Tableau and CRM Analytics – Better Together

I have had a great many conversations over the past few years regarding the distinctions between the various reporting tools and platforms offered by Salesforce. This has been the source of much confusion for the Salesforce and Tableau ecosystem. 

For example, I manned a demo booth at the Sydney Salesforce World Tour a few weeks ago. I spoke with at least 20 customers, and perhaps 80% of conversations revolved around the distinctions in functionality and usage between Tableau and CRM Analytics (formerly known as Tableau CRM). Also, a blog post that I published on the subject proved to be very popular, attracting well over 11,000 views. 

Most people assume that the question of CRM Analytics (CRMA) and Tableau is one of OR, rather than AND. That is, CRMA and Tableau are treated as competitive solutions, rather than complementary solutions – people assume that it is a zero sum game. However, this is a common misunderstanding. Tableau and CRMA do, indeed, play very well together.  

I have worked with many customers using both Tableau and CRMA, both as a consultant and a Tableau Solution Engineer, including a global communications business, a state government body, a leading recruitment platform, and a premier accounting platform. These organizations gained tremendous business value from the deployment of both CRMA and Tableau. In my role as the Practice Lead of a Salesforce and Tableau partner business, I had many in-depth discussions with key stakeholders at such organisations, from data analysts to the CTO of a multi-billion dollar global business. Their challenges around data and analytics were no different to hundreds of others that I have spoken with over the years – they were drowning in data when they should have been swimming in insights!

Drawing upon my experience working with Salesforce and Analytics since 2016 as a business analyst, consultant, and solution engineer, I have a few thoughts regarding the value of Tableau and CRMA working together in harmony. I offer my informed opinion on the following points of interest: 

  1. Which reporting tool fits who?
  2. The benefits of CRMA AND Tableau, not OR
  3. How does this work in the real world?
  4. Why can it be difficult to use both platforms?
  5. What is the recipe for success with a synergistic approach?

1. Which reporting tool fits who? 

When speaking to customers since Salesforce acquired Tableau in 2019, the most common question that arises is,

What is the difference between Tableau and CRM Analytics?

Now, it is unwise to draw a hard line of demarcation between these platforms, as there is significant overlap in capability, and they continue to rapidly evolve. 

However, to provide a baseline of understanding to work from, here is a brief comparison based upon my experience:

Salesforce reports and dashboards

  • Operational reporting
  • Your “go to” option for a quick win based upon real-time Salesforce data
  • Reports and dashboards are quick to configure
  • Salesforce admins can manage the analytics

CRM Analytics

  • Salesforce process intelligence
  • You want to quickly embed and action analytics in Salesforce
  • You’re looking for easily embedded AI 
  • Inherit Salesforce security and sharing


  • Enterprise B.I. for data exploration
  • Your insights will be shared among Salesforce and non- Salesforce users
  • You need flexibility around how the BI platform fits in with the business technology stack

Platform comparison summary slide

I think it is clear that there is room for two or three of these to work together in a synergistic manner to take advantage of the incredible power that they provide to maximise business value from the variety and diversity of data sources that are available. 

2. Better Together – The benefits of CRMA AND Tableau, not OR

Why are Tableau and CRM Analytics so much better together? Here are six reasons, and I imagine there are many more: 

A. You get the best of both worlds – the powerful exploration and analysis of Tableau plus the embedded and actionable insights of CRMA

CRMA infuses intelligence into the Salesforce user experience – you go from this:

To this:

These insights are embedded in the Salesforce user flow of work and actionable on platform. 

What Tableau then offers is powerful, simple and visual exploration and analysis of business-wide data, available to any user, governed at scale, and deployable anywhere. Therefore, CRMA + Tableau = The best of both worlds!

B. Business users can go quickly and easily from data to insight to action regardless of where the data is stored and where the user lives and works

CRM Analytics is all about the Salesforce user experience, enabling the user to go quickly from data to insight to action without leaving CRM – goodbye swivel chair and spreadsheets! Tableau extends this capability outside of Salesforce to all users anywhere with all data. For example, a customer service manager could receive actionable service insights within Salesforce, embedded on the case or account page, whereas a CFO or finance manager can review business performance from a collaborative dashboard that draws data from multiple sources including a cloud data warehouse and on-premise finance system. 

