Data and intuition walk into a bar. Data orders a gin martini — strong, reliable, and no-nonsense. Intuition, on the other hand, asks for something off the menu.

Data knows what it wants and orders based on experience, evidence, and time-honored tradition. Intuition isn’t interested in those things. It wants to push the envelope, get creative, and try something new.

Your team might be filled with intuitive sellers. But to hit your sales goals, there’s nothing stronger than data. That’s why sales analysis is so important. When you pair your instincts with real data, your reps can make evidence-based decisions and steer clear of guesswork.

Research from McKinsey shows that companies using data analytics to drive their sales processes have seen lead conversion rates soar up to 30%. We’ll break down how you can achieve the same success.

What you’ll learn:

• What is sales analysis?
• The benefits of sales analysis
• Key sales metrics to watch
• What to look for in a sales analysis tool

What is sales analysis?

Sales analysis is the process of gathering and “dissecting” sales data to uncover trends and patterns in your sales team’s performance and your customer behaviors. For example, you might see patterns in product performance, customer purchasing patterns, or the effectiveness of your sales channels. This meticulous attention to detail helps sales leaders identify areas where they can enhance forecasting accuracy, boost team performance, and speed up internal processes.

For example, recognizing inefficiencies in the sales process could lead to targeted interventions, such as refining your approach to lead qualification or improving follow-up tactics, directly impacting sales effectiveness.

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The benefits of sales analysis

Sales analysis is key to honing your sales strategy, providing a clear picture of where your efforts are paying off and where they’re not. It’s about increasing your team’s productivity by identifying the most efficient sales practices, and highlighting areas that aren’t working and need improvement. On the customer side of the equation, sales analysis can help you prioritize prospects most likely to close, ensuring resources are allocated effectively.

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Key sales metrics to watch

Depending on your goals, there are different ways to slice and dice the sales data you can analyze for actionable insights. Below are the most common sales metrics and KPIs that sales teams analyze to understand performance and opportunity:

Pipeline metrics

These metrics, like how quickly a lead moves through the pipeline and how many leads are in the pipeline at any given time, offer a view of how successfully a rep is selling. It can reveal obstacles that cause deals to stall and help you manage rep workload to ensure they have enough — but not too much — to focus on.

Conversion rates

A critical measure for both sales reps and managers, conversion rates show you the rate at which leads are moved from one stage in the sales process to another. By analyzing these rates, sales reps can refine their approaches to improve actions in specific stages. For example, a rep may choose to add follow-up emails after the sales call stage to ensure prospective buyers remain engaged.

Average deal size

This metric provides insight into the typical value generated per sale. Ultimately, this guides sales managers in strategic planning, setting revenue targets, and identifying lucrative market segments for focused engagement.

Average sales cycle length

Used to assess the efficiency of the sales process, this metric helps in identifying bottlenecks that lengthen the cycle. Shortening the sales cycle through faster lead qualification and engagement tactics in various sales process stages can significantly impact overall sales performance.

Won and lost deals

Comparing won and lost deals reveals patterns and areas for improvement in sales strategies. This analysis is invaluable for enhancing onboarding and training programs and refining sales tactics to increase future success rates.

Customer churn

This metric pinpoints when and why customers leave your business and opens the door for conversations and ideas about how to improve retention rates. Are there common times when customers leave, or triggers that seem to push them out the door? How can you fix these?

Sales call feedback

Sales reps primarily use this metric to assess their call performance. Managers can also use it to coach reps on effective communication techniques and call strategies. Additionally, they can find insights to praise or discourage certain techniques during performance review conversations.

Lead response time

Your lead response time is the amount of time it takes for reps to follow up with potential clients after they first contact your company.

Forbes cited the average lead response time as 47 hours and notes that those who reach out within five minutes are 100+ times more likely to see success than those who wait even 30 minutes. Ultimately, understanding this metric can help sales reps become more proactive about reaching out to leads.

Annual revenue

A comprehensive metric that reflects the overall financial health of the business, annual revenue is crucial for strategic planning and growth projections. It provides a broad view of the company’s success and areas for future expansion.

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What to look for in a sales analysis tool

Sales analysis tools help you turn raw data into actionable insights. They not only simplify the process of gathering and analyzing sales information, but they also give you a complete view of your sales performance. To improve your sales analysis, look for tools with this functionality:

Easy-to-use customer relationship management (CRM) capabilities

CRMs manage sales data of all kinds in one place: customer interaction, sales activities, and overall performance. For example, without a CRM, you might miss key information like customer behavior patterns, such as when potential customers typically drop out of the sales cycle or which channels engage customers the most effectively.

A CRM that balances advanced features (like AI and automation) with an intuitive interface empowers your team to excel without unnecessary complexity. This ease of use is crucial for ensuring that the tool becomes an integral part of your daily operations. For maximum impact, it should facilitate seamless management of customer relationships and sales data analysis.

AI-powered insights

Many advanced CRM systems now incorporate AI for a deeper, more nuanced analysis. For example, AI can use data to identify which potential customers are most likely to purchase based on analysis of past deal behaviors and customer trends, so teams can create more targeted sales strategies.

Here’s an example: AI surfaces an insight showing female customers from the Midwest between the ages of 18 and 35 prefer a particular brand and flavor of soda. Sales teams can use this information to focus their efforts on this region with tailored promotions and personalized communication to this demographic via social media.

Visualization

Embedded in CRM systems, dashboard creation tools provide visual summaries of sales metrics, often in real-time. They highlight vital data like leads in pipe, conversion rates, and customer engagement levels. They can also flag problem areas. For example, a dashboard might reveal that many deals are stalled at the negotiation stage. This allows you to address the issue by refining negotiation tactics or adjusting pricing to start moving more deals forward.

Automation capabilities

Now often found built into CRMs, automation helps simplify tasks like record updates, report generation, and other admin duties. Automation not only brings consistency and efficiency to routine processes, but it frees up reps’ time to focus on relationship-building.

Predictive analytics

Using historical sales data, predictive analytics can forecast future trends. These forecasts are instrumental in preparing for market shifts or changes in customer behavior. For example, if analytics reveal that certain customers tend to upgrade their services at the end of the fiscal year, sales reps can proactively time their outreach. Then, they can tailor their conversations to offer upgrades or additional features around that period.

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Take action with insights from sales analysis

Sales analysis digs into data for insights and strategies. It’s about finding what works based on solid evidence. When blended with a seller’s instinct and human intuition, sales teams can make informed decisions while testing new strategies and recipes to drive sales success.