Sales Data: An Actionable Guide to Mastering Your Analytics

Sales data gives you a sense of context.

It tells a story.

Where you were, where you are and where you will go.

Without it, it's like trying to read from a book with missing pages.

Confusing and invaluable.

In the B2B landscape, your sales data gives you a complete view of your customers. An important thing to have in your strategy toolkit, right?

Yet, only 15% of B2B companies feel they have a complete view of their customers, and 19% say they understand their customer journeys.

If you don't view your company as an effective user of advanced analytics or struggle to benefit from basic sales data, you're in the right place.

In this post, we're breaking down how you can use your sales data throughout the customer journey to help you make better business decisions and focus on the things that'll improve your growth rate and customer retention.

What is sales data?

Sales data is any information your sales team can use to improve decision-making, close deals, and understand what drives your users to seek a solution and make a purchase.

Without it, your business strategy lacks key data points, and you won't have accurate or timely insights to respond to changes in the market.

Net promoter score (NPS), customer lifetime value (LTV), and revenue per sale are some examples of sales data you can track with your customer relationship management (CRM) system.

However, you’ll need other tools to help you uncover insights, improve your sales forecasting, and identify the best sales metrics and key performance indicators to track.

How sales data helps your entire sales team

Sales data helps you become a more data-driven sales team. It removes intuitive feelings and guesswork and replaces it with facts that can remove bottlenecks from your pipeline.

Here's how to get the most out of your sales data.

It helps you identify new opportunities and avoid bad-fit customers

Leads and online dating are two peas in a pod.

Often, we get stuck in a chasing loop.

We swipe right and spend hours getting to know the person, even if there are giant red flags all over their profile.

*cough* dog people *cough*

It's the same in B2B sales.

To maintain a healthy pipeline and hit quotas, reps lose focus and spend time nurturing leads that aren't good fit customers.

Your sales data can help you cut through the noise, identify best-fit prospects, and prevent you from chasing leads that will never convert.

Let's look at an example:

You attend SaaStr: The event is a success, and you come home with a stash of business cards from potential customers.

The only problem: You might have demographic data like a name and email address, but you're missing core firmographic data to decide if a lead is worthwhile pursuing.

The solution: You plug the email address into a tool like Clearbit to find the missing firmographic data you need.

Finally, you'll look at your ideal customer fit percentage. If you have the Breyta CRM integration, the tool will automatically calculate your customer fit score from multiple external and internal sales data points, saving you time and giving you a more accurate ICP score.

This helps you avoid nurturing bad fit leads and re-route high-quality SQLs to your SDRs faster.

You’ll get a more accurate and effective sales pipeline

The B2B buyer journey is non-sequential.

Leads can come in at any point, and your team needs to tailor their response based on where the customer is, not the next logical step, according to you.

If you're holding onto the linear sales process of the past, you're manifesting a wonky pipeline, but that doesn't mean you can throw your entire SaaS customer lifecycle out the window. You still need to understand the triggers for each stage to figure out the next steps to convert the lead.

Here's how you can use your sales data to improve your sales pipeline accuracy.

Using your customer journey data

When you look at your customer journey data holistically, navigating the unpredictable seas of non-sequential selling is easy. You're not forcing users to complete your buying cycle in a specific order but adjusting the map to suit their journey.

Let's say you have a lead with a 90% customer fit score.

The user visits your landing page and signs up for a free account but doesn't download your app. That's a major red flag your sales data can pick up and mitigate by triggering a campaign to re-engage the user to complete the download and see the value in your tool.

Unpack your user engagement

Do you know your time to value (TTV) when a user signs up for a free trial?

What about who is the most engaged user from a company? Or if customer activity is increasing or decreasing?

If those questions are drawing blanks, it's a sign you need to enrich your sales data.

By using a tool like Breyta that syncs up with the data in your CRM software and other external sources, you don't need to spend hours trying to analyze user engagement.

You can see who is accelerating a purchasing decision (your customer champions) and which leads need some TLC from your customer success team before anyone clicks the "unsubscribe" button.

Identify the bottlenecks in your pipeline

Friction stops growth.

Use your sales data to find those bottlenecks and remove them to create a seamless lead to customer experience.

Answering these questions will help you create a more accurate pipeline:

Automate lead nurturing for low-quality leads

Don’t ditch your lower-quality leads.

Just because a lead doesn't meet your ideal customer fit score now doesn't mean they won't in the future.

Use your sales data, like customer fit score, to weed out the low-quality SQLs, decrease the number of touchpoints from your sales team, and automate the nurturing process with email sequences.

When the lead score bumps up, you can switch to personalized communication and hand off a higher quality lead to your SDRs.

Use real-time data for accurate forecasts

The problem with modern CRMs and sales metrics?

It's old data.

You're constantly referring to the past to make decisions for the present or basing your strategy on guesstimates for the future.