C. Superior business outcomes with faster time to value and higher ROI from using the right tool for the right job 

Using the wrong tool for the job is disastrous, even if that tool is best-of-breed. For example, take the best chainsaw in the world and try to cut an intricate pattern in a fine piece of wood – you won’t get a great result! You need a small jigsaw for such detailed work, or else the outcome will be poor, regardless of the skill of the craftsman. 

The same principle applies in the world of data and analytics. Can you embed Tableau dashboards in Salesforce? Yes. Can you deliver business intelligence across your organisation using CRM Analytics? Yes. However, you’ll get a superior result if you use the platforms for their intended use – CRMA surfacing intelligence for your Salesforce users, and Tableau delivering analytics across your organisation in a variety of deployments. 

D. Predictions and insights from ML and AI deliver business value through an analysis and action framework that is flexible and scalable

Public research shows that 80-90% of machine learning (ML) and artificial intelligence (AI) objects never make it into production. That is, most ML and AI initiatives never deliver on the promise of enabling business users with predictive, actionable insights. There are many reasons for this, but one of the most important is that the business lacks an analysis and action framework that is flexible and scalable. Without this framework, deployment and scaling of the predictions to end users is doomed to failure. 

CRMA and tableau provide this flexible and scalable analysis and action framework – CRMA within Salesforce, and tableau across the organisation. 

E. A joint approach enables customers to deploy insights and analysis anywhere and leverage their existing data environment

Between CRM Analytics and Tableau, customers can take data from anywhere and deliver insights to anywhere with a solution architecture that is flexible, secure, and scalable. 

To deploy analytics broadly across your organization, you need to have the confidence that your choice meets you where you are today and that it will continue to work when your technology decisions evolve in the future. That’s why CRMA and Tableau are designed to fit, rather than dictate, your data infrastructure, data ecosystem, and business workflows so that you can leverage your existing technology investments and expertise.

F. A robust end-to-end analytics solution that provides a flexible governance methodology to deliver analytics at scale

Tableau and CRMA enable you to deliver true self-service analytics at scale with a highly configurable, manageable, and customisable platform that enables the responsible use of trusted and governed data by everyone in your organisation, regardless of deployment type – fully-hosted SaaS, public cloud and containers, on-premises, or native in Salesforce. 

3. How does this work in the real world?

There are many examples that I could share with you regarding the success of Tableau and CRMA in a real-world use case. However, for the sake of this article, I will share one: 

Revenue Intelligence and Forecasting

Olivia is a Sales rep at Acme Inc. She wants to see a breakdown of her opportunities by forecast category and her pipeline over time. Salesforce AI is predicting that out of her $1.2m commit, she will likely lose $805k and win $397k. AI takes away the dependence upon gut feel regarding what big deals are likely to close, and then guides where time is spent. 

Olivia can easily drill down into pipeline deals that Acme is predicted to lose using her embedded dashboard, then look at the table and see details around these deals at risk. She then adds these opportunities to a marketing campaign using a bulk action:

Olivia’s biggest focus right now is the Omega Inc deal that she received a Slack alert about – she can’t afford to lose this one. Here she has a 360 degree view into the 335k Omega Inc deal. Every important metric related to this deal can be found in this page, driven by comprehensive data that has been connected and harmonised by Salesforce Data Cloud. 

Salesforce AI helps Olivia to mitigate the risk of losing deals, predicting that there is a 41.1% chance of winning this deal. The Leading Causes area explains the ‘why’, explaining that they are competing against Dopple Ganger and the deal compete team has not been engaged. 

The AI is also giving Olivia recommendations on how to improve the likelihood of closing this deal. For example, it is suggesting she engage with the Deal Compete team and extend the quote expiration date. With just one click, Olivia engages the deal compete team. 

Olivia engages the deal compete team with one click, using the power of Salesforce automation. This is the guided selling Nirvana that businesses dream of!

Now, Karen is the head of revenue operations at Acme Inc. She wants a deeper understanding of company revenue and profitability across business units, teams, products, regions and countries. However, the COGS data required to calculate profit, and a lot of other contextual data, is contained in a variety of data sources. Historically, the process of analysing revenue and profitability across the board has been very slow, painful and manual, involving many spreadsheets and a great deal of effort. 

