What is the role of data in driving sales?

What is the role of data in driving sales?

10 Min read

Sell to everyone. The more people you try to sell your product or service to, the more chances you have of making a sale. It’s common sense, right?

That was the traditional way of selling. It’s intuition-driven. You know it’s right because your gut tells you it’s right.  

But by selling to everybody, you’re also selling to people who don’t want your product. That’s a lot of time and effort spent on something that’s dependent on luck. 

Fortunately, you don’t have to do intuition-based sales anymore. You have a more potent weapon in your arsenal, which is… data. 

Table of content 

  1. Rise of data and its significance to selling
  1. What is data-driven sales?
  1. What is the role of data in driving sales?
  1. Best practices for developing a data-driven approach to sales?
  1. Conclusion

Rise of data and its significance to selling

While using data is not new, it never was on this level. Why? The availability of big data on this scale was not possible in the past.  

First, storage and access to data are challenging. Most big companies use magnetic storage to store data, which is prone to damage and is expensive.  

But with the rise of software as a service (SaaS) applications that usually use the cloud for storage, everything changed.  

Data storage and access have become easier and economical. Suddenly, data is no longer something those big businesses can use.  

Now every business, big or small, uses data to get an advantage in the market. If you are not using data in your sales process, you are fighting an already uphill battle unequipped.

What is data-driven sales?

Data-driven sales is sales outputs from a data-driven strategy that leverages the collected information in every customer interaction.  

With data-driven sales strategies, your company is better equipped to customize brand and sales messaging, predict and anticipate potential customer needs, and consistently win new customers.  

The adage about working smarter and not harder applies here. With data, you can intelligently focus your efforts on things that matter instead of blindly selling to anyone willing to hear you.  

For example, you can analyze where most of your callers are coming from by using data from your communications solutions.  

With this information, you can get insights into where your business is getting good engagement with your potential and existing customers vs. the locations where you have no presence.  

From there, you can cross-reference that data to other sources to get a bigger picture about your over-the-phone customer transactions.  

With the right information, you can customize your sales approach based on the goals of your business.  

What is the role of data in driving sales? 

The example above is a simple application of how data can improve your sales strategy. However, the role of data is bigger than that.

It is no coincidence that around 49 percent of companies are now using data analytics, according to State of BI & Analytics Report 2020, a Special COVID-19 Edition by SiSense.

Small businesses, 50 percent of them in particular, are using data in sales. The four key functions of data in sales are to: 

The graphs above show that businesses are using data and analytics more after the pandemic started. (Source)  

1. Significantly improve lead generation 

This is where data’s effect is quickly felt. It is where the shift from “selling to everyone” to “targeted selling” starts.  

Using historical data, many companies develop insights into each area’s potential customers or sales prospects. By cross-referencing with other external and internal data, you can improve the accuracy of your lead generation and better identify the right customers and the right time to contact them. 

Some companies also use artificial intelligence or AI components to automatically process lead generation activities. Then, they identify the most promising prospects.  

2. Maximize customer lifetime value 

Customer lifetime value refers to the worth of a customer to a business throughout their relationship. It is essential because it does more than help you develop solid, data-driven sales strategies, and strategies to retain existing customers.  

This also helps your business reduce customer churn by identifying signs of discontent and dissatisfaction even before the customer makes a complaint. It allows your organization to take action before it leads to a cancellation.  

3. Price your products right 

Determining the right selling price can be the difference between success and failure for a business. It isn’t simply about setting a price lower than your competitors. Doing that can result in getting the wrong message about your product.  

Imagine thinking customers will see your product as affordable but instead be seen as cheap and unreliable. That is why it’s crucial to determine a suitable price that will set your place in the market.  

It’s where data comes in. It’s not just about how to sell but everything that comes with selling, including pricing. Using data from interactions with customers, you can narrow down the price point where customers are most comfortable buying your product. 

From there, you can make reasonable pricing adjustments that would optimize profit and avoid loss. 

4. Match the right people to specific roles

Traditionally, hiring the right salespeople relied primarily on the judgments of sales managers to determine talent. 

However, with the abundance of information available, determining the right people for the job has become more data-driven.  

By combining data from sales, customer interactions, and HR (human resources), you get a clearer picture of what personalities and traits are needed to drive sales success. It allows businesses to identify the best talents and allocate them to the proper accounts.  

