Imagine ordering a high-end jacket online. The estimated delivery date comes and goes. You check the tracking – “delivered.” But there’s no package. You contact support, they investigate, and frustration builds. Now multiply this by thousands of shoppers.
This is the reality for many brands, and poor delivery experiences create ripple effects — lower shopper satisfaction, more support tickets, and operational headaches.
Retail and logistics leaders know these challenges well. In our recent survey, 73% of respondents said delivery speed and reliability are the most important factors when selecting a 3PL, and 51% said improved tracking and visibility are key benefits of a last mile carrier service. These numbers show a clear demand for precision, reliability, and real-time visibility in the last mile.
This is why GoBolt is using AI and machine learning to fix these inefficiencies before they become problems.
Continue reading to see how we’re using AI and machine learning to power faster, smarter logistics:
Major Pain Points in Last Mile Delivery
- Operational Inefficiencies – Many brands (and their last mile carrier of choice) struggle with inconsistent proof of delivery (POD), poor visibility into last mile performance, and manual issue resolution that slows down operations.
- Shopper Satisfaction Concerns – A missing or unclear POD can lead to disputes, support escalations, and frustrated customers. In our recent survey, 55.5% of surveyed logistics leaders cited customer service and support as key factors when selecting a new 3PL, reinforcing the need for proactive issue resolution.
- Technology, Cost & Performance Challenges – Many retailers lack real-time insights to optimize last mile delivery, leading to inefficiencies and higher costs. Nearly 60% of respondents said that last mile performance and cost tracking are crucial for their operations, yet many struggle with fragmented technology that doesn’t provide full visibility. This growing demand for smarter, data-driven decision-making highlights the need for integrated AI solutions.
How GoBolt’s AI & Machine Learning Solve Last Mile Inefficiencies
Smarter Customer Insights with AI-Powered Sentiment Analysis
- We use Vertex AI and Google Gemini to analyze customer reviews, sorting feedback by sentiment and reason.
- This data is then pushed to our operations team, helping improve processes and performance in real-time.
AI-Powered Proof of Delivery (POD) for Accuracy & Trust
- AI provides real-time guidance to drivers to capture high-quality POD images, ensuring clear visibility of the package and drop-off location.
- This helps prevent “delivered but not received” claims by improving POD accuracy.
POD Quality Control for Carrier Reports
- Our Fleet Operator portal uses machine learning to flag low-quality or incorrect PODs.
- The Operations team then follows up with delivery partners immediately, ensuring better compliance and accountability.
“At GoBolt, we’re always looking for ways to enhance the customer experience, and AI is at the center of that,” says Lamya Ezzeldin, Sr. Product Manager – Transportation at GoBolt. “By leveraging machine learning for real-time insights, we’re able to identify inefficiencies before they become issues, optimize last-mile performance, and improve our proof of delivery accuracy. This helps our brand partners deliver on their promises to their customers, while also streamlining operations.”
AI in Action: Elevating Last Mile Efficiency
By integrating AI into our last-mile logistics, GoBolt reduces delivery issues, improves compliance, and enhances shopper satisfaction. With 73% of brands prioritizing delivery speed and reliability when selecting a 3PL, and 51% saying improved tracking and visibility are major advantages of a last mile carrier, GoBolt is well-positioned to simplify your logistics.
At GoBolt, we don’t just deliver packages, we deliver certainty. Want to see AI-powered logistics in action? Contact us to book a meeting today.