Tableau and Data Cloud have changed all that, providing Karen and her colleagues with a comprehensive, up-to-date view of company-wide revenue and profitability. Also, the complex machine learning algorithms built by their data science team no longer go to waste, as they are deployed in Salesforce analytics and provide valuable predictive insights to the leadership team.

Karen shares the Q4 insights and predictions with her team securely via the cloud ahead of their upcoming revenue call. Karen and her leadership team collaborate via tableau Cloud and make decisions based upon current, complete data.  

4. Why can it be difficult to use both platforms?

Confusion around solution design and platform utilisation

Users are often confused about where to go for what insights – SF reports, CRMA, or Tableau. They can easily lose trust in data and create their own source of truth to work from, resulting in an ungoverned, confusing mess. 

Overlap of effort with duplicate, conflicting deliverables

A clearly-communicated and well-governed strategy and framework are necessary to prevent the inevitable overlap and inefficiency that can so easily result when delivering across two diverse and complementary platforms. 

Misalignment on which team owns what initiatives, plus projects are often totally opaque to other teams 

For example, I know one enterprise business whose data science team asked about what Einstein Discovery could do for them in relation to churn – being completely unaware that the sales ops team (SF owners) had successfully deployed Einstein Discovery and CRMA in Salesforce to great effect!

Challenges regarding systems architecture and data pipeline

Here are a few examples of the challenges I have seen:

  • “For non-Salesforce data, do we:”
    • Bring it directly into CRMA using native connectors?
    • Bring it directly into CRMA using an integration layer (e.g. Mulesoft)?
    • Bring it into CRMA from our data warehouse (DWH)? 
  • “For analysis of SF data, do we:”
    • Perform all Salesforce (SF) analysis in CRMA, which is consumed in SF, and export SF data to the DWH for combination with other data if required? 
    • Export SF data to the DWH, combine and transform using an ETL tool, then bring the combined dataset into Tableau (non-SF users) and SF (SF users)? 
    • Export SF data to the DWH, combine and transform using an ETL tool, then bring the combined dataset into Tableau for all users – ditch CRMA except for AI&ML. 
  • How can we best use the Tableau → CRMA and CRMA → Tableau connectors? 
Data governance and management across platforms and frameworks

For example, I have seen a lack of clarity regarding definition and calculation of metrics across platforms and assets. Imagine the confusion when a metric is calculated differently in Salesforce, CRMA and Tableau…!

Misalignment of platform and data with use case results in poor business outcomes, both for BI and AI

Again, you need the right tool – and the right data – for the right job. 

5. What is the recipe for success with a synergistic approach?

How can you maximise your odds of success when deploying both tableau and CRMA?

An agreed and unified strategic approach is absolutely critical

This must include clarity regarding:

  • Overall business systems architecture
  • Data pipeline
  • Ownership of projects and data
  • Data sharing and governance
  • Best practice for where and how Tableau, CRMA SF are used
The business analytics solution and strategy must be owned by one leader

They must ensure that: 

  1. The unified strategic approach is agreed to and adhered to in practice
  2. Both IT (Tableau) and Operations (CRMA) master effective, low-latency collaboration. 
  3. No rogue projects are allowed – freedom with a framework
Solution discussions with business stakeholders must be product/platform agnostic, focused on solving problems and delivering outcomes

Stakeholders are easily confused by product and platform discussions, especially when naming and branding changes occur. Also, product and platform comparisons should take place at a later stage during deep-dive technical solution discussions. 

Establish, publish and maintain a clear and comprehensive data glossary/dictionary

This will mitigate the risk of a lack of clarity regarding definition and calculation of metrics across platforms and assets. 

Now What?

I hope that this article has provided you with some thoughts, ideas and recommendations that will form the basis of a constructive and creative discussion within your organisation. 

Please feel free to contact me here with any questions or comments. 

As far as next steps go, may I suggest:


  1. Why do you need CRM Analytics when you have reports and dashboards?
  2. Are you confused about Einstein, Tableau, and CRM Analytics? Read this
  3. Einstein and CRMA Trailmix
  4. 200+ blogs on CRM Analytics and Einstein Discovery
  5. Learning Tableau 2022
  6. Creating Actionable Insights Using CRM Analytics

Please Note:

These views are entirely my own and in no way represent those of my employer, Tableau, a Salesforce company.  

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