those queries effectively. SQL is more than just a query language; it’s about understanding how data is structured, how relationships are built, and how to extract meaningful insights from databases. SQL gives you the foundation to translate questions into queries and ensures that you’re not just a passive consumer of AI-generated code.

2. Contextual Awareness

While LLMs are powerful, they might not fully grasp the nuances of your specific database environment or the business rules that govern your data. Learning SQL allows you to tailor queries to your unique context, ensuring the results are accurate and aligned with your business needs. This contextual understanding is something that AI, despite its advancements, can’t fully replicate.

3. Collaboration with Data Teams

SQL acts as a common language in the data world, bridging the gap between business professionals and technical teams. When you understand SQL, you can communicate more effectively with data engineers, analysts, and other stakeholders. Understanding the data structures needed for analytics also increases your awareness as you alter the Salesforce data model. At the end of the day, having SQL in your toolkit makes you a more valuable contributor.

4. Troubleshooting and Optimization

Even the best AI tools can generate inefficient queries that may impact system performance. By learning SQL, you gain the ability to troubleshoot, optimize, and refine these queries, ensuring they run efficiently and deliver the desired results.

5. Future-Proofing Your Career

SQL skills continue to be in high demand, with job opportunities in this field projected to grow significantly over the next decade. As DataCloud takes off, employers will value SQL proficiency, as it’s a core skill for data cloud related roles when you need to “bring your own data warehouse.”

More about SQL course for Salesforce

What You’ll Learn:

Data Query Language (DQL): Focus on querying and analyzing data.
Salesforce Integration: Learn how SQL concepts align with Salesforce SOQL.
Practical Skills: Hands-on exercises to build familiarity and proficiency.

View Course

Salesforce Data Cloud is a Game Changer

Posted on 2024-06-22 - 4:01 pm by Ryan Goodman

Salesforce Data Cloud is here to help enterprises move from being transaction centric to information based. Recording sales, processing orders, and tracking customer interactions through various processes is what helped Salesforce grow to one of the world’s largest enterprise software companies. Typically, Salesforce is one node in a complex network of loosely integrated applications and services. Modern data warehousing and data lakes have served as a hub to bring disparate data sources together for analysis. Data Cloud aims to solve integrating disparate data for analysis and action.

Salesforce Data Cloud

Activating data into assets into decisions and actions across systems is hard work. Salesforce Data Cloud offers a comprehensive suite of tools to create relationships not only be tween disparate systems, but also data lakes and data warehouses. Salesforce is leaning on modern standards and learning into Snowflake, DataBricks, and Google Cloud. Acknowledging and integrating existing data cloud investments is a big part of Salesforce’s vision to “bring your own data lake.”

So far most of the messaging and examples for activating Data Cloud are facilitating better data-driven customer experiences . It sounds great in writing, but the journey for enterprises will require true cross discipline and organization collaboration.

CRM Transactional System of Record

CRM systems have traditionally served as the transactional system of record, capturing customer interactions, sales transactions, and service requests. While valuable, these transactional records often provide a limited view of customer relationships and preferences. Salesforce Data Cloud expands on this foundation by integrating additional data sources and enriching customer profiles with contextual insights, behavioral data and centralizing many customer signals.

How Salesforce Data Cloud Organizes Data Graphs

Salesforce CRM organizes a relational model that connects accounts, contacts, and activities. Data Cloud creates a data graph that establishes connections based on various objects, including purchase history, communication channels, social interactions, and demographic data. Learn more about Salesforce Data Graph Structures

This graph structure is powerful when implemented, but integrating disparate data into Data Cloud requires the same expertise, thoughtful design, and deep understanding of data / meta-data management.

Salesforce Data Cloud Connects to Disparate Business Applications and Data Clouds

One of the strengths of Salesforce Data Cloud lies in its ability to connect to disparate systems meta-data all within a common and familiar Salesforce cloud. Putting structured and semi structured data from business applications, cloud tools, and other data lakes are possible. Whether it’s CRM platforms, marketing automation tools, social media channels, e-commerce platforms, Data Cloud integrates data from diverse sources into a unified data graph. This integration eliminates data silos and timely data extraction and management processes to gain visibility needed to understand data relationships.

