How Sales Data Analysis Cuts Prospecting Times in Half

Everyone has an enemy—even salespeople.

Let’s check the dictionary: an enemy is a person (or thing) that actively opposes, harms or threatens another person (or thing). Now, conventional wisdom says to avoid enemies, but what if we told you having an enemy can actually be a good thing?

A threat can challenge your salespeople and give them a purpose in their role. When they overcome the challenge they’ll become more courageous and competitive and elevate their sales performance. That’s right—enemies can help sales reps become better at B2B prospecting!

So who or what is salespeople’s biggest enemy when it comes prospecting? Is it laziness? Poor sales data that gives them unreliable insights? Or how about terrible managers that don’t provide the correct training, technology, and resources to find new sales-qualified opportunities? The answer is… none of the above.

The main enemy of sales representatives is time. In every step of the prospecting process, the biggest issue salespeople will face is lack of time to complete a task or the wastage of time. Like how web-generated leads are 100x more likely to respond to a cold call if the sales rep responds back within 5 minutes—but their average response time is 3 hours!

And that doesn’t mean reps are procrastinating; they could simply be putting their efforts into the wrong tasks. Either way, time is their biggest opponent. If sales reps don’t learn to get the best of time, time will get the best of their pipeline.

There’s only one real way to defeat this enemy: sales organizations need to conduct sales data analysis. They need to confront what their reps, leads, and prospects are really doing during prospecting hours and learn how to complete prospecting activities in half the time. Keep reading to see how to defeat your arch-nemesis when looking for new business opportunities.

What is sales data?

Sales data is any quantified information you gather about your sales organization, potential buyers, and current customers.

It includes facts and statistics that measure your sales process, your performance, your pipeline, your revenue, your campaign successes and failures. Sales data is also information about your potential buyers: who they are, what they want, how they respond to your sales activities, how they behave at every touchpoint in your funnel, and even what they do outside your pipeline that may affect their buying decisions. Sales data of a company is collected from your databases and sales tools, like your CRM, surveys, and customer feedback.

Is sales data analysis really the answer to shorter prospecting times?

There’s a very good reason to learn how to get prospecting done faster. According to a HubSpot study, 72% of companies don’t reach their financial goals if they have less than 50 new opportunities each month. The longer you take to find, qualify leads, and connect with them, the more you risk missing your sales targets.

It’s tempting to shift the blame away from time. Some teams complain, “If only we had stronger leadership and better training! Then we would get double the amount of prospects every month!” But the reality is nothing impacts successful prospecting more than wasted time.

An alarming recent study shows some salespeople are prospecting with 50% of their leads unqualified. Ouch—that’s at least 50% of their time lost to outreach that virtually guarantees a disappointing result. It’s also taking longer than ever to make a connection, with data saying an average of 18 calls are needed before you can connect with a B2B buyer!

Making things even more difficult is the fact that today’s decision-makers prefer to be contacted through email and messages, which may elongate .

How sales data analysis offers a cheat code

Prospecting is the starting point to finding and reaching out to your next customer. If you’ve ever gotten off on the wrong foot with someone, you know that the wrong glance, a bad choice of words, or bad timing can kill a relationship within milliseconds.

That’s why, before sales reps begin searching for new leads, they should know how and when to communicate. Otherwise they’ll waste precious time and energy trying to connect with the wrong people on the wrong channels.

Good communication starts with taking a deep, hard look at data and conducting sales data analysis. What is sales analysis? It’s an in-depth report that summarizes information, your team’s sales performance, and customer data. It has both historical and current data and reports on trends, downturns and upturns in customer behavior and buying patterns. An analysis can be a written, verbal or visual report, or a mix of all three.

