The “soft” skills of the profession are what most people think of when they picture a salesperson. Salespeople are typically viewed as people-oriented, engaging, and charismatic. They must be able to think quickly on their feet, be sympathetic to the needs of their customers, and be highly-aware of the logical and emotional motivators of each stakeholder involved in the buying process.
While these “soft” skills are still valuable and necessary, the organizations that refine their selling practices using hard data increasingly end up coming out ahead.
Sales data is the collection of quantitative and qualitative information gathered throughout the sales process. Quantitative data includes measurable figures like revenue, conversion rates, and deal volume, while qualitative data captures insights such as customer feedback, buying motivations, and sales rep observations.
This data can cover a wide range of categories, including firmographic, technographic, behavioral, and transactional information. Each type offers valuable perspectives that, when combined, create a complete picture of sales performance and customer behavior.
When used strategically, sales data drives smarter decision-making—helping businesses identify opportunities, forecast growth, refine sales strategies, and ultimately boost their income by focusing on what works best.
Sales data is more than just numbers on a spreadsheet—it’s the foundation for smarter, more strategic selling. By analyzing sales data, teams can prioritize leads more effectively, focusing on prospects with the highest potential to convert. It also plays a crucial role in sales forecasting, helping businesses predict future revenue, plan resources, and set realistic targets.
Informed, data-driven decision-making empowers sales teams to move away from guesswork and toward strategies that are backed by real evidence. With a clear understanding of what’s working (and what isn’t), teams can optimize their performance, improve customer engagement, and drive consistent revenue growth.
Ultimately, leveraging sales data turns every interaction into an opportunity—not just to close more deals, but to build stronger relationships and scale success over time.
To build a truly effective sales strategy, it’s essential to tap into different types of sales data—each offering unique insights into your customers, your market, and your team's performance.
Demographic data focuses on individual buyers, capturing details such as age, gender, job title, and education level. This type of data helps sales teams personalize outreach and tailor messaging to fit different audience segments more effectively.
Firmographic data provides key information about companies, including industry, company size, location, and revenue. These insights help sales teams qualify leads, prioritize accounts, and target organizations that closely match their ideal customer profile.
Technographic data reveals the technologies a company uses, from CRM platforms to cybersecurity tools. Understanding a prospect’s tech stack enables more relevant conversations and allows teams to position their solutions more strategically.
Behavioral data tracks buyer actions, such as website visits, email engagement, webinar signups, and product demo requests. By analyzing behavioral patterns, sales teams can gauge a prospect’s level of interest, anticipate needs, and time their outreach more effectively.
Leveraging a combination of these diverse data types allows businesses to build a comprehensive, data-driven sales strategy—one that drives better engagement, smarter targeting, and stronger revenue growth.
Sales data isn't just theory—it delivers real, measurable results when put into action. Here are a couple of examples:
A SaaS company can analyze behavioral data, tracking which prospects engaged most with product demos and marketing emails. By focusing their efforts on these high-intent leads, they can increase their win rate.
A B2B sales team can use firmographic data to better qualify their outreach, targeting companies that closely matched their ideal customer profile. By zeroing in on the right accounts, they can shorten their average sales cycle and close deals more efficiently.
These examples show how leveraging the right sales data not only improves decision-making but can lead directly to faster, more profitable results.
Sales data can come from a variety of internal and external sources, each adding important layers of insight to your strategy.
CRM Systems: Customer Relationship Management platforms like Salesforce and HubSpot are rich with data on contacts, deals, activities, and pipeline stages.
Sales Calls and Meetings: Conversations with prospects and customers offer valuable qualitative insights that can reveal buying signals, objections, and decision-making processes.
Email Tracking and Engagement Tools: Platforms that track email opens, clicks, and replies provide real-time behavioral data on prospect interest and responsiveness.
Market Research Reports: Industry studies and reports give broader context about market trends, competitor benchmarks, and shifting customer demands.
Buyer Intent Tools: Solutions like Bombora and ZoomInfo Intent gather data showing when companies are actively researching solutions like yours, helping you prioritize outreach.
Third-Party Data Providers: Platforms like LinkedIn Sales Navigator, Clearbit, and Apollo enrich your internal data with updated firmographic, technographic, and contact information.
