Conquering the power of sales data analysis: A guide to success

Data is at the heart of informed decisions in a dynamic, changing business environment

Liam Costello by Liam Costello on June 25, 2020  |  13 minute read
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The sales process of any business generates a considerable amount of data, particularly among those with outside traveling sales teams. From customer metrics to information about lead generation, the average sales manager has a lot of metrics and key performance indicators at their fingertips.

When sales decision-makers take the time to analyze this information, they can open up a world of opportunities to improve sales performance and drive more revenue. Sales managers can use data-driven insights to support their decision-making while taking into account the actual performance of their individual sales reps.

However, gathering, analyzing, and leveraging sales data can be a complex task without the right expertise and tools in place. Managers need a way to keep track of sales territories and spot emerging trends.

When done successfully, sales data analysis can help you balance workloads and opportunities among your sales reps, successfully meet service level agreements, and drive revenue growth for your business. By harnessing the power of data, businesses can uncover patterns, identify opportunities, and optimize growth strategies.

This blog will explore the art of conquering sales data analysis and how it can lead to unprecedented sales success.

What is sales data analysis?

These days, businesses in every industry use data analysis to access in-depth insights. For sales leaders, that involves an array of different key performance metrics, from marketing and prospecting to creating opportunities and closing deals.

In its ultimate guide to sales metrics, HubSpot identified three levels to which sales metrics could be applied to: a single sales rep, the wider sales team, or the company as a whole.

These metrics enable managers to get the best idea of individual, team, or business performance. Combined with the right analytics platform, they can show patterns of growth, areas in need of improvement, expansion opportunities, and more.

"Sales metrics help track progress toward goals, prepare for future growth, adjust sales compensation, award incentives and bonuses, and identify any strategic issues," HubSpot explained.

How sales data analysis drives revenue

Conducting high-level sales data analysis is vital to the bottom-line success of any business. But, you'll need to evaluate several types of data. Analysis of sales records is just one piece of the puzzle. The level of analysis needed to drive good decisions requires time, effort, and data-visualization tools like a good mapping software platform.

The result gives you access to in-depth sales analytics that can support bottom-line improvements. Let's examine a few of the ways sales decision-makers can leverage their sales data analysis to drive profitability and growth:

1. Establish or realign sales territories

With the help of mapping software, managers can use their sales data analytics to create new territories or review existing territories.

Sales territory mapping software makes territory design easy

Sales territories can be broken down in a few different ways, including by geography. This ensures each field sales rep can effectively and efficiently serve the clients in their territories. What's more, when new leads and opportunities arise, clearly defining territories makes it instantly clear which sales rep is responsible.

Using sales territories also improves customer service. Better service means higher customer satisfaction ratings, which can ultimately increase the lifetime value and revenue.

Overall, businesses that build and realign their territories based on their sales data analysis have reported a 2-7% increase in sales numbers, proving the effectiveness of this approach.

2. Sales leaderboards motivate employees

Team leaderboards can show where each sales rep stands in relation to their peers. Managers can create these leaderboards for weekly, monthly, and quarterly sales figures. Using this data, management can reward top-performing reps and incentivize all team members to drive improvement.

These sales leaderboards are critical tools for today's sales teams. And they are just one of the ways decision-makers can leverage their sales data analysis to drive revenue. Sales leaderboards can also help managers improve their sales team resource allocation, ensuring each sales rep is assigned to the most appropriate sales territories.

We'll delve into this and other uses for sales data analysis a bit more below. First, we need to understand the types of metrics sales team managers and business leaders need to track in order to enable these actionable insights.

3. Visualize data in meaningful ways

When managers don't have the right analytics and visualization tools, it inevitably affects sales. Without these tools, they can't use data analysis to make meaningful decisions about account prioritization and resource allocation.

Sales team mapping software is designed to help managers visualize and understand their data. The result: more insight into the business and higher sales. For instance, managers and sales teams can leverage powerful features to view:

  • Sales team geographic coverage: A map of the key areas that the sales team currently covers can help managers identify new regions for expansion. eSpatial's mapping software allows users to see the geographic coverage of each sales rep individually, so decision-makers have the best understanding of their traveling sales teams' boundaries and responsibilities.
  • Account and sales lead overlays: Mapping software can also overlay geographic coverage maps with the locations of current accounts and prospective sales leads. In this way, managers can quickly and easily identify their highest-value accounts, as well as areas that need more attention from the sales team.
  • Heat maps: This data visualization tool is one of the most effective for sales data analysis. With a robust mapping software tool, users can view regional heat maps or hot spot heat maps. Using these visualizations, decision-makers can get the best understanding of their regional market performance, high and/or low-performing sales territories, location-based sales trends, and even clusters of existing customers. For example, managers can find regions with opportunities for new customer acquisition by looking at customer clusters.
Sales data analysis using a regional heatmap

If you want to maximize the usefulness of sales data analysis, tools like the above provide numerous ways to turn statistics into action.