How sales data saves time when prospecting:

• Ideal customer profiles and buyer personas will automatically update. There’s no worse way to spend time than adding unqualified leads to your pipeline. When you use a good sales prospecting tool that enriches the firmographic and demographic data on your leads, it automates updating info so your campaigns are sent to qualified leads.
• Connections will come sooner. Once you’ve mapped which touchpoints (website, LinkedIn, etc.) your leads and prospects frequent, you’ll know which platforms to speak to them on and which to avoid. Sales data analysis will even help you narrow down the tone, word choice, and correct time to contact leads.
• You can calculate how long tasks take to complete. With sales data, you’ll know exactly how long it takes for sales reps to send out 100 cold pitches or how quickly they follow up with leads. No more guessing and getting it wrong, and running out of time when planning your week.
• You’ll always know your next move: Analysis tools today have features that can predict trends in your industry and behaviors of your future prospects. This can result in you receiving feedback on how and when to send outreach, who to contact and how to strengthen your prospecting strategy.

Sales data examples for every prospecting step

Have we convinced you that time is your (good) enemy, and analysis is the weapon you need to defeat it? Great. Next we’ll take a look at a sales data example for every step in the prospecting process: defining quality leads, searching for opportunities, sending outreach, and finally making a connection.

For each of these steps, we’ll also show what good and great sales data looks like. Good data provides information, but great data is hyper-specific and more useful when figuring out where your time is going.

1. Defining quality leads

Most salespeople know that prospecting without a solid ideal customer profile and buyer persona is like hunting for Pokémon without any Poké Balls. If your ICP and buyer persona aren’t quite ready for action, any sales data relating to your leads, prospects, and customers can come in handy. This data will give insight into your customers’ firmographics, demographics, psychographics and personality to flesh out these profiles and to identify them quicker.

Sales data examples:

• Good data: 70% of our customers live in the U.S.
• Great data: North Texas, Los Angeles, and Arizona are where the majority of our B2B customers are located.

2. Searching for opportunities

Now that you’re ready to hunt for new leads, a huge time zapper is looking on the wrong platforms. To accelerate the search process, make sure you’re tracking exactly which channels and platforms deliver quality leads so you can generate a steady stream of opportunities.

Sales data example:

• Good data: LinkedIn brings in the highest-value leads each month compared to other channels.
• Great data: Linkedin brings in 25 high-value leads each month, 10% more than email marketing and cold calling efforts.

3. Sending outreach messages

You might have heard the term “sales enablement content”—this includes case studies, white papers, blog posts, in-depth product guides, video tutorials and anything else that educates your leads on your product or service. It’s vital to have on hand when sending outreach messages, especially when a prospect is at the beginning of their buying cycle. Ready-made content saves incredible amounts of time and is much better than typing an essay every time someone asks about that one feature in the new version—or even worse, copying and pasting the same dry template email. Sales enablement content helps you send personalized assistance quickly for your leads.

Sales data example:

• Good data: Leads are more likely to finish reading case studies than white papers.
• Great data: Leads are 3 times more likely to finish reading case studies over white papers.

4. Getting a connection

Finally, the moment every sales rep lives for—getting a connection. Your prospect is ready to learn more about your product or service, and they’ve scheduled a meeting, presentation, or demo to get their questions answered. Important metrics to watch here include connection rates and number of meetings scheduled per number of calls or emails sent. Customer segmentation is important to utilize when looking at connection rates because you need to understand how different customer bases respond to outreach.

Sales data examples:

• Good data: On average a sales rep needs to send 3-4 follow-up emails within a month to get a response.
• Great data: On average a sales rep needs to send 3-4 follow-up emails between the hours of 8 am and 11 am within a month to get a response.

Every place you can collect sales data

There are three main ways to collect sales data: tracking customer data, asking for customer data and buying industry data. Whichever you choose, it’s important to collect, store and organize company sales data immediately so information isn’t left scattered across several B2B databases, outdated, useless, and forgotten.

1. Tracking customer data

This is the low-hanging fruit of the sales data tree since it’s easy to obtain. It comes from leads and prospects on your website, lead capture forms, social media channels, and campaigns, and it can be gathered through analytics, your CRM, customer service reports, and more. Aim to start tracking your potential buyers in the beginning stages of their sales journey, as this will reveal which channels and platforms they come from, what content they’re interested in and which actions they take both in and outside your funnel.

