Smarter Sales Through Data: allcargo’s AI-Driven Approach

in today’s competitive logistics landscape, Indian giant Allcargo Logistics is turning to advanced data analytics and machine learning to enhance its cross-selling strategies. The goal? To offer customers additional services without overwhelming their sales teams. This initiative aims to boost revenue by identifying and targeting customers most likely to benefit from supplementary offerings.

The Cross-Selling Challenge in Logistics

Cross-selling, the practice of offering additional services related to a company’s core business, is a common growth strategy. For logistics firms like Allcargo,this could mean offering insurance,customs clearance,or extensive supply chain solutions alongside services like container loading,air freight,or warehousing.According to Ramgopal Prajapat, Senior Vice President of AI and Data Science at Allcargo Logistics, this approach can considerably increase annual revenue per customer.Though, the challenge lies in identifying and effectively targeting the right customers to avoid overburdening sales teams.

The sale of additional products and services to existing customers is though much more profitable than the acquisition of new customers.
Ramgopal prajapat, Senior Vice President of AI and Data Science at Allcargo Logistics

Unlike sectors like banking, logistics companies often lack comprehensive data on whether their customers are already using related services like insurance or customs clearance. Furthermore, the logistics industry faces a low average conversion rate for customer outreach, hovering around 1.5%, as highlighted in a 2023 study by Ruling Analytics. This means a meaningful number of calls are needed to close a single transaction, placing a strain on already busy sales teams.

Creative Data Solutions for Targeted marketing

To overcome these challenges,Allcargo Logistics is adopting innovative methods to gather and analyze data. One approach involves exploring public data sources to identify companies engaged in shipping activities with competitors, thereby indicating potential needs for additional services. This proactive approach allows Allcargo to identify potential customers who might potentially be using competitor services.

Machine learning is then used to analyze the ancient behavior of potential targets, identifying patterns and predicting their needs. For example, Allcargo is exploring whether AI can improve conversion rates by proactively contacting the 10% of customers identified as most interested in additional services. The company also uses AI to identify “similar customers” – those with characteristics and behaviors similar to existing users of complementary services – and target them with relevant offers.

Case Study: Optimizing Full Container Load (FCL) Sales

Allcargo Logistics put its machine learning hypotheses to the test with a specific project focused on identifying customers with a high potential interest in full Container Load (FCL) services. The initial dataset included 3,000 customers representing 80% of the FCL volume over the past three years, and also 20,000 users of Less Than Container Load (LCL) services who had never used FCL. Among these, 2,000 were already customers of othre Allcargo Logistics products.

To refine this target group, Allcargo used machine learning to model the characteristics of existing FCL customers. The AI and Data team then tagged the 5,000 most engaged LCL customers and used a “closest neighbors” (K-NN) algorithm to identify 10 “similar” customers for each FCL customer. they extracted customers who did not currently use FCL and prioritized those with the closest similarity to existing FCL customers.

Notable results and future Implications

The results of this targeted approach were significant. Allcargo Logistics achieved a conversion rate 2.5 times higher compared to previous awareness campaigns, demonstrating a more efficient use of sales resources and a stronger impact on revenue with less effort.This success highlights the potential of machine learning to transform cross-selling strategies in the logistics industry.

A conversion rate 2.5 times higher compared to previous awareness campaigns… a stronger impact on income with less effort.
Ramgopal Prajapat, senior Vice President of AI and data Science at Allcargo Logistics

As AI and machine learning technologies continue to evolve, logistics companies like Allcargo Logistics are poised to unlock even greater efficiencies and revenue opportunities through data-driven cross-selling strategies. This approach not only benefits the company but also provides customers with more tailored and relevant service offerings.