Maintaining data accuracy and enrichment is critical. Outdated or incomplete information can derail even the best sales strategies. Regularly verifying, cleaning, and supplementing your data—through reputable third-party providers—ensures your team always works with the most reliable insights available.
Collecting and tracking sales data effectively requires the right tools and processes to ensure accuracy, consistency, and real-time insights.
CRM Systems: A reliable CRM like Salesforce, HubSpot, or Pipedrive should be the backbone of your sales data collection. It captures every interaction—from lead generation to closed deals—and keeps your team organized.
Web Tracking Tools: Platforms like Google Analytics and website visitor tracking software monitor prospect behavior across your digital properties, revealing valuable intent signals.
Email Analytics: Tools such as Outreach, Salesloft, and Cirrus Insight track opens, clicks, and replies, giving insight into which messages resonate and when to follow up.
To maximize the value of your sales data, focus on automation and real-time data syncing. The less manual entry your team has to do, the more accurate and complete your data will be. Look for solutions that automatically update records, log activities, and connect seamlessly across platforms.
Consistency and integration are key. Sales, marketing, and customer success teams should all work from a unified, integrated system to ensure that data flows freely and remains up-to-date—fueling smarter decisions at every stage of the customer journey.
Research from McKinsey shows that companies that base their marketing and sales decisions on data improve their return on investment by 15%-20%. In addition, they are 5%-6% more profitable than their competitors.
By collecting data and measuring the right sales metrics, you can:
Relying solely on gut instinct and intuition leaves you vulnerable to disruption by smarter, more data-savvy competitors, no matter what industry you’re in.
In order to remain competitive, you must be able to quickly adapt to changing marketing conditions, trends, and customer demands. In such a dynamic business environment, a well-designed sales data program has become a necessity, rather than a “nice to have”.
Fortunately, a sales data program is relatively easy to set up, and it can deliver drastic profit increases by improving decision-making, increasing efficiency, and expanding your capacity to close more deals in less time.
While there are nearly limitless amounts of data you can collect and track in your organization, it’s important to try to cut through all the noise, and only focus on the data that matters the most.
When trying to brainstorm ideas for which types of data to track, we’ve found that it’s helpful to look at what other sales organizations are tracking, and what they’ve found to be most helpful when it comes to guiding performance management and decision-making.
The LevelEleven research team sought to answer that very question by analyzing 3,000+ types of sales data being tracked by 800+ sales teams.
Here are the top 7 types of data being tracked, in order of popularity:
If you need even more ideas for different types of sales data to track, HubSpot has put together a fairly exhaustive list here.
Once you have begun collecting and tracking your sales data, here are the top ways you can use that data to make smarter predictions, close more deals, and generate more revenue:
By tracking and analyzing the right sales data, managers can be more effective at correcting performance issues, setting realistic sales goals, incentivizing high performers, and motivating their team.
When sales managers have reliable data, they can create a sales forecast for each, individual sales rep, and compare their current performance to their performance in the past.
If a sales rep has unusually low performance, sales managers can focus more time on coaching and training that sales rep.
On the other hand, if a sales rep has unusually high performance, sales managers can now acknowledge and reward that rep’s hard work.
In addition, by looking at data from your CRM, you can see how reps spend their time, and identify which activities make the most impact when it comes to closing deals and generating revenue.
Based on data points you have on your most profitable customers, you can now target and acquire more customers only if they exhibit similar behaviors and characteristics. This effectively allows you to “clone” your most profitable customers.
By utilizing data to improve the targeting of your sales outreach and advertising efforts, you can avoid wasting time and money targeting customers that aren’t likely to be a good fit for your company.
By analyzing demographic, transactional, and customer interaction data, you can now segment leads in your pipeline based on how profitable they are likely to be and how engaged they are (an indicator of how quickly they are likely to close).
Instead of wasting time reaching out to leads that aren’t likely to be interested in your products, sales intelligence tools can now use your sales data to generate a list of the most viable and profitable opportunities to contact first.
This data can also allow you to identify and fix weak points and bottlenecks where leads are getting stuck in the sales process, or falling out of your pipeline completely.
Most organizations find it extremely challenging to develop value propositions that are effective at convincing each segment of customers they target to buy from them. While most companies opt for a one-size-fits-all approach, data-driven companies are able to test many different value propositions on different segments of customers to identify which are the most effective.