2. Asking for customer data

Asking current prospects and customers for information is the only way to get psychographic sales data. This data includes personality, values, attitudes, interests, lifestyle choices, spiritual and political beliefs and more. Why is this data important to have? It provides better context behind why a prospect may buy your product or take longer to respond to a message, and making a personal connection to someone’s values and beliefs is hands down the best way to pitch to them. Ask for customer data by sending surveys, hosting quizzes on your website and speaking to your sales team about common interests they notice among prospects.

3. Buying industry data

The final method to collect sales data is to just buy it! This data is collected by big data firms and industry publications, and it includes a host of statistics that go beyond what your sales organization can gather on its own. For example, you may want to know what percentage of web visitors convert to prospects in your industry. If you know that number is 10%, you can use it as a benchmark to see if your campaigns are converting well. Just make sure the sales data you buy is relevant to your industry, vertical and customer base. You can also purchase prospecting lists if your sales manager doesn’t provide you with adequate leads to shorten your research time.

Three sales analysis methods you should focus on

If you want to learn how to analyze sales data, you’ll need to get familiar with the different methods out there. Sales data analysis isn’t just about examining any ol’ information, it’s about pinpointing the time issues within your prospecting process and gathering insights to help you solve them.

Here are three popular methods:

1. Sales pipeline analysis: Sales pipeline analysis tracks your prospects’ behavior starting from the moment they enter your pipeline. From that initial connection to their interactions across channels, touchpoints, and with sales reps, tracking the sales data in your pipeline can provide a breakdown of how leads feel, act and think in the beginning stages. This data can show you where leads might be dropping off so you can come to the rescue with better sales enablement content or faster response times.
2. Sales performance analysis: Sales performance analysis monitors and tracks how well your salespeople perform tasks. For example, if your sales reps are taking too long to find an email address, this may mean you need to cast a wider net to find more decision-makers at a single company, and/or use a better B2B email finder. If this sounds helpful, try Lusha Extension; it can find email addresses from a lead’s website or LinkedIn profile within seconds, and it has a 90% accuracy rate.
3. Sales trend analysis: A sales trend analysis looks at the historical behavioral, relationship and buying trends among customers. This sales data can help your organization anticipate how future prospects will react to certain sales pitches, campaigns and other messages. It gives you time to plan campaigns in advance and get ahead of future threats that could suck time away from your team.

How to analyze sales data and get tasks done in half the time

Once you’ve chosen one or two methods to start with, you should know the step-by-step process for how to analyze sales data correctly. You examine your reports, then you look at the data patterns, relationships and behaviors, and data insights will reveal themselves. These insights will give you a deeper understanding of your prospecting efforts and performance and hold the answers to some of your biggest time challenges.

To get you started, here’s how to analyze sales data in 3 simple steps.

1. Identify the metrics you want to measure

If you want to grow and improve your prospecting activities and performance, you’ll have to track the right metrics.

Here are a few to choose from:

• Number of prospecting hours per week
• Number of appointments scheduled
• Number of sales opportunities generated each month
• Number of lead to sale conversions

2. Let technology do the grunt work for you

Lucky for you, many CRMs and other sales software today already have analysis features built in. What’s great about these programs is that they do all the heavy lifting for you; all you have to do is sync your databases and you’ll get fresh sales data reports generated with crystal-clear graphs about your prospecting and performance times.

3. Share and discuss findings with your team

After you have a brand-new spanking report, share the results with the sales department and get focused on discovering new data insights. Insights will provide a deeper understanding and help you get to the bottom of how and why you’re wasting time when prospecting. Sales analysis is impossible without human input; opinions and feedback are necessary to get insights, problem-solve and come up with solutions.

Key takeaways

• The biggest issue salespeople are facing when B2B prospecting is wasting time and focusing on the wrong tasks. The only way to overcome this issue is to take a look at sales data.
• Sales analysis is the key to solving your time issues. Examining the relationships between data, behaviors and patterns will give your sales team better insights into where their time is going and how to speed up their prospecting performance.
• The sales data of a company should be hyper-specific to help you speed up every activity. One prospecting tool that’ll help you gather information on your leads is Lusha. It’s a B2B lead enrichment email and phone number finder extension that will deliver firmographics, demographics and contact info within seconds. Calculate the ROI Lusha will bring you with our sales revenue calculator.