The Power of Data Science and Predictive Analytics in Modern Sales

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Ahmed Mainul
Ahmed Mainulhttps://www.hospitalitycareerprofile.com
Ahmed Mainul (Mainul Mondal) is a seasoned journalist with extensive experience in hospitality news, executive appointments, biographies, and industry updates. Having worked with reputed hotel brands like Marriott, Taj, and others, he brings a wealth of industry knowledge to his writing. His deep understanding of the hospitality sector and his commitment to delivering insightful stories make him a trusted contributor to Hospitality Career Profile
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Sales today is completely different from what it was ten years ago. As Neeraj Athalye, Vice President & Head – APAC at Icertis, explained during the Expert Edge session, ‘The amount of information your customer has about you is 1,000 times more than it was ten years ago.’ This shift has made data science and predictive analytics essential tools for sales professionals.

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“The places where a customer tries to understand whether this solution is meant for them start way before they meet the sales guy. For a salesperson, it’s important to understand the buying journey of a customer—when does he start hunting and where does he go?”

Thanks to data driven insights, sales teams can now get a better idea of what customers need, how they buy, and what they might want next—without having to guess or rely on old-school sales tactics.

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How Predictive Analytics is Changing Sales

Neeraj compares the shift to cloud adoption in sales, explaining, “Cloud completely changed the way customers started buying, companies started selling, and organizations started servicing.” In the past, sales would start only when a customer raised their hand and expressed interest. Today, predictive analytics enables sales teams to engage customers long before that moment.

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“Now, it starts much earlier because the customer searches for solutions on YouTube, on websites, and attends events. The places where a customer tries to understand whether this solution is meant for them start way before they meet the sales guy.”

Predictive analytics helps sales professionals by:

  • Spotting promising leads before they even express interest.
  • Analyzing customer behavior to determine the right timing for engagement.
  • Automating recommendations on the next best action based on past interactions.

Neeraj elaborates, “For a salesperson, it’s important to understand the buying journey of a customer—when does he start hunting and where does he go? Is your organization ensuring that they are giving the customer the right information at that stage?”

With predictive analytics, sales no longer start when a customer reaches out—it starts when they begin their research.

AI in Sales: The New Normal

AI-powered tools are now essential for sales success. Neeraj highlights, “My tools for selling are becoming smarter than me. I hate to say this, but because I know this, I have decided to leverage this fact.”

AI assists sales professionals by:

  • Analyzing data trends to predict which customers are most likely to buy.
  • Providing automated recommendations on follow-ups and engagement strategies.
  • Speeding up the sales process by focusing on prospects ready to buy.

“AI tools can recommend the best approach to be taken based on the data. For instance, they might suggest sending a customer an email or improving your solution demonstration with the pre-sales team.”

AI-driven insights can help sales teams focus on the right opportunities at the right time instead of following low-priority leads.

The Evolution of Sales Roles in a Data-Driven World

With the rise of predictive analytics, the role of a salesperson has also changed. Neeraj explains, “The life of a sales guy used to stop at selling the software, taking the money, and moving on. Now, it’s a full 360-degree journey. You must stay in touch with the customer all the way until renewal, or they won’t renew.”

The modern sales process now involves:

  • Continuous engagement: Sales teams must track customer interactions even after a deal is closed.
  • Customer retention strategies: Predictive analytics helps detect early signs of churn and suggests interventions.
  • Personalized selling: AI ensures each customer interaction is tailored to their specific needs.

Neeraj emphasizes, “If you drop the ball and leave the customer after the first year because you’ve done your target and went to Hawaii, rest assured after three years, he’s not gonna renew.”

This data-driven approach makes sales more strategic, ensuring long-term success rather than just short-term wins.

Neeraj sums it up perfectly: “Nobody cares how much you know until they know how much you care.” Predictive analytics and AI are not just tools—they are reshaping how sales professionals build relationships, understand customer intent, and drive revenue growth. The future of sales is no longer reactive—it is data-driven, proactive, and deeply personalized.

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