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Contract renewal: predicting renewals and timing

For companies offering fixed-term leasing contracts, understanding whether customers will renew and when is critical. As contract end dates approach, uncertainty often remains about customer intentions. This makes it difficult to plan sales activities, allocate resources efficiently, and retain customers.

Without clear insight into renewal behavior, organizations face several challenges:

• Missed renewal opportunities

• Inefficient sales planning and misdirected dealer efforts

• Higher customer churn

• Unpredictable renewal revenue

As one finance manager put it:
“How can we predict which leasing customers will renew and when so dealers can contact the right customer at the right time?”

A predictive, data-driven renewal process

Contract renewal analytics address this challenge by using historical contract, customer, and behavior data to build a predictive model that estimates:

• The likelihood that a customer will renew their contract

• The expected timing of that renewal

This shifts the renewal process from reactive follow-ups to a proactive, structured approach.

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Turning predictions into action

The model outputs are directly usable by sales and service teams:

• Dealers can prioritize customers with the highest renewal likelihood

• Customers are contacted at the optimal moment, based on predicted timing

• Sales resources are allocated more efficiently across the customer base

Business impact

This data-driven approach delivers clear benefits:

• Proactive customer engagement instead of last-minute outreach

• More efficient use of sales and service capacity

• Reduced customer churn

• Better visibility into renewal behavior and customer lifecycle patterns

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By transforming contract renewals into a strategic, insight-driven process, organizations improve both operational efficiency and long-term customer retention, while making renewal revenue more predictable.

Geo dashboarding: data-driven B2B prospecting by region

Geo dashboarding supports B2B marketing and sales teams in identifying and prioritizing prospecting opportunities across different geographic regions. Instead of working with fragmented data or intuition, teams gain a clear visual overview of where potential customers are located and where sales efforts will have the most impact.

The challenge: prospecting without direction

At NMBS, the B2B team is responsible for closing contracts with companies to provide train subscriptions for employees’ daily work commutes. However, several challenges limited their effectiveness:

• Low data maturity: limited insight into current performance and market potential

• Lack of internal alignment: no shared view on priorities or regional focus

• Inefficient prospecting: no clear guidance on which companies to target

Without data insights or visual overviews, the B2B growth strategy felt like prospecting in the dark.

A data-driven approach to geographic prospecting

Geo dashboarding addresses these challenges by combining multiple data sources into one actionable view:

• Internal sales and customer data

• External data sources such as RSZ/ONSS

• Geographic data on office and employee locations

An algorithm enriches and matches these datasets to identify potential B2B prospects and align them with ongoing sales efforts.

From raw data to actionable insights

Using this approach:

• Over 4 million employees were mapped to their office locations

• The share of employees with a feasible train commute was calculated, based on whether train travel time is equal to or faster than driving

• Current versus potential train commute adoption was calculated per company and per region

These insights are then visualized in an interactive geographic dashboard, showing:

• Where NMBS already has strong penetration

• Where untapped potential exists

• Which regions and companies should be prioritized by sales team

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Result: focused outreach and better alignment

By visualizing prospecting opportunities geographically, B2B teams can focus their outreach on companies with the highest potential, align sales and marketing around the same insights, and move from reactive to targeted, data-driven prospecting.