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 About Ryan Goodman

Ryan Goodman has been in the business of data and analytics for 20 years as a practitioner, executive, and technology entrepreneur. Ryan recently created DataTools Pro after 4 years working in small business lending as VP of Analytics and BI. There he implanted an analytics strategy and competency center for modern data stack, data sciences and governance. From his recent experiences as a customer and now running DataTools Pro full time, Ryan writes regularly for Salesforce Ben and PactBub on the topics of Salesforce, Snowflake, analytics and AI.

Essential Salesforce Metrics & KPIs Guide

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.

  1. 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.
  2. 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.
  3. 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.
  4. Lead to Close Win Ratio – How many leads do you need to generate to close deals?
  5. 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.

  1. Deal Win Rate – How many fully qualified Sales opportunities are closed? This metric is used to measure the effectiveness of your sales team.
  2. 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.
  3. 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.
  4. Lifetime Value $ – For every customer, what is the total average value over time?
  5. 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

  1. 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.
  2. Clear and concise metric definitions will ensure your business stakeholders, Salesforce admins, and your data and analytics team are aligned.
  3. 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.

Exciting New Native Salesforce Snowflake Integration

Salesforce and Snowflake Integration

When it comes to optimizing your business processes and data analytics, Salesforce and Snowflake stand as two potent platforms, each with its own ecosystem of developers, stakeholders, and users. The Salesforce Snowflake Integration is an essential conduit that amplifies the bond between these two cloud platforms.

Salesforce and Snowflake Integration

Native Salesforce Snowflake Integration: A Milestone in Native Data Sharing

Earlier this week, Salesforce and Snowflake made a groundbreaking announcement: the general availability of native Salesforce data sharing for Snowflake,  via what is colloquially referred to as “BYOL” (Bring Your Own License). This is a significant advancement, especially for Snowflake users familiar with the benefits of zero-copy sharing, a core Snowflake feature. With this integration, gone are the days when you needed layers of additional software, services, and complex processes to bridge the two platforms. This is where the Salesforce Snowflake Connector comes into play, simplifying data access and queries between Salesforce and Snowflake.

Skill Enhancement through Certification Paths

Salesforce Data Cloud serves as a data hub orchestrating a wide range of business activities—be it CRM, marketing, or or any web/mobile activities. To encourage this, Salesforce recently launched its Certified-Data-Cloud-Consultant learning path. This will help Salesforce organizations readily find skilled professionals adept in Salesforce Snowflake Integration.

Salesforce Runs on Snowflake: Following the Leader

In a revelation that should add credibility and assurance to the Salesforce Snowflake Integration, Salesforce’s internal data and analytics have migrated to run on Snowflake. This shows Salesforce is not just advocating for the technology but using it themselves, setting the stage for rapid advancements in Salesforce and Snowflake connectivity.

Transforming AI/ML Workloads

The Salesforce and Snowflake partnership holds tremendous promise for accelerating the time-to-value from your Salesforce data assets. From curating data to deploying ML models, the integration, facilitated by the Salesforce Snowflake Connector, will enable enterprises to leverage their data in novel ways, including the utilization of advanced AI features. There are many first and third party powered solutions to weave your model deployment efforts.

Need Help Navigating these Waters?

We have been in front of Salesforce and Snowflake integrating analytics apps for years. We recreantly wrote the  Salesforce data synchronization to Snowflake Guide and can’t wait to extend this into DataCloud. We have an incredible partner network that can help you implement any Salesforce or Snowflake Cloud components (CDP, MarketingCloud, Tableau).

Schedule a meeting to learn more

Unlocking the Full Potential of MLOps with Snowflake and Predactica

Machine Learning Network

The Evolution of Machine Learning Platforms

Snowflake has rapidly emerged as the go-to platform for data-centric enterprises. Its ability to centralize and harmonize diverse data types makes it an exceptional foundation for any data strategy. Machine Learning Operations (MLOps) have matured significantly over the years, thanks to Platform as a Service providers like Amazon, Google, and Microsoft, who have developed comprehensive solutions that span the entire model lifecycle. However, a plethora of platforms and tools exist in a very crowded and confusing marketplace. So, what should a customer with Snowflake, a data and analytics team, and a desire to get models to production quickly and practically do?