To become a data-driven organization, you need real-time sales data.

A tool like Lative gives you the real-time growth efficiency metric you need to create an accurate sales pipeline. You'll know where your team will land at the end of the month based on what is currently happening, not what did happen or might happen in the future.

Key Performance Indicators (KPIs)

Your KPIs aren't for setting lofty company goals and hoping for the best.

By running a sales data analysis, your sales leaders can identify performance issues, set realistic quotas, incentivize high performers, and ensure your most important accounts go to the best salespeople.

Set and track your KPIs

The secret to sales team performance?

Carefully selected KPIs that track and measure the performance of the entire sales organization.

Your average customer lifetime value (CLV) and customer acquisition cost (CAC) are arguably the most important metrics for any B2B start-up.

…But here's the thing.

These key sales metrics aren't stock standard. What's an important KPI for one sales team won't make sense for another.

Every KPI you track needs to match up with a goal. This will help everyone on the team understand the "raison d'etre" of the company and create focus.

Evaluate team and individual performance

Is a sales rep not performing? Use your sales data to figure out the best solution.

Schedule extra training, look into fine-tuning your sales enablement practices, and re-visit your sales metrics to make sure you're not setting unrealistic goals.

Got a sales rep crushing their quotas? Analyze your high performers and use the data to replicate their success.

Refine your product suite

Your product suite is something that's in a state of constant flux.

As your PLG company grows, you'll fine-tune your processes, add features, or completely remove products that don't serve your ICP.

The only way to ensure you're on the right track is by continuously looking at your product sales data.

Run a product sales analysis

How well do you truly know your user base?

Without looking at any of your sales data, do you know:

A product sales analysis gives insights into your customer's purchasing behavior and helps uncover patterns costing you money or driving conversions.

Tweak your sales process

After running a product analysis, start refining your GTM strategy.

Churn, Cross-sell, and Upsell

Your sales data doesn't end at the conversion.

Once a user hands over their money, you still need to track engagement and usage to prevent churn and identify cross and upsell opportunities.

Predict customer churn

It's much easier to prevent churn than to try to win back an unsubscribed user.

Use your data to identify indicators of possible churn and set up triggers to hand over the account to your customer success team.

Some of the data points you can track include:

But that's not all.

A key source of possible churn data is customer satisfaction.

According to research by Esteban Kolsky, 1 out of 26 unhappy customers complain, yet 67% report bad experiences as a reason for churn.

How do you identify unhappy customers? Customer satisfaction surveys.

For example, you can send out a simple email blast asking your users, "On a scale of 0-10, how likely are you to recommend this product to your friends, family, or business associates?".

Users who respond are segmented into three buckets: detractors (0-6), passive (7-8), and promoters (9-10).

For the accounts reporting low satisfaction scores, your customer success team can step in and proactively reach out before it's too late.

In another study from Mckinsey, regional managers who had a list of at-risk customers with guidance on how to engage each one to save the account managed to reduce churn by 25 percent.

Finding cross-sell and upsell opportunities

Your customers are a gold mine.

While growing your user base is an important aspect of hitting milestones like $1M in ARR, it shouldn't come at the expense of existing users.

The probability of selling to someone who has already given you their credit card details is between 60-70%. Whereas selling to a new prospect has a probability of 5-20%.

Yikes.

That's not all.

Existing customers are 50% more likely to try new products from you and spend 31% more than new users.

How can you use your sales data to leverage customer retention?

Use dynamic customer segmentation and AI to offer tailored recommendations based on past purchasing decisions.

For example, when you create a free account with Canva, you have 5GB of free storage. Once you hit the limit, the app automatically prompts you to sign up for one of the paid plans. If you don't, you'll need to delete your content manually, and it's not a quick process.

Hyatt Hotels is another excellent example of a brand using sales data to increase cross-sell and upsell opportunities. Using customer preferences and history from their membership program, the hotel chain can create customized offers based on a unique combination of room upgrades, activity packers, and amenities.

Without a guest saying a thing, the front desk will know if that person prefers rooms with an ocean view or is most likely to book a spa package.

It creates an incredible customer experience and seamlessly boosts the hotel's bottom line.

Data-Driven Sales

Data is the key to your success.

In a competitive business landscape, you need to leverage the power of data-driven sales.

Without it, you'll lag behind everyone else and miss out on opportunities that can take you from a struggling start-up to one of the top PLG companies in the world.

This isn't a hypothetical scenario.

Research from McKinsey & Company shows companies that leverage sales data are 5%-6% more profitable than their competitors.

What does a data-driven sales approach look like?

As you can see, a data-driven approach will save you time, money, and resources. It streamlines your entire sales process to maximize revenue.

Ready to take the next step? Connect your CRM and other data sources to Breyta and get a 360-degree view of your entire SaaS customer lifecycle.