Salesforce CRM Analytics and Einstein Discovery Consultant Exam Questions 2025

A Look at the Certification That Puts Salesforce Analytics Skills Front and Center

The Salesforce CRM Analytics and Einstein Discovery Consultant certification is meant for professionals who are serious about using data-driven tools inside Salesforce to solve real business problems. Unlike generic cloud certs, this one focuses heavily on applying analytical logic within the CRM environment using both visual dashboards and predictive models. It’s not just about building pretty charts. You need to prove you can make insights useful across teams.

This exam isn’t made for beginners. It’s built for people who’ve had solid exposure to CRM Analytics tools. You’ll need to understand how to manage datasets, apply filters, design story-based dashboards, and use Einstein Discovery to make automated predictions. And it’s not only technical folks taking this cert – business analysts, data leads, and Salesforce consultants are all getting certified to bring better decision-making to the table.

Getting this certification tells employers and clients you’ve got the skillset to pull real value from data. It places you in roles like Salesforce BI consultant, data strategy lead, or analytics architect, especially inside organizations that are scaling their Salesforce operations. Many certified consultants also work freelance or contract-based, where this badge can push their rates significantly higher.

What to Know About the Structure and Content of the Exam

This Salesforce certification exam is crafted around hands-on, scenario-based logic. You’re not answering flashcard-type questions. You’re solving business problems using Salesforce’s CRM Analytics platform and Einstein Discovery tools. The structure of the test itself is pretty straightforward but requires solid prep due to the way questions are worded.

Take a look at how the exam breaks down:

There’s no officially published score requirement, but most candidates who pass report getting between 65 to 70 percent. That means knowing the topic isn’t enough – you need to move quickly and confidently through questions. With under two minutes per question, preparation focused on accuracy and recall is what really helps.

Domains That Are Heavily Tested in This Certification

The exam blueprint provided by Salesforce touches on several domains, each tied to core job responsibilities of an analytics consultant. While there’s no hard rule on weighting, the more practical the domain, the more it shows up in scenarios. This test is built around what consultants do day to day, so the domains reflect the reality of using CRM Analytics in projects.

Core topic areas include:

• Setting up datasets, dataflows, and recipes in the Data Manager

• Creating and optimizing dashboards with actionable components

• Applying security layers, including row-level access and app permissions

• Configuring Einstein Discovery stories and managing prediction models

• Evaluating model accuracy and adjusting based on use case needs

• Controlling sharing and user roles based on data sensitivity

• Managing solution deployment and best practices during project rollouts

This exam covers both technical and strategic application of analytics. You’ll get questions that test how to approach stakeholder requests, how to design for insight delivery, and how to ensure privacy while still showing the right data to the right users.

Why Some Sections End Up Being More Difficult

Candidates don’t always struggle because they lack knowledge. Many times, they get stuck because the exam mixes technical logic with business needs, and that forces you to think from both ends. The hardest parts of this cert aren’t just about writing filters or setting up predictions – they’re about figuring out what makes the most sense in a real scenario.

These areas tend to catch people off guard:

• Row-level security vs. dataset filters – knowing when each applies

• Difference between dataflows and recipes, especially for complex joins

• Picking the right bias correction or improvement method in Discovery

• Reading output from models and interpreting their weightage

• Assigning permissions across multiple users when roles overlap

If you’ve worked inside CRM Analytics before, you’ll likely recognize these pain points. If not, you’ll need to spend extra time practicing actual platform behavior so you’re not surprised during the test.

A Smarter Study Plan That Gets to the Point

Instead of grinding through every single Trailhead module, candidates benefit more from a focused plan that combines hands-on testing, targeted review, and concept linking. You don’t need to master Salesforce from top to bottom – you need to master the platform tools this cert covers and understand how to apply them efficiently.

Here’s a structured way to study:

Practical Study Workflow:

• Work directly inside Analytics Studio to build a few working dashboards

• Test creating both dataflows and recipes to process datasets

• Play with filter logic, especially multi-layered security controls

• Use the prediction builder inside Einstein Discovery and test its accuracy

• Map out user roles and permission flows based on scenario prompts

• Revisit Trailhead for domain summaries, but focus on use-case learning

This mix of learning by doing and revisiting specific explanations works better than trying to cram theory. When you’re confident navigating the UI and interpreting results, you’re ready for what the test throws at you.

Use Your Final Days Wisely by Prioritizing Speed and Accuracy

The last stretch before exam day should feel like review, not a crash course. This is when you stop collecting knowledge and start testing how fast and clearly you can apply it. Use these final few days to polish your weak areas and tighten your decision-making.

Final 3–5 Day Checklist:

• Evaluate 2–3 dashboards for UX clarity and business alignment

• Reread real-world project examples and note data transformation paths

• Review row-level security steps and permission boundaries

• Sketch out your process for handling a new dataset from start to dashboard

• Revisit Einstein Discovery terminology and prediction metrics

If any topic still feels shaky, work through one example hands-on. Application sticks better than reading, especially when under pressure. Test yourself under timed conditions so you know where you might need to slow down or speed up.