4. Improve resource allocation

Mapping software is also a considerable advantage when allocating resources and balancing workloads. It can help you see where you're over- or under-distributing valuable resources through sales data analysis. An example of this would be eSpatial's Territory Manager. It offers balancing, which can show when one sales territory has more clients than the others. Managers can use this information to better balance workloads. That way, every sales rep has a fair shot at the leaderboard and is at a lower risk of burnout.

What's more, mapping software combined with good sales analysis can enable sales leaders to assign the right sales rep to each sales territory based on their individual strengths. For example, particularly challenging territories can be given to senior sales reps with more experience. Prioritizing and targeting workload and employee resources in this way can help maximize revenues in each territory.

5. Engage in what-if analysis

The greatest strategies arise from using historical data to predict future outcomes. So, before making any adjustments to field sales strategy or established sales territories, managers can also engage in what-if analysis. These exercises help decision-makers view the impact of their proposed changes to ensure that adjustments will provide an increase in revenue or other objective improvement.

6. Meet SLA requirements

When sales reps consistently meet service level agreements (SLAs), it helps build a track record of success and good customer service. Consistently meeting SLAs can also foster upselling and cross-selling to existing customers. Customers are more likely to increase their business with you once they've seen that your company follows through on promises.

Tracking SLA requirements is key, as is mapping the data you need to plan for them. When you build SLA minimums into all your sales territory planning, it's easy to meet your commitments to customers.

7. Consistent review and improvement

Finally, all of the above elements allow managers to review their sales team's performance and associated metrics regularly. With this data, decision-makers can identify areas of improvement, adjust their sales territories, and craft new SMART objectives to help drive sales further.

Conducting a thorough analysis of sales data helps you figure out what's working, what's not, and precisely how to amplify your overall performance.

How to analyze sales data: A step-by-step guide

Ready to get started? Here's a quick overview of how you can start analyzing sales data.

1. Collecting quality data: The foundation of success

Conquering sales data analysis starts with collecting quality data. Ensure that your data sources are reliable, up-to-date, and comprehensive. Use customer relationship management (CRM) systems, sales reports, and other tools to gather relevant information. Focus on using clean and timely data to eliminate inconsistencies and inaccuracies, laying the foundation for accurate analysis.

2. Defining key performance indicators (KPIs): Analyzing the right metrics

Identify and define the key performance indicators (KPIs) that align with your sales and business goals. Clear KPIs, such as conversion rates, customer acquisition costs, or average deal size, provide a roadmap for analysis. These metrics become the benchmarks against which you measure the success of your sales efforts.

3. Utilizing advanced mapping software: Making data work for you

Invest in advanced mapping software to unlock the full potential of your sales data. It offers powerful features for visualizing and interpreting data. You can create interactive maps, conduct deep dives into specific metrics, and gain insights that drive strategic decision-making.

4. Segmenting data for targeted insights: Personalizing the approach

Segmenting your sales data allows for a more granular analysis, revealing hidden patterns in large datasets. Understand your customer segments, product categories, or geographic territories to tailor your sales strategies. Personalizing your approach based on segmented data can optimize sales and marketing efforts and improve productivity.

5. Continuous monitoring and iteration: Adaptability is key

Sales data analysis is not a one-time task; it's an ongoing process. Establish a culture of continuous monitoring and iteration. Regularly review and update your KPIs, refine your data collection methods, and adapt your strategies based on the insights gained. An iterative approach ensures that your sales organization remains agile and responsive to changes in the market.

6. Cross-functional collaboration: Breaking silos

Conquering sales data analysis requires breaking down silos within your organization. Several teams within your company possess useful data for sales analysis purposes — not just the sales team. There is no better tool to foster cross-functional collaboration between sales, marketing, finance, and other departments than mapping software. By sharing maps and insights and collaborating on data-driven strategies, you create a holistic approach to sales optimization that considers the entire customer journey and business operations.