Shift from Single Centralized System / Source of Truth

Coupled with innovative “zero-copy” data integration via “bring your own data lake”, Data Cloud is primed to integrate many clouds like Snowflake, Databricks, and Google Cloud platform without the expensive and slow bottlenecks that can occur with big data and dealing with terabytes of information. The ultimate 360-degree view of a customer has been the battle cry for every business software product for years. Only a small fraction of enterprises that embarked on the journey have publicly shared their success and have also produced sustained growth numbers to match the success story.

Key Features of Salesforce Data Cloud

Data Governance

Data governance is another critical aspect of Salesforce Data Cloud. With robust security measures, data encryption, and compliance tools, organizations can ensure data integrity, privacy, and regulatory adherence. Additionally, advanced analytics and AI for deploying models, predictive analytics, and AI-driven insights are pivotal to putting data to action.

Integration with Salesforce Ecosystem

A key strength of Salesforce Data Cloud lies in its seamless integration with the broader Salesforce ecosystem. This integration extends to Salesforce CRM, Marketing Cloud, Service Cloud, and other Salesforce products, creating a unified data environment. Furthermore, integration with third-party applications and APIs enhances functionality and flexibility, allowing organizations to customize data workflows and processes according to their specific needs.

This unified ecosystem streamlines data management, enhances collaboration across teams, and accelerates time-to-insight. Whether it’s enriching CRM data with external sources, automating micro-segmentation marketing campaigns based on event and time sensitive insights, or leveraging AI-driven analytics for sales forecasting, the integration capabilities of Salesforce Data Cloud empower organizations to extract maximum value from their data assets.

Data Governance and Compliance

In heightened data privacy concerns and regulatory scrutiny, Salesforce Data Cloud prioritizes data governance and compliance. Robust security measures, including data encryption, access controls, and audit trails, ensure that sensitive information remains protected at all times. Compliance tools help organizations adhere to industry regulations such as GDPR, CCPA, HIPAA, and more, mitigating compliance risks and enhancing trust with customers.

Additionally, the growing emphasis on ethical data practices, transparency, and data privacy will shape the evolution of data cloud platforms. Salesforce’s commitment to data ethics, trust, and security positions Salesforce Data Cloud as a trusted partner in navigating the complexities of modern data management.

Challenges and Considerations

While Salesforce Data Cloud offers immense value in concept, organizations may encounter certain challenges during implementation. These challenges may include data migration complexities, meta-data mapping, integration with legacy systems, and user training requirements. Addressing these challenges requires careful planning, stakeholder buy-in, and a phased approach to deployment.

Getting Started with Salesforce Data Cloud

The future of data management revolves around agility, intelligence, and scalability. Salesforce Data Cloud is well-positioned to address emerging trends such as AI-augmented everything, machine learning, and real-time data processing. The convergence of data integration, analytics, and AI capabilities under one integrated platform is certainly attractive for enterprises vested in Salesforce.

Curated Salesforce Data Cloud Resources

Salesforce Data Cloud represents could represent a complete paradigm shift in how you think about Salesforce as a data integration platform. Conversely it could simply provide an opportunity to displace existing, expensive tooling that have been streamlined with Salesforce Data Cloud integrations and partnerships. Building and refining your strategy to transition from transaction-centric to information-driven solution should point to measurable results first. Your path to success starts with a clear data, analytics, and AI strategy.

Our team at DataTools Pro is thrilled to see how early adopters embrace Salesforce Cloud not only to displace previous technology investments, but also take a leap forward in customer service and engagement.

Top Salesforce Data Cloud Resources for Learning

Continue Reading Top Salesforce Data Cloud Resources for Learning

Salesforce Journey Map Tips for your Salesforce Marketing Cloud Strategy

Continue Reading Salesforce Journey Map Tips for your Salesforce Marketing Cloud Strategy

Exciting New Native Salesforce Snowflake Integration

Continue Reading Exciting New Native Salesforce Snowflake Integration

Ultimate Salesforce and Snowflake Guide on Salesforce Ben

Continue Reading Ultimate Salesforce and Snowflake Guide on Salesforce Ben

Salesforce Entity Relationship Diagrams Makes Visual Storytelling Simple

Posted on 2023-12-16 - 6:02 pm by Ryan Goodman

One of the most useful tools in the admin or data professional’s toolkit are Salesforce entity relationship diagrams. Understanding conceptual and physical data models is difficult enough. A business stakeholder responsible for sales, marketing, and revenue typically has little interest in the Salesforce data model. When information coming out of Salesforce is incorrect, sometimes you need to revisit your existing data model.

Bringing Salesforce admin, data and business professionals together, sometimes a conceptual entity relationship diagram is very useful to algin to the same level of understanding to make the right forward decision. To help explain and prioritize data work for a client, I recently used our entity relationship diagram to pinpoint and explain the root cause of reporting problems.

Real World Lead Attribution Use Case with Salesforce ERD

Lead attribution is one of the most important and challenging aspects of running your “got to market” stack. To do so requires attention to data consistency and quality. One of our customers had an ambitious and practical approach to connects Leads, Accounts, and Opportunities with a junction object called “Vintage”. The ability to automatically track a lead vintage (when the lead enters the funnel), is very useful to report funnel conversion and lifetime value. Reports for revenue and lifetime value by lead source is important for planning and budgeting independent of campaign activity.

To communicate the issue, I used the following DataTools Pro ERD Diagram to demonstrate the additional data relationships that were maintained. Additionally, I explained how existing reporting requirements could easily be achieved without the vintage object. The following is the exact picture I painted to describe the specific linkage that was effectively broken in the Lead Attribution Funnel.

Resolution with Empirical Proof

There were some objections to remove the Vintage object. During the meeting, I clicked to demonstrate where those data relationships are maintained. It was very effective to satisfy most objections in real time.

There was one objection we had to clear to deprecate the Vintage object. Using historical data analysis I discovered the Vintage objection use case occurred 1 in every 500 opportunities which made it a true edge case. Sometimes you engineer a solution to account for anticipated scenarios that rarely occur in real life; this was one of those cases.

The consensus was the vintage object and all of the processes needed to maintain it could be deprecated. Rather than trying to accomplish detailed lead attribution from the lead object, campaign and campaign members are used to capture clients that enter the funnel multiple times from multiple channels.

How to Build a Salesforce entity relationship diagrams for Free

Salesforce provides an out of the entity diagram for Salesforce administrators to visualize and manage the Salesforce data model. I find them useful for administration but not for sharing and distribution.

Build better, easier to visualize ERDs with DataTools Pro: Our desire to build a better ERD for Salesforce led us to create ERDs. Here are some of reasons you may want to check out the free diagraming capabilities we offer:

Simpler, minimal design
Exportable to single page document (SVG)
Connected directly to Salesforce
Custom views aligned to business topics and tech modules.

Get Started

Learn More

Your 2024 Tableau Salesforce Integration Guide

Posted on 2023-10-15 - 5:58 pm by Ryan Goodman

In this guide, we will walk you through the process of setting up Tableau Salesforce Cloud using the latest and greatest native integrations. Tableau Cloud natively integrates with Salesforce for enhanced security and access as the two clouds have become tightly knit together. In addition to the nuts and bolts, we will focus on key use cases how Tableau can provide valuable insights beyond standard Salesforce reports and dashboards. Tableau’s capabilities for deeper analysis, data manipulation, end-user ad-hoc analysis, and access to diverse data sources make it a powerful complement to Salesforce’s offerings.

Tableau Cloud Setup

Setting up Tableau cloud is as simple as signing up and provisioning an account through the online setup form. Once provisioned you can immediately start connecting and building.

Salesforce SSO for Tableau: Security and Access

Salesforce cloud natively supports Salesforce for user access and authentication. This allows you to extend your user management and access into Tableau so you are not needing to duplicate work.

Simply check “Salesforce” so when you invite users they will need to utilize their Salesforce username and password. If you use Multi-Factor Authentication MFA with the Salesforce authenticator app, you do not need to perform any additional configuration for it to work.

Embedding Tableau inside of Salesforce

For Salesforce organizations, Tableau should be a seamless experience that resides side by side with standard Salesforce.com dashboards. To accomplish this goal, we typically utilize the Tableau lightning component. With Tableau cloud, you can utilize the “Default Authentication type for Embedded Views”, ensuring a secure and seamless experience for end users.

The best user experience is one that reduces friction. We typically embed dashboards inside of Lightning pages and also make use of tabs to isolate Salesforce dashboards and Tableau dashboards side by side based on topic.

To allow embedding of Tableau inside of Salesforce as of Winter 24, simply go to Setup and enable Tableau embedding.

Tableau for Salesforce Use Cases

Before embarking on a Tableau Salesforce its important to understand key uses cases where implementing Tableau makes sense above and beyond standard Salesforce reports and Dashboards.

Deeper analysis

When we refer to “depth of analysis” we mean taking a single subject and exploring history, relationships, and paterns that impact the subject.

For example, if you see that yur lead to opportunity conversion rate is lower than expected, you may ask questions related to sales rep activity including speed to lead, number of calls, number of reps to leads and other ratios. When building Tableau dashboards and supporting reports, you can drill and explore these relationships over time with greater ease and relate them together.

More flexibility to slice and dice data

Slicing and dicing data in many cases requires analysts or in the world of Salesforce reports saving data to Excel. Tableau was born and designed for visual exploration of data where you can filter, drill and modify the subject of your analysis with.

End User Ad-hoc analysis

Salesforce provides an amazing ad-hoc reporting capability, granting business professionals with the power to produce powerful reports. While the report developer has a full fledge reporting solution, end consumers of the report are limited to basic filtering. Tableau on the other hand provides end user ad-hoc analysis for changing dimensions, drilling, and constraining information.

Access to more data sources for analysis

Salesforce reports and dashboards are limited to the data available inside of Salesforce. Tableau on the other hand opens the door to connect more data sources with Salesforce.

Connecting Tableau to Salesforce Data

Tableau provides a native Salesforce data connector, allowing direct access to Salesforce data objects. This is quite useful for real-time access to Salesforce data, or static extracts that harness the full power of Tableau data.

Native Salesforce Connector

Unfortunately, the Tableau integration with Salesforce data is imperfect. Using the standard Tableau connector for Salesforce prevents Salesforce formulas in the results. This limitation has long existed as an enhancement but is not obvious.

Working with Data Time Fields

Small variances in metrics can occur when using DateTime fields as a result of data extractions rendering in UTC instead of your local time zone.

Connecting Tableau to Salesforce Data Cloud

With the recent release of Salesforce Data Cloud, Tableau has a new modern approach to data access that bypasses some of the traditional limitations. We will cover this topic in detail with an upcoming post!

Plan your Salesforce Tableau Initiative

Need help planning and validating Tableau is the right fit for your Salesforce based analytics or simply need an “Analytics First” perspective on your Salesforce org? Setup a free consultation with our team and ask about our rapid adoption blueprint.

Essential Salesforce Metrics & KPIs Guide

Posted on 2023-09-25 - 12:32 am by Ryan Goodman

Futuristic Salesforce Metrics and KPIs Dashboard

Salesforce metrics and KPIs are important tools to define how you will manage and monitor your Sales and Marketing efforts. Metrics and KPIs playing a crucial role in aligning strategies with business goals. In this article, we dive into vital Salesforce Lead and Opportunity Pipeline Metrics, emphasizing the importance of consistency and clear definitions. Whether a stakeholder, Salesforce admin, or a member of a data analytics team, here, you’ll gain insights, answers to common questions and examples.

5 Salesforce Lead Metrics you Should be Tracking

While different organizations and industries have varying definitions for leads, prospects, and customers, the following metrics are designed for organizations where lead generation and handoff occurs inside of Salesforce.

Qualified Leads Generated – How many qualified leads are delivered to sales? The qualification definition will vary per organization, as some use MQL (marketing qualified leads) and others use SQL (sales qualified leads). Having the qualification definition also helps identify un-workable leads which creates a feedback loop to improve lead generation channels.
Lead Generation to Response Time – How fast are you making contact with leads after a prospect is delivered to your sales organization? Turn time for some businesses are measured in hours but for some they are measured in minutes.
Lead Conversion Rate – How many leads need to be worked to generate a deal with revenue potential? Many organizations convert leads and create opportunities different stages of the Sales cycle. We recommend measuring from a key, well defined the point in your Sales funnel that is unlikely to change over a long period of time.
Lead to Close Win Ratio – How many leads do you need to generate to close deals?
Cost per Lead and Closed Won – What are your marketing campaign costs relative to lead generation and deal closure? For organizations that track their marketing campaigns and spend inside of Salesforce, this metric can be tracked using Salesforce campaigns. Not all organizations track marketing spend inside of Salesforce unfortunately.