Predactica: The is a Glimpse of the Future of MLOps in a Snowflake-Centric World

One name that should be on your list is Predactica.. This innovative solution is engineered to fit seamlessly with Snowflake. Predactica elevates MLOps by offering a natively integrated, end-to-end machine learning solution within Snowflake. Unlike other platforms that require disparate workflows and additional data pipelines, Predactica unifies these operations, making it the ideal companion for Snowflake-centric enterprises.

The result is a unified, agile, and compliant system that dramatically reduces the time-to-market for new models while ensuring their long-term reliability. Risk modelers and data scientists can now focus on the nuances of data, feature engineering, explanation and fine tuning.

Snowflake as Center of Gravity for Enterprise Data

With the introduction of Snowpark, Snowflake has also paved the way for native model deployment, allowing organizations to manage the entire model lifecycle within the data platform. This is done using the same tools, Python libraries, and workflows that data scientists, data engineers, and DevOps professionals already use. However, the rapid evolution of MLOps calls for a more streamlined, low-code solution that can natively integrate with Snowflake. This is where Predactica comes in to compliment or potentially replace external ML platforms and expand aspects of your MLOps to more contributors.

The Competitive Edge: Agility, Compliance, and Real-Time Monitoring

Another often-overlooked aspect of the machine learning lifecycle is monitoring model performance over time. Models, especially in credit risk, are not “set and forget.” They require ongoing attention to ensure they do not degrade and continue to make accurate predictions as market conditions and customer behaviors change. Predactica addresses this crucial need by offering built-in performance monitoring features. These tools enable teams to catch performance drift early, allowing for timely model adjustments and ensuring that your decision-making remains both agile and accurate.


The collaboration between Snowflake and Predactica represents a leap forward for organizations looking to democratize model development and accelerate speed to value.. Don’t take our word for it, setup a meeting or sign up for a trial and let us know what you think! Sign up for a Predactica Trial

Salesforce Document Management And Attachment Export Made Easy

Document Madness

As Salesforce has expanded its reach beyond CRM over the past 15 years, its document management capabilities have kept pace. Many businesses use Salesforce to attach various types of documents to specific records, right out of the box. With built-in support and compatibility with third-party tools like Docusign, Salesforce simplifies the process of uploading and streaming documents for end users.

But what if your document library grows and suddenly you find yourself needing to batch-process, transfer, or migrate these files? You might end up down a technical rabbit hole, exploring Salesforce’s data models, APIs, and a plethora of third-party tools, all without finding a straightforward way to extract your documents from

We had 4 key requirements that led us to create our own solution:

  1. We needed to select and tag a finite number of salesforce records for which documents existed
  2. We needed to select specific file types
  3. We required only the latest version of documents
  4. We needed to rename and prefix the files with data from the salesforce record and organize the files into sub folders.

How do we make Exporting Salesforce Documents Easy?

In my mind, simplicity is the level of effort and friction to get my desired outcome. In my case, I chose Azure DataFactory due to my experience and success building data pipelines. Configuring document migration in Azure Data Factory is still a few hours of work, but the level of effort to execute the migration is a single click. This article explores the complexities you need to understand before embarking on a Salesforce document migration.

Understanding Salesforce Attachment vs ContentDocument

When you’re in the trenches of Salesforce’s data architecture, trying to extract documents, you’ll encounter two main objects: Attachment and ContentDocument. These objects function differently when it comes to extraction, and understanding their nuances is crucial for a smooth operation.

Attachments are straightforward but limited. If your documents are stored as Attachments, you’ll likely need to perform a record-by-record extraction via Salesforce’s API. This is because each Attachment is directly tied to a single Salesforce record. It’s a one-to-one relationship, which makes extraction easier.

In contrast, ContentDocument is part of Salesforce’s more modern and robust Files architecture. It allows for file versioning and can be associated with multiple records via the ContentDocumentLink junction object. However, it’s not all smooth sailing here either; Salesforce restricts your ability to perform bulk queries and downloads of ContentDocument objects. You may have to employ more sophisticated methods including code or third party tools.

Overcoming Key Limitations for Managing Salesforce Document Metadata

Query All Files in Salesforce

Salesforce by default, limits your ability to query and extract metadata for all of your documents. To query all files, your salesforce admin needs to add a permission set. This article explains step by step how to Query All FIles to obtain a complete list of your documents.