7. Empowering your sales team with actionable data: Maps built for success

Equip your sales team with the skills and knowledge to interpret and leverage data effectively. Or take a shortcut and share a map with your critical data. Seeing is believing. Your team can make informed decisions, identify market trends, capitalize on opportunities — and do it intuitively using map visualizations. They are better positioned to understand customer needs, personalize interactions, and close deals more efficiently.

Important sales metrics businesses should track

When it comes to sales data analysis, choosing what to track is half the battle. So, what sales data should you monitor?

1. Sales revenue

Focus on trends. Month-on-month or year-on-year growth. How are the numbers trending, positive or negative? Each review will prompt critical questions like "What is the reason behind this trend"?

2. Sales lead metrics

As well as tracking the number of leads in your pipeline, focus on the conversion rates. You may experience a growth in the number of leads (which is good) but a decline in the conversion rates (a reason to investigate further). Calculating the likelihood that today's leads turn into future sales is essential.

Here is how:

  • # New leads per month - 100
  • # MQLs (marketing qualified leads passed to sales to work on) - 50
  • # SQL's (sales have qualified leads to the next stage - 10
  • # New opportunities (or deals) - 5
  • # New closed sales deals - 2

My conversions

  • Lead to MQL is 50% (50/100)
  • MQL to SQL is 20% (10/50)
  • SQL to Deal is 50% (5/10)
  • Deal to closed sales deal is 40% (2/5)

3. Average time in each stage

This KPI measures productivity by tracking the time it takes for potential customers to become paying customers. You can combine it with metrics like lead conversion rate and total sales opportunities for a complete sales pipeline overview.

To calculate it, add the total time taken for all lead conversions during a specified period and divide it by the number of lead conversions during that period. Most CRM software will calculate this for you, so no heavy lifting is involved.

4. Sales activity metrics

Tracking sales activities is essential, as they can be a crucial predictor of pipeline growth, but be wary of encouraging the wrong behaviors.

Yes, tracking the number of emails and sales calls can be helpful, but what's most important are the outcomes of those emails and calls. Discovery calls and demos are the critical results you want to focus on. They are predictors of future pipeline growth.

5. Sales pipeline value

Pipeline value is essential, but remember that it is only one metric. As forecasting is notoriously inaccurate, use this one wisely. Far too often, pipeline values are inflated and overly optimistic. As a sales manager, you'll want to focus on the hard facts.

6. CLV

Another critical metric is the customer lifetime value (CLV). There are a few ways to calculate this metric. Still, the result provides sales managers with a better understanding of how much the company stands to make with a particular client throughout the relationship.

Understanding CLV can help managers prioritize leads and opportunities. For example, focus sales efforts on prospects and customers with high CLVs. They warrant more in-person meetings and resources as they generate more value for the business over time.

You can also use predictive analytics to actively target industries, organizations, or job titles that have previously generated higher CLV for your business.

7. Monthly Recurring Revenue (MRR)

SaaS companies rely on specific metrics to track and compare their monthly revenue growth with the previous month. These metrics help companies evaluate the performance of their sales and marketing teams and identify ways to reduce customer churn to boost future revenue.

MRR is a simple and effective way to measure performance growth. For example, if you have 1,000 customers (total customers in a month) who spend $50 a month (average revenue per account - ARPU), you have an MRR of $50,000.

Boost Your Sales Strategy with eSpatial

Need a recap? To conquer sales data analysis, follow these steps:

  1. Collect quality data
  2. Define KPIs
  3. Utilize analytics tools
  4. Segment data
  5. Embrace predictive analytics
  6. Adopt an iterative approach
  7. Foster collaboration
  8. Empower your sales team

Using sales data analysis, you can harness the full power of sales data, pave the way for a more successful sales operation, embrace the data revolution and conquer your sales goals.

In-depth sales analysis is a critical process for today's businesses and becomes even more intuitive and valuable when teams have access to mapping software to support their analysis.

To find out more about how mapping software can benefit your sales data analysis, have a chat with one of our mapping experts or start a 14-day free trial today.

Learn more about how mapping software can benefit your sales data analysis

Liam Costello Written by

Liam Costello

Liam is an eSpatial account manager and mapping expert. He specializes in helping businesses solve problems and increase sales through mapping visualization, territory management, route optimization and more. Liam holds a Master's Degree in Geographical Information Systems (GIS) and Remote Sensing.

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