The money is in the data. You’ve probably heard this many times. As technology advances, the statement grows more relevant.
So, businesses looking to gain customers and close sales are integrating software like CRMs into their sales cycle to collect this data. Statistics show that data-driven businesses are 58% more likely to reach their revenue goals than those that do not use data.
But how do you ensure your business benefits from sales data?
After collection, the next crucial step is understanding how to analyze sales data. Through sales data analytics, you can interpret the data and turn it into actionable insights that, when well-implemented, leads to business growth.
This article delves into more benefits companies stand to gain from a sales data analysis. But first, let’s start with the basics.
What Is Sales Data?
Sales data is measurable information collected during a sales process. You can use this information to guide each sales rep and make data-driven decisions. These decisions range from matters like sales strategies, prospecting, and sales automation. Solutions developed, as a result, help shorten the sales cycle and align your sales goals.
There are different sales data categories. However, here are the most crucial ones relevant to a B2B business sales process:
- Demographic data. This is the most basic sales data example. These are details like the company maturity stage, location, and the number of employees.
- Technographic data. This sales data example helps you understand the technology your customers use to run day-to-day activities smoothly. Using technographic data, you could, for instance, notice that a company is missing an accounting software you provide. Then, you can turn this into a sales opportunity by pitching the tool to them.
- Chronographic data. This data shows businesses' changes that either make them new prospects or revive cold leads. The data may include a company’s location changes, funding, acquisition, or IPO.
- Intent data. This helps you understand your current customers’ online behavior, making it easy to identify their interests. The data can either be first-party or third-party data. First-party data is the sales data collected from your website, while third-party data is collected across various websites.
Ensure your sales team understands how to analyze sales data in different categories, from the sales manager to the last sales rep. For instance, they need to know that the intent data makes it easy to understand historical sales. But if they want to identify their ideal sales targets, they can use demographic data.
5 Ways Sales Data Analysis Helps Business Growth
Now that we’ve discussed sales data and its vital role in a business, let’s look at the specific benefits. We’ll also look at how you can use sales data solutions to better your processes and sales enablement strategies and increase your revenue and profit margin.
1. Improved retention rates
Even when looking to attract new customers to grow your sales capacity, you should also focus your sales effort on retaining current customers. Statistics show that the success rate of selling to your existing customers is around 70%, but only 5% to 20% for a new customer.
Sales analytics reports make this possible by helping you determine what customers want. First, you identify your top customers. Then, with the help of sales data analytics, your team develops strategies that ensure better customer satisfaction and customer retention rates.
Your team can also identify factors causing high churn rates, rectify that and improve customer experience. For instance, you might realize that your sales team's email marketing mistakes like spamming behavior, poorly timed emails, and generic emails are the main reason for your high churn rates. You can rectify these mistakes and grow your conversion rate with this information. In addition, you can use discounts or timed free trials as incentives.
Finally, effective sales data analysis helps you notice customers' habits and patterns. With these, you can embrace data-driven sales strategies like upselling and cross-selling. These tactics help retain customers by giving them more value from your existing products. It also turns the customers into return customers through targeted recommendations and programmatic ads.
2. Better forecasting
Forecasting is using data to project future outcomes, which in this case is sales outcomes. Through sales forecasting, you can use the data to prepare for future risks, sales opportunities, challenges, and developments. That puts you one step ahead, leading to accelerated business growth.
For instance, you can forecast your revenue by projecting potential sales. That makes it easier to allocate resources to your sales team better. It also encourages them to work toward the projected goals and outcomes.
Here’s an example of revenue forecasting done by Chargify:
Your sales forecast success is dependent on the data used for the process, so ensure you use factual and accurate data. Also, pay attention to your sales data quality because the higher the quality, the more precise your sales forecast will be.
The other factor you should note is the different techniques to use for your sales forecasting. There are three main techniques: qualitative, time analysis, and the projection causal models:
- Qualitative model. This analyzes and uses past sales operations data to predict future operations. For instance, you could predict factors like the number of products to manufacture to match the future customer demand.
- Time series model. This mainly focuses on the specific sales patterns and changes to help predict future outcomes.
- Causal model. This makes predictions by considering different variables that could influence the market's future direction. The variables range from the GDP, population, or general economic conditions.
Your technique choice is influenced by the sales data and the stage of the sales process you want to forecast. However, you can use them collaboratively for an accurate sales forecast.
3. Accurate value propositions
Your value proposition's potential is great, but how do you achieve it? Data. With the help of data collected and analyzed, you can fully understand what customers expect. You can then ensure your value proposition captures this and compels target customers.
Value propositions explain to your customers why you should be their choice. Your value proposition should cover three main elements:
- The promise of what you will deliver
- What they will gain by choosing your business
- Why they should choose you over your competitors
Here’s an excellent example of a good value proposition:
Your value propositions should help you present your business in a way that compels customers to buy from you. For instance, in the example above, the promise to acquire more clients will likely compel businesses to choose to work with CIENCE.
You can also add supporting statistics and factual data after your value proposition. That helps a business promote B2B customer loyalty and boost conversion rates.
4. Stronger pipeline management
Pipeline management is vital, especially when your leads list is constantly growing. You don’t want to end up with poor-quality leads that will not boost your future sales. Instead, you want a healthy pipeline that makes it easy to identify profitable customers.
It should also make it easy to track your leads through the five sales stages:
Unfortunately, the more your leads grow, the harder it gets to keep a healthy pipeline. But quality sales data can solve this. Trying to sell your products or services to the wrong people will only lead to high churn rates, bounce rates, and slow business growth.
Once you learn how to analyze sales data, you can easily segment the leads in your pipeline based on profitability and engagement level. It’s also easy to track how leads are moving in your sales pipeline—making it easy to identify your weaknesses and sales bottlenecks where you lose most of your leads.
The sales data also helps you note the customer journey, patterns, and details like your clients’ company size and location. These make it easy to determine your prospecting and sales strategy to use.
For instance, your data could show that most of your clients are middle-size businesses. This intel can help you shape your product offerings, pricing, marketing strategies, etc., in such a way middle-sized businesses will want your services. Using dynamic pricing tools can be one of the ways to make this task easier.
5. Targeted marketing
Targeted marketing is one of the most effective and budget-friendly marketing strategies for any business. That’s because you’re marketing with a focus on a specific lead segment. Hence, you use branding and tones that resonate with the target group, which results in higher engagement and conversions.
A sales analysis report helps you understand your audiences, making it easier to create target groups. You can divide the target groups into segments that could vary from job titles, location, interests, and values. You can then use targeted data-driven marketing strategies to reach these specific customer groups and boost your sales growth rate.
A good example is this Dropbox Business’s marketing campaign that targeted marketing teams:
You can also shorten your sales cycle with a more direct marketing strategy. That gives you a competitive edge over your competitors. Finally, you can use current sales data to build lookalike customers. As a result, you will reach more prospective customers, cut costs, and maximize your profit.
Choose Data-Driven Strategies for Business
Sales data helps you make informed decisions and choose the right sales strategies. If you learn how to analyze sales data, you can quickly notice trends and patterns that will empower your sales team. They will then help you boost your business’s growth through sales.
As discussed in the article, sales data analysis can lead to business growth by improving retention, better forecasting, accurate value proposition, better pipeline management, and making targeted marketing possible.
Start using data analysis in your sales process to grow your business today.