In addition, you also eliminate some manual tasks by automating some of the human-related tasks like data entry. By automating tasks like data entry, you remove the need to hire more personnel for a simple job, you take away the element of human error, and you can refocus your hiring efforts to finding the best talent for your sales team.

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Best practices for developing a data-driven approach to sales 

1. Align your objectives, metrics, and data 

The first step to a data-driven sales approach is to determine the objectives and goals of the team. Every team member should be aligned with the primary objectives and the short-term goals needed to achieve them.  

After that, you have to determine what types of data are available to your team. Data can come from the tools you are using, including your customer relationship management app (CRM), your business communication platform, or business productivity apps.  

You can also collect feedback and reviews from customers, and of course, your actual sales performance data.  

From there, you also want to determine how you plan to measure success. It includes the key performance indicators that will show the success or failure of your data-driven sales strategies.

An excellent example of this practice is sales funnel metrics. The end goal, of course, is profit or revenue, but there are short-term goals for each funnel.  

The top funnel is about creating awareness, and the metrics associated with this are usually website sessions, unique visitors, new accounts, etc. In this stage, you’re not concerned with the conversion but just putting your name and your product out there. 

The middle funnel, on the other hand, is about engagement and building trust. Some of the metrics associated with this funnel include page sessions, accounts engaged, and churn. At this stage, you are now converting possible leads to sales conversion opportunities.  

The bottom-funnel, of course, is conversion. It’s where you close the deal. Some of the common KPIs are qualified leads, accepted leads, and the most important, conversion rate. 

Image shows a typical sales funnel and the metrics to measure success in each stage. (Source

2. Customize insights to the needs of your sales team 

When distributing information from data analysis, the policy should be on a need-to-know basis. It’s not about withholding information but rather about avoiding information overload.  

Your salespeople do not need to know the nitty-gritty of the data and how you analyzed it. What they need is the insights you gathered from the process. Things that they can apply when they are interacting with prospects or potential customers.  

A great way to go about this is through dashboards. It is a visual display of your data. Instead of showing the spreadsheets, you can use dashboards to convey your analysis findings and insights.  

Customize your dashboards depending on who will be looking at them. The dashboard for C-executives who are more concerned with the bottom line will differ from the dashboard you present to sales managers who are more concerned with increasing sales conversion.  

From there, the stakeholders can strategize action points that can be applied to their respective roles. 

3. Break down silos in customer interactions 

Traditionally, each department is doing its own thing. Marketing, sales, and support are doing their own data collection, analysis, and campaigns without communicating with each other.  

It’s not maximizing the resources the company has at its disposal because there’s no information sharing.  

To optimize your data-driven sales approach, you must break down your silos. Not only would your team members be on the same page, but your departments as well.  

Yes. Marketing and sales traditionally have different metrics that measure success. Marketing may be content in producing many leads, but it may leave sales unhappy when there’s a low number of conversions. For them, quality leads trump quantity.  

One of the best examples of where companies can have unified data for sales, marketing, and even customer support is in digital marketing. Every touchpoint in your website produces data that all departments can access and use throughout the company. It includes metrics like time on site, engagement, and churn.  

From these uniform sets of data measured, you can set integrated campaigns that aim to improve the quality of leads from marketing, which improves conversion for sales and decreases customer dissatisfaction for customer support.  
 

4. Train your sales team and give them the right tools 

Applying insights derived from data analysis is not easy. You cannot expect your sales team to become proficient with new strategies overnight.  

That is why training plays a big part in helping them understand the new concepts and overcome their old instincts that counter the new strategy.  

It also helps if you equip them with the right tools so they can focus on their sales interactions. Salesmate, in particular, combine CRM functions with automation functions that help them focus on closing deals and not worry about repetitive tasks.  

Conclusion 

By combining data with your sales process, you eliminate a lot of the guesswork and focus your efforts on things that matter.  

And it doesn’t only help you in just the act of selling. From identifying the right customers to setting the right price and hiring the right talent, a data-driven sales approach provides insights that can help you make better decisions not only to close sales but also to keep existing customers.

Mark Dacanay is a Digital Marketing Professional who has been working with RingCentral offering enterprise communication tools and VoIP solutions for more than five years. He is obsessed with anything about the cloud – the technology, not the fluffy stuff in the sky

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