With this data, you technically have all of the medata you need to start downloading files. The problem is that unless you have configured the ParentId to associate your documents with another object, you lose context to what that document is related to. In other words, you could download your vendor invoice but have no data to know what customer or deal that invoice belongs to.

ContentDocumentLink is the Missing Link

To connect your Salesforce documents to the parent record, Salesforce has a junction object called ContentDocumentLink. The problem is salesforce does not allow you to query and download all of the records in bulk.

To solve this problem, I employed Azure data factory to obtain all of my documents, select only the document records I care about, then one by one query and fill a database table with all of the ContentDocumentLink records. At this point, to make my life simple, I appended the additional data points I would use to ultimately rename my files and sub folders from the parent Opportunity record.

Bulk Download Salesforce Documents

With a database table containing all of my DocumentAttacmentLinks + ContentDocument records, built an Azure DataFactory flow that used the Salesforce REST API to GET each file 1 by 1 and loaded it into Azure Blob Storage. I could have loaded it into another storage solution like Google Drive but opted to keep it in Azure.

Are you Bulk Exporting Documents and Attachments?

We are always looking for better and faster ways to get data in and out of Salesforce. If you have another third party tool or process makes this faster and easier we would love to work with you!

If you need help offloading the effort to get your documents and attachments out of Salesforce, feel free to book a meeting with us.

Ultimate Salesforce and Snowflake Guide on Salesforce Ben

Salesforce Ben

This week Ryan released a guide for Salesforce and Snowflake on Salesforce Ben. Salesforce Ben is the leading independent community and authority on all things

Snowflake and Salesforce is a perfect marriage of cloud business applications and cloud data platform to turn data into information. Salesforce has built a powerful first-class integration within Salesforce Data Cloud that is the most advanced of any third party connectivity

If you are currently using Salesforce Data Cloud or Salesforce Tableau CRM this article is for you. Additionally, while at SnowflakeSummit2023, we saw some incredible Salesforce Data Cloud enhancements for Snowflake that will be game changing for enterprise cusetomers.

We can’t wait to write about upcoming zero copy feature from Salesforce to Snowflake. Included in our article is step by step tutorials how to integrate Salesforce with Snowflake to day. Should you have any questions how these capabilities apply to your enterprise or how Snowflake can advance your Salesforce analytics, we are here to help!

Snowflake and Microsoft Expand their Data and AI Partnership

Microsoft and Snowflake Logos

Snowflake and Microsoft, announced a press release at Snowflake Summit 2023 that they are expanding their partnership promising substantial advancements for data scientists and developers. This enhanced collaboration is set to seamlessly merge Snowflake’s Data Cloud with Microsoft’s Azure ML, extending its capabilities through the potent combination of Azure OpenAI and Microsoft Cognitive Services.

This strategic alliance means that Snowflake and Microsoft Azure shared customers will gain access to the cutting-edge frameworks of Azure ML, a streamlined process for machine learning development right through to production, along with integrated continuous integration and continuous deployment (CI/CD) processes.

But this partnership doesn’t stop there. Snowflake is setting its sights on creating even more meaningful integrations with a host of Microsoft offerings, aiming to elevate the user experience even further. These plans include closer ties with Purview for advanced data governance, Power Apps & Automate for simplified, low code/no code application development, Azure Data Factory for efficient ELT processes, and Power BI for intuitive data visualization, among others.

The end goal? To foster a seamless ecosystem that capitalizes on the synergies between Snowflake and Microsoft’s product suites, unlocking new possibilities and delivering unparalleled value to users.

At DataTools Pro, we couldn’t be more excited to see our favorite data platform, Snowflake, with new enhancements that make data management easier. Azure balances powerful data management with scalable cost that makes sense for our clients. Additionally PowerBI continues to advance its dominance for Business Intelligence. We have been working with Snowflake and Microsoft together for years and have built a toolkit that can help you jumpstart Snowflake and Azure integration.

Learn how to use Azure Data Factory and Snowflake Together

We have created free interactive step by step tutorials to help you get started!

Create a Snowflake Data Source in Azure Data Factory

Create a Data Pipeline to Connect Salesforce to Snowflake

Publish your ADF Pipeline, Data Sets, and Triggers

Create an ADF Scheduled Trigger


Azure Data Factory for Snowflake Articles

More Getting Started Tutorials