Predictive Promising: The Future of Delivery Estimates

In the competitive world of retail and grocery, every advantage counts. There's one often-overlooked factor that has a surprisingly big impact on customer satisfaction—the accuracy of estimated delivery dates (EDDs). Think about the last time you ordered something online. Did a clear delivery window help you relax and get excited about its arrival? Or did a long, vague timeline have you glued to the tracking info every few minutes? We've all been there.

That's why we're diving deep into the power of accurate EDDs. We'll explore the benefits they bring to both you and your customers, the challenges retailers face in getting them right, and how innovative solutions like predictive promising can make a huge difference to the delivery experience.

Firstly, let’s talk about why getting EDDs right matters so much.

The Power of Knowing When It Arrives

Accurate EDDs are a double win for your business. Firstly, they build trust and eliminate uncertainty at a crucial moment when shoppers are on the fence about a purchase. This transparency can nudge them towards that all-important, "complete order" button, boosting your conversion rates.

Secondly, accurate EDDs significantly reduce the dreaded "Where is My Order?" (WISMO) inquiries. Inaccurate EDDs create confusion and frustration for customers, leading to a surge in these inquiries. By setting realistic expectations, you can slash the number of WISMO inquiries and free up valuable customer service resources for more pressing matters.

Hidden Potential in Your Existing Networks

The good news? Many retailers and grocers with intricate fulfillment networks might be underestimating their ability to deliver faster. This hidden potential translates to missed opportunities to delight customers with quicker deliveries and potentially gain a competitive edge.

Brick-and-mortar stores can be a game-changer for quicker deliveries, especially for customers in close proximity. However, effectively integrating them into EDD calculations requires sophisticated planning. This involves accounting for processing times within stores and ensuring inventory availability to meet the promised delivery window.

Relying on drop-ship vendors for specific items introduces an element of uncertainty into delivery timelines. Retailers often factor in overly conservative estimates based on the vendor's lead times to avoid disappointing customers with late deliveries. A common strategy is to set intentionally long EDDs to ensure on-time deliveries and exceed customer expectations. While this might seem positive on the surface, it sacrifices transparency.  More importantly, it misses the opportunity to offer faster, more competitive delivery options that can win over customers.

Building a Foundation for Accurate EDD

Creating these specific and accurate delivery promises is no easy feat. It involves a complex setup process and ongoing analysis.

The foundation for accurate EDDs starts with a thorough analysis of historical data. Retailers need to delve into their past fulfillment performance to understand their realistic delivery capabilities.

Once you have that understanding, the real work begins. A multitude of factors need to be precisely configured to reflect your specific fulfillment network.

This includes:

• Node Processing Times & Cutoffs (Stores and FCs)
• Node Capacity and Availability
• Item Eligibility, Exceptions
• Inventory
• Node / Carrier Eligibility
• Transit Days
• Operating Calendars
• Static Cut-offs & Buffers

The work doesn't stop after this initial configuration. Once you have made these decisions, you must constantly analyze your performance against this specific EDD. Think of it like checking the weather forecast – you wouldn't rely on a week-old prediction, right?  This ongoing analysis lets you see where adjustments might be needed so you can fine-tune the system to keep those EDDs accurate.

Why Retailers and Grocers Leave Speed on the Table

Despite the clear benefits of accurate EDDs, many retailers continue to struggle with prioritizing them. The reason? Complexity. Configuring and maintaining a system for pinpoint delivery promises can feel like a daunting task.

A recent Maergo study revealed a significant gap between retailer practices and consumer expectations when it comes to delivery date transparency. The study found that 92% of consumers who don’t select expedited shipping options are left in the dark about when their orders will arrive. Many retailers offer free shipping but fail to communicate the associated delivery timeframe, which leaves customers frustrated and guessing—ultimately resulting in cart abandonment and missed sales opportunities.  

Ditch the Complexity and Embrace Speed with Predictive Promising

Nextuple's Predictive Promising microservice cuts through the complexity and empowers retailers to leapfrog the EDD challenge. This innovative solution lets you offer accurate, day-level delivery promises that are likely faster than what you're currently offering, all without extensive analysis, setup, and ongoing monitoring.

The Predictive Promising microservice utilizes artificial intelligence (AI) and machine learning (ML) to analyze your historical node and carrier performance data. It factors in every relevant detail you'd want to consider—time of day, item type, fulfillment performance, seasonality, and more—but without any manual configuration. Imagine having an EDD system that considers all