Unlock Your Sales Potential with Sales Analytics Essentials

By: Stephan Miller - Guest Contributor on February 14, 2023

Sales are the backbone of any business. Without sales, a business could not survive, let alone grow. This is why monitoring and analyzing sales performance is an important part of ensuring the success of a business. With an effective sales analytics process, businesses can identify patterns, trends, and areas for improvement, which will allow them to make informed decisions to increase sales and revenue.

As a small or midsize business sales operations leader, it’s important to understand the key performance metrics that can help you forecast and plan for the future of your business. But even when you are monitoring the most important KPIs, your analytics process may fall short because of the challenges of poor stakeholder engagement and low data quality.

What is sales analytics?

Sales analytics is the process of collecting, analyzing, and interpreting data in order to generate insights about a business’s sales performance. This can include metrics such as revenue, conversion rates, customer demographics, and more.

Sales analytics is especially relevant for small or midsize businesses (SMBs) with limited resources because with it they can make data-driven decisions that allow them to compete with larger enterprises. By understanding key performance metrics, SMBs can identify patterns and trends that can help them optimize their sales efforts.

For example, analyzing customer demographics can help a business understand which customer segments are most profitable and how best to target them with sales efforts. By monitoring conversion rates, a business can identify areas of its sales process that need improvement. Businesses can also use sales forecasting to anticipate future demand and plan accordingly. This can help a business make informed decisions about inventory, staffing, and other resources and avoid overstocking or understaffing.

What are the essential sales analytics?

Sales analytics can change the growth trajectory of a business for the better. But sales analytics teams often struggle to deliver the impact they promise because of common challenges, including poor stakeholder engagement and low data quality.

Here are some of the keys to a successful sales analytics program that will help ensure your analytics provide true and useful insights.

Improve data quality and trustability

Many organizations find themselves trapped in a vicious cycle of poor data quality. When system data is incomplete or incorrect, teams lose trust and interest in the results. This low adoption, in turn, results in less motivation to maintain data quality. This perpetual cycle makes widespread adoption of sales analytics in the business close to impossible.

Instead of cross-functional efforts to improve data quality and trust, a business will often resort to relying on anecdotal evidence and gut instincts. This approach limits the potential impact of sales analytics and the business’s ability to make strategic decisions based on the insights they discover.

To break this cycle, organizations must prioritize data governance and data literacy in order to improve data quality, trust, and the adoption of analytics.

Develop analytics that meets the true needs of all commercial functions

As buyer preferences evolve along with the business landscape, collaboration among business teams needs to grow. The CRM data provided by sellers that once provided valuable insights on buyer behavior and intent may not be enough anymore. To stay competitive, sales analytics teams must understand the information needs of the larger organization and share insights with other teams.

One way to achieve this is ensuring that business leaders support transforming the sales analytics function to keep up with these changes. This can be done by designing a clear vision for sales analytics that takes into account the information needs of each department and how they can work together to achieve the goals of the business.

Drive more cohesive decision making

Sharing analytics data among business functions is essential for driving more cohesive decision-making within an organization. This can be achieved by:

  • Understanding the type of insights each department needs and creating processes to gather the relevant data

  • Creating targeted analytics and identifying areas for improvement for each department

  • Providing training and resources for understanding and using the data

  • Encouraging cross-functional collaboration and communication

Overcome incomplete integration of channel interaction data

As B2B buyers continue to shift towards digital and self-service channels, suppliers need to have a more holistic view of their customers’ interactions than ever. However, some suppliers struggle to do this because of siloed systems and databases that span different functions within the business.

This lack of integration makes it difficult for business teams to rely on data insights. Instead, they depend on non-technical stakeholders or citizen data scientists to extract information from disconnected signals. This can make it hard for sales managers to effectively coach their sellers on individual deals or overall performance when the only easily accessible data comes from the CRM system.

To keep up with buyer preferences, businesses must integrate their systems and data so they have a complete view of their customer’s journey and can find and interpret signals accurately and quickly.

