Seven Best Practices for Salesforce Analytics

By Miko DiGiacomo-Castillo | Updated November 13, 2020

Sales and marketing teams can unlock all of the benefits of Salesforce Analytics with these seven best practices. To maximize the easy-to-use AI tools for a business, consider intelligent market monitors that process the billions of external buying signals that matter.

What's inside this article:

Salesforce Analytics Is Approachable AI

Businesses of any size or industry can use Salesforce Analytics to uncover meaningful insights about their CRM data. By using a set of intelligent tools powered by AI technologies like machine learning, natural language processing, and computer vision, Salesforce offers its users the opportunity to learn more about their teams and clients. When sales and marketing teams have the best tools, they can perform their best work—but everyone from salespeople to team managers needs to know how to use these features correctly. Following a few best practices ensures that everyone is on the same page.

Transform Data Into Insights With Salesforce Analytics

Salesforce Analytics is particularly helpful for transforming data into insights that can be used to face complex business challenges. Managers can build flexible and advanced visualizations to better understand salespeople's performance. And clients receive more custom recommendations for their needs because salespeople understand exactly what to anticipate in the sales process. Suggestions like these are all based on previous deals and client interactions that the AI learns to build predictions from to offer intelligent sales insights.

The Seven Best Salesforce Analytics Practices to Know

Having the right AI tools is important. But that alone won't accomplish anything meaningful for teams or clients. Knowing the seven best practices to Salesforce Analytics is a good first step in unlocking the potential of using intelligent features in the sales process. They're listed below and the following sections go into more detail as to how teams could benefit from them.

  • List and rank priorities.
  • Empathize with the user.
  • Visualize to answer questions.
  • Find app structure through patterns.
  • Take advantage of unique capabilities.
  • Work with quality data.
  • Maintain through regular reassessment.

#1: List and Rank Salesforce Analytics Priorities

Before kicking off an AI analytics project, a business needs to identify, list, and rank its priorities. If this is their first time using Salesforce Analytics features, it's the perfect time to clearly isolate the AI goals of your business. The key to starting is finding the dashboards and models that can be built quickly and have the highest sales impact. This is imperative for showing the effectiveness of Salesforce Analytics and fully integrating it into the standard workflow.

Use Design Advice From Salesforce

Director and former Senior Product Designer of Salesforce Analytics UX, Eddie Picot and Anwesha Samanta shared design best practices to a group of trailblazers. They describe a well-functioning analytical app and dashboard design process as having three steps that continually move through each other. Empathy, ideation, and finally, communication and testing. When these intelligent tools can seem overwhelming, simple breakdowns like this help make sense of Salesforce Analytics.

#2: Empathize With the User

The empathy stage of the design process means identifying the audience, goals, and questions of whoever the analytical models will be used by. Thinking of the end-user allows the app designer to understand their intentions and desired goals. Picot and Samanta use the example of a CEO at a car company that wants to improve sales. With this in mind, several questions can be posed to get to what kind of features would be most beneficial in a Salesforce Analytics model.

Follow Up With Questions

The Salesforce duo goes on to share which kinds of questions appear once empathizing with the user and their goals. Included below are questions that a variety of salespeople and managers ask themselves throughout the year.

  • How much have I sold this year?
  • How much of each product have I sold?
  • Who are my top sales reps?
  • What are my most effective sales channels?
  • Where are we selling the most and the least?

#3: Visualize in the Ideation Step

The ideation process realizes the user's goals to begin visualizing how the above questions can be answered. This is a great time to invite others into the design process to get a range of perspectives on what can work. Intelligent sales tools rely on intuitive elements that quickly make sense to users—this is where a lot of that planning happens.

#4: Find App Structure Through Patterns

The next best design practice that Salesforce recommends is to communicate and test the ideas generated in the previous step. This is the time to organize existing questions into patterns. For the example of a car company, the designers realized that there were questions about sales and trends, then another group of questions about how to manage the team. With this in mind, it becomes clear that the app should cater to these questions.

#5: Take Advantage of Unique Salesforce Analytics Capabilities

Another best practice to keep in mind is to take advantage of the Salesforce Analytic features that only it can deliver. Since these intelligent tools work directly with the Salesforce CRM, it's incredibly easy to use client data and history. Salesforce is great at seamless integrations and businesses can search through the AppExchange marketplace to find additional sales tools to improve the analytic experience.

#6: Work With Quality Data

Every analytics project needs quality data—this data should be accurate, consistent, and reliable. As mentioned, one of the unique features of Salesforce Analytics is how seamlessly it works with other CRM products. This means that Salesforce users have unlimited access to the data they need to build meaningful analytical models. Users can also add intelligent market monitors to their dashboards to process all of the external data that may affect their business.

External Data Could Maximize Salesforce Analytics

It's worth expanding on the value of external data because of its importance to intelligent analytics. These are the billions of signals that have some impact on a business. For teams who want to ensure they're using the most efficient tools with the most reliable information, intelligent market monitors should be a top consideration. As mentioned, intelligent market monitors can be added directly to Salesforce tools like Einstein Discovery through the AppExchange marketplace.

#7: Maintain Through Regular Reassessment

The final best practice comes at the end of the design process. Analytical models and intelligent sales tools that are built need to be continually reassessed for their accuracy and effectiveness. Does it still answer the original questions asked? Are those questions still important?

Salesforce Analytics With and Without Data Scientists

The magic of Salesforce Analytics and these seven best practices is that it can all be done with or without a data scientist. For larger organizations with a dedicated data scientist, Salesforce offers excellent tools that help organize data so that they can quickly get to work with the most intelligent features for building custom models. For small businesses with tighter budgets and smaller teams, Salesforce is still an excellent solution because it comprehensively guides users into building custom models that offer the same intelligent insights. No matter the size of the team, there will always be a best-fit set of AI sales tools to benefit the business.

Know the Right Salesforce Tools and How to Use Them

As mentioned, sales and marketing teams need the right tools to get their work done. With these seven best practices, now they can learn how to use these special features to unlock the most intelligent insights. Both the tools and the know-how are integral components to building a smart sales process that is easy to navigate amongst complex data sources.

Salesforce Analytics Can Go Further

Salesforce Analytics offers a set of tools that allow CRM to go further and with these seven best practices your team will know how to unlock all the benefits. Consider adding intelligent market monitors to the platform so that your team is best equipped to uncover hidden opportunities and target accounts in net new markets. At Aptivio we understand how to harness the power of AI tools to fuel efficient growth. Our Aptivio Intelligent Market Monitor for Sales creates simple dynamic digital sales playbooks from billions of buying signals to maximize your CRM investment.

Our impactful action cards generated by analyzing 150 proprietary signals from billions of external data points can transform the performance of expert salespeople. With seamless integration directly into your CRM and business intelligence platforms, Aptivio is the missing link to creating a digital sales machine. Ready to learn more? Get started for FREE today!

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