By collecting and cross-referencing many data points, it’s possible to build highly-personalized value propositions tailored to the specific needs of each customer segment.
Over time, you can also gather data on which types of marketing collateral, demos, and sales presentations are the most effective at converting different types of prospects.
You may learn that some prospects prefer short, concise sales presentations, while other prospects prefer more in-depth, detailed demonstrations of the product.
Another challenge is setting the price of new products and services to ensure maximum sales and revenue. Using market data and dynamic-pricing engines, companies can test many different price points to determine what the optimal price is for each solution, and even for each segment of customers.
Some companies have discovered that, in order to maximize revenue, they actually needed to raise prices. While price increases may cut the number of potential sales, by growing the average size of each sale, you may be able to achieve an increase in overall revenue.
You can also increase sales significantly by personalizing discounts and promotions to each prospect.
For example, if the data shows that a certain type of prospect typically ignores a 10% discount, but often makes impulse purchases once a product is 40% off or more, you can send them a customized promotion to increase the likelihood of closing the sale.
This same level of personalization can be applied to all kinds of other incentives, such as free shipping, freebies, etc.
You can only derive valuable insights from your sales data if you’re collecting it in the first place. This is where the biggest challenge lies for most sales organizations.
The process of manually entering sales activity and customer data into a CRM such as Salesforce™ is often extremely tedious and frustrating, decreasing the chances that your sales reps will actually take the time to do it.In fact, sales professionals cited manual data entry as their #1 challenge to using their CRM, according to HubSpot’s State of Inbound: Sales Edition Report.
Source: HubSpot’s State of Inbound: Sales Edition Report
The report goes on to state:
“Data entry time negatively correlates to user satisfaction. Practitioners and executives alike prefer time spent selling to time spent on manual tasks that software should help avoid….”
There’s no wonder why only 40% of sales updates are ever entered into the CRM, on average, according to ActiveCampaign. Even when data is entered into the CRM, there’s no telling how accurate it is. Even small typos by hurried salespeople can ultimately add up to major errors down the road.
Because critical sales data isn’t being tracked in any kind of systematic or consistent way, business leaders are too often forced to make strategic decisions based on poor data, guesswork, or intuition.
While getting sales reps to enter accurate and thorough data is an uphill battle, you simply can’t afford to not have this data.
The only viable solution is to find a way to eliminate manual data entry entirely and make the whole process automatic. However, until recently, there has been no reliable technology capable of doing this.
Fortunately, Sales Force Automation (SFA) tools have become extremely helpful at automatically handling all kinds of mundane, tedious administrative tasks.
According to SiriusDecisions:
“These improved systems are capturing information automatically so that reps spend less time doing data entry, and they’re analyzing the data they capture to help reps target the best prospects and accounts, offload tasks such as calendaring, and guide reps using insights from the SFA data. SFA systems are finally becoming a valuable tool for reps and sales operations.”
Cirrus Insight, for example, is an SFA tool that works transparently in the background to automatically record and track 100% accurate sales activity data so your team is free to focus on more important activities, like attracting, delighting and retaining your customers.
With Cirrus Insight, your sales reps can carry out their work like they normally do, sending emails, booking appointments, making phone calls, etc. As they work, Cirrus Insight automatically tracks all of their sales activities, without them having to think about it.
By eliminating manual data entry, Cirrus Insight gives your sales team hours of valuable time back that they can use for high-impact sales activities and coaching.
It’s like having a virtual sales assistant working behind the scenes to record events in Salesforce, book meetings, and find the data-driven insights your team needs to deliver sales quotas.
With Cirrus Insight:
Sales data is typically tracked using CRM systems, email engagement tools, web tracking software, and call recording platforms. Automation is key—choose tools that log activities and update records in real time to minimize manual work and reduce errors.
Start by identifying the key metrics you want to track, such as conversion rates, sales cycle length, or deal size. Use CRM dashboards, reporting tools, and data visualization software to spot trends, measure performance, and uncover opportunities for improvement.
Sales data can come from internal sources like your CRM, email analytics, and call notes. You can also supplement it with external sources, such as market research reports, buyer intent data, or third-party providers like LinkedIn Sales Navigator or ZoomInfo.
Selling data is often referred to simply as sales data. It includes all the quantitative and qualitative information collected during the sales process, such as customer interactions, deal histories, and prospect engagement.