Overcome gaps in data literacy that limit ROI on sales analytics

As new technologies continue to emerge, it’s becoming easier for the average person to access and analyze data on their own. However, just because they can access the data doesn’t mean they understand it. As more data sources are integrated into a business, the metrics that result from them only become more diverse.

This makes data literacy more important than ever before. Everyone does not need to be an expert in advanced analytics algorithms, but they need to understand the data sources and constructs, as well as how to use a particular metric or insight. By having a better understanding of data, stakeholders will know where analytics can be most useful, collaborate more effectively with other departments, and help the business make better decisions.

What are the key features of essential sales analytics?

When it comes to analyzing data, business teams have similar needs and requirements, whether they are gathering insights from sales, inventory, or customer information. Most analytics software systems have certain core features in common:

  • Data collection: The process of collecting and organizing data following every transaction is crucial. It is time-consuming to manually record and store the details of each action, some of which may not even be valuable in the long run. Analytics software helps to save time by automating this process.

  • Reporting: With analytics software’s reporting capabilities, it’s easy to store and access data for future reference and analysis, often with a single click. Historical data can be used to conduct predictive analytics, which can help identify potential trends, vulnerabilities, and opportunities in the future.

  • Dashboards: Dashboards make it easy to understand insights by presenting them in easy-to-digest, interactive visual formats like charts, graphs, and tables. Some analytics software offers mobile dashboards for easy access to sales, customer, and inventory information from anywhere.

What kind of business should consider sales analytics essentials?

Sales analytics is a powerful tool that can help businesses of all sizes make data-driven decisions that will improve their business. However, as the business landscape changes and preferences shift, many businesses may find that their current analytics solution isn’t providing the insights they need. This means their sales analytics strategy must evolve to keep up.

Businesses struggling to keep up with evolving buyer preferences and aren’t quite sure how to close the gap between their CRM data and the actual needs of their stakeholders should look into sales analytics.

Prepare your business for tracking essential sales analytics

If your current sales analytics strategy doesn’t completely meet your business needs now, it can be improved. Here are some steps you can take to change it for the better:

  1. Identify stakeholders and business needs for sales analytics: A successful sales analytics vision must account for the goals of both internal and external stakeholders. Identifying these stakeholders and their needs can help to guide the strategy and find areas where you need to invest in analytics.

  2. Ensure executive support for transforming the sales analytics function: Do this by creating a clear and compelling vision that addresses the needs of all commercial functions within the organization. Use it as a guide to align the sales analytics strategy with the goals of the company and drive cohesive decision-making.

  3. Build and communicate your analytics vision and value proposition: This can be done through one of three common approaches: positioning sales analytics as a utility that removes data management and analysis roadblocks, as an enabler that provides access to data sources for specific use cases, and as a driver that enables quick access to data sources for discovery purposes.

  4. Set strategic objectives to establish a formal data governance strategy: To ensure that the data governance strategy is relevant, it should be directly linked to the goals and challenges of the business functions it needs to coordinate with.

  5. Establish a dictionary of sales metrics and centralize resources: Enterprise-wide data literacy can be achieved when all consumers of data and analytics share a common understanding of the data and metrics that drive the business. To achieve this, sales operations leaders should create a dictionary of standard commercial metrics, including information on data sources, calculation rules, input data quality considerations, and update frequency.

  6. Initiate a cross-functional data literacy program: By regularly assessing their organization’s data literacy, sales operations leaders can discover which functions need help and develop a curriculum that addresses gaps in knowledge.

  7. Develop a multi-year roadmap for sales analytics technology: Analytics software is always evolving. While that doesn’t mean a business should adopt every new change, it should develop a process to identify and prioritize use cases where new technologies offer a potential impact.

Drive future success with sales analytics

Sales analytics is a powerful tool that can help businesses make data-based decisions that drive success. However, as the business landscape continues to evolve and buyer preferences shift, it can be difficult for some SMBs to keep up. By investing in data governance, data literacy, advanced analytics technology, and other best practices outlined in this article, you can bridge the gap between stakeholder needs for data-based insights and the current state of data and analytics.

To learn more about the analytics tools that will help you accomplish these goals, visit these resources: