Sales and marketing teams are no strangers to predictive analytics. Large and small enterprises keep adopting this technology for numerous reasons, like increasing CR or refining their lead gen strategies.

The latest big data trends reflect that predictive models remain one of the leading technologies worldwide. It is hardly surprising since enterprises of all sizes keep digitizing their operations. And as a result, the volumes of captured, created, and consumed data continue to grow.

How can a marketing and sales team use this technology to achieve its objectives? Since one of the goals is to attract qualified leads, marketers need to collect pertinent demographic and behavioral data. And predictive analytics is the sure-fire way to get this information.

How Predictive Analytics Drives Value

Let’s face it: there is nothing revolutionizing about the concept of carefully studying and utilizing the collected information. But recent advancements in data science, deep and machine learning have established the basis for vast stores of data that can be automatically parsed and aggregated.

Companies deal with numerous transactions, log files, and data sources daily. So gaining predictive insights can help them pinpoint the risks and assess the potential of specific marketing campaigns.

It is no secret that consumers expect to find personalized solutions and receive hyper-personalized offers from brands. It means that today, companies have to consider the level of appeal when identifying the most lucrative offers. In other words, it is crucial to predict customer needs and estimate which marketing efforts are likely to generate the highest ROI.

Let’s look at the example. Such streaming services as Netflix use this technology to identify individual viewing patterns and offer specific recommendations to their clients. Simply put, if you spend countless hours watching Sci-Fi and horror movies, you will be offered to watch similar or somewhat similar content that suits your viewing needs.

Data analytics allows evaluating these massive volumes of data, leveraging historical data, and making educated guesses and predictions about possible results. The technology encompasses data mining, machine learning, and predictive modeling techniques. Predictive modeling uses existing data as part of an algorithm model to help marketers design their growth strategies, optimize their spending and resources.

When it comes to call analytics, it is crucial to test the strategies. That is why a modeling feature can help brands make data-driven decisions. For instance, it allows visualizing the probable outcomes. In other words, you can test the strategy and adjust the variables without the need to spend money or launch the campaigns.

Naturally, every industry-specific strategy requires a comprehensive approach. If your campaigns drive numerous calls, then utilizing advanced call analytics software is what you need to evaluate and assess all the data collected from similar campaigns before.  

What does advanced call analytics software do? In a nutshell, it enables companies to collect insights on all their campaigns and access the performance breakdown. The latter implies that the success of every campaign can depend on time, location, or specific keywords. Gaining access to such analytical tools and reports can significantly improve sales logic and simplify core marketing processes.

Let’s look at how predictive modeling can help sales and marketing teams to get the most of lead gen campaigns.

#1. Increasing the Value of Your Leads

Let’s be fair: attracting leads is not enough. Businesses must convert them and keep the CR high.

Here is what you need to control:

The lead quality;

The performance of your campaigns.

Predictive modeling tools like Waves can come in handy if your goal is to generate more sales and revenues.

#2. Tracking and Measuring Call Outcomes

Automated systems allow brands to track their inbound calls and analyze historical data. This way, they can compare the past and current performance of their call campaigns.

Combining several tools with call analytics software can help sales teams get a complete and correct view of the customer journey.

#3. Creating a Pen Portrait of Your Audience

The ultimate goal is to understand the data created by consumers while they interact with the funnel. Every touchpoint, every interaction can be aggregated and used for modeling purposes. This way, the company can assess the overall performance and get a sense of where things are going.

With predictive analytics, brands can comprehend the collected data, identify lucrative opportunities that might have been lost at some point, and set up more efficient business operations.

#4. Improving Customer Retention

Once the leads get converted, businesses need to engage and interact with customers to keep the retention rate high. But what if some of the customers decide to leave?

With predictive analytics, enterprises can make use of the data consumers leave behind. Simply put, it is possible to determine and assess specific warning signs and identify the clients who might end up leaving as well. This way, brands can make a sensible decision about adding services to specific packages or offering some tools for free.


Predictive insights can be used by any enterprise regardless of the industry. This technology can contribute to setting up, supporting, or optimizing the marketing processes at any stage.

Ultimately, call analytics software and the technology itself help brands understand their products, clients, and partners better. By leveraging predictive insights, your marketing and sales team can run scalable campaigns and ensure the highest CR and ROI.