5 Salesforce Opportunity Pipeline Metrics you Should be Tracking

It goes without saying the count of won opportunities, revenue and margin are important and common sales metrics. Here are 5 additional metrics that you can look to for inspiration.

Deal Win Rate – How many fully qualified Sales opportunities are closed? This metric is used to measure the effectiveness of your sales team.
Outbound Activities to Close – Measuring how many phone calls, emails, and SMS are required to close deals is effective at aggregate to measure top and bottom performers and understand globally what it will take to move customers through each stage to a win.
Average Deal Size – Understanding your average and potential median deal size are important to understand market shifts, targeting, sales effectiveness and is typically a driver for forecasting and predicting future deals.
Lifetime Value $ – For every customer, what is the total average value over time?
Churn Rate – For customers that are won, how many of them churn at the end of their service period or no longer make second purchases within a specified timeframe?

3 Salesforce Metric Tips for Success

Consistency of your metrics and KPIs are measured over time is most important. If the definitions change often, your ability to effectively use the metrics diminishes. Ensure you use clear definitions for points in your sales process.
Clear and concise metric definitions will ensure your business stakeholders, Salesforce admins, and your data and analytics team are aligned.
Ownership of every metric helps ensure accountability not only for monitoring. This also helps ensure changes in definitions and assumptions have a point person for approval.

Common Salesforce Metric and KPI Questions

What is a Salesforce Metric

A Salesforce metric measures performance over time where Salesforce is typically the system of record where the business process and transaction occurs. Salesforce metrics like sales revenue or lead conversion rate are created, calculated and measured with reporting inside of Salesforce or using 3rd party reporting and dashboard tools directly integrated with Salesforce.

What is a Salesforce Metric vs KPI?

A Salesforce metric tracks measurements over time while a KPI or Key Performance Indicator typically has not only a definitive target, but also a timeline and linkage to business goals and objectives.

A KPI should indicate the current and historical performance (Sales revenue is a common KPI for sales), while metric could help identify the leading indicators that influences sales (outbound calls, talk time).

How do I manage Salesforce metrics?

Many organizations simply manage Salesforce in Excel or word, which is fast and easy but requires a tremendous effort and cross functional ownership. There are a number of free solutions that help automate and streamline collecting, organizing and sharing metrics and tracking changes over time.

How do I ensure consistent Salesforce metrics?

Consistency in naming and consistency in measurement are two very common challenges within Salesforce. Tracking and managing aliases or synonyms for metrics over time is important but the measurements and application of metrics in reports needs to be consistent.

How do I design Salesforce KPIs?

The best advice is to ask your business leadership first what is the objective or goal that is most important? From there what are the top 3 things we should do to reach that goal? That is the framework for your KPIs. Setting a target and timeline to achieve the target in many sales organizations are monthly or quarterly. The most important thing is not to get hung up on terminology. If you are setting and agreeing to measurable goals and outcomes, that is most important. Consistency in terminology and approach is most important.

What is DataTools for Salesforce Metrics?

We built DataTools Pro to help inventory, manage, and track implementation of metrics and reporting inside of Salesforce. Bringing the same techniques we use for large scale enterprise Business Intelligence solutions, we have paired it down to make it very simple for Salesforce users.

Inventory metrics
Track aliases / synonyms for metrics
Align dashboards and reports to metrics
Detailed definitions and ownership
Align metrics to topics and lines of business

How do I create Salesforce Metric and KPI Dashboards?

Salesforce provides powerful and flexibility reporting and dashboard tools that ship standard with Salesforce. As the sophistication of your reporting and tracking requirements grow or complexity of calculations increase you may need a solution like Tableau (owned by Salesforce) or one of the many powerful point solutions.