Artificial intelligence (AI) is proving to be a substantial driver and differentiator to the success of the global economy. More than ever, retailers have the unique possibility to leverage the power of AI in their services. In particular, inventory and delivery management are and going to stay key domains for substantial retail growth, powered and emphasized further by machine learning. In recent years, data-driven decisions regarding intelligent shipping optimizations, inventory management, and delivery date estimations have become more prominent and important. This analytical influence is instrumental in enhancing the customer experience throughout their journey.
One of the key customer satisfaction drivers is the successful management of delivery expectations. More than 60% of customers would rather have their delivery date estimated correctly than a fast shipping option, proving the importance of predictive algorithms in achieving high delivery standards.
What is Trending Late?
In response to the constant need for better tools to manage delivery expectations, parcelLab has successfully revolutionized how retailers handle potential deliveries and their implications. This industry transformation comes from our latest AI system, Trending Late. At its core, Trending Late has been designed to estimate the probability of a delivery delay in the post-purchase stage, utilizing vast retail and industry-specific data. Crafted with versatility in mind, this complex AI system extends its application to various areas of retail interest, including order marking, communication triggering, order filtering, and more—all powered by its predictions. Trending Late elevates the efficiency and responsiveness of post-purchase processes, aligning with the dynamic landscape of consumer expectations, while seamlessly working in the parcelLab product environment.
This new predictive machine learning model uses a sophisticated gradient-boosting tree-based algorithm to predict the likelihood of a delay occurring throughout the delivery process from start to finish. The AI model takes into consideration a vast list of attributes that are based on industry and carrier data inference when it comes to deliveries. All predictions are referenced against the provided announced delivery date, sourced from either parcelLab Promise or directly provided by the retailer. The development processes involved intricate data collection and processing, accompanied by vigorous feature engineering and model training. The result is an agile and intelligent system that learns patterns and correlations from large historical datasets, empowering it to make accurate and reliable predictions that were not possible before.
The testing process does not fall short either, proving our AI model’s profound technical advantages. By testing with both our large historical data and with BETA customers, we have identified the potential of Trending Late to predict delays exceptionally early in the shipping process, even before the carriers themselves, reaching accuracy scores of more than 97%. Furthermore, ongoing training with additional operational data can make predictions possible before the shipping phase, showcasing the model’s adaptability and multiple capabilities.
Through our unparalleled model monitoring availability, we have opened avenues for continuous performance measurements and automatic iterative improvements. This ensures that the model evolves in tandem with the dynamic operational landscapes, considering both the industry and retail custom data.
By striving towards personalization and adaptability, we were driven to add yet another distinctive feature to Trending Late: the ability to leverage customized thresholds. This approach, informed by meticulous data analysis of diverse variables like regional and carrier data, provides high flexibility for retailers and their needs. It empowers them to adjust to real-world conditions dynamically and the intricacies of operational reality, ensuring a finely tuned and responsive system.
How our AI solution can benefit your business
From a business standpoint, Trending Late introduces a host of opportunities to streamline operations and enhance customer relationships. Primarily, it reduces the burden on customer support teams, minimizing the need for routine inquiries about order status. This efficiency not only improves the overall customer experience but also allows support teams to concentrate on different issues, fostering long-term improvements.
Moreover, the predictive nature of the tool enables proactive measurements to prevent customer dissatisfaction and potential reputational brand damage. Timely interventions and issue resolutions contribute directly to heightened customer satisfaction, translating into reduced returns, customer exchanges, and a shortened time to the next order. In essence, the transparent communication of potential delays establishes a foundation of trust with customers, which is pivotal for their retention and loyalty, further solidified by the accuracy of the predictions. As a result, the Trending Late system becomes a strategic asset for businesses aiming to optimize customer relations, minimize operational complexities, and foster loyalty, followed by long-term success.
At parcelLab, we have developed a state-of-the-art AI model that empowers businesses with a notable competitive edge. Providing accurate delivery predictions throughout the whole order journey not only distinguishes a business from its competitors but also serves as a crucial factor in a market where customer experience holds substantial importance. Accurate and confident predictions have the power to not only attract but also retain customers. The insights, generated by AI systems, contribute valuable data, enabling strategic decision-making. This data becomes a cornerstone for ongoing improvements in processes, the fine-tuning of delivery strategies, and the agile adaptation to fast-paced evolving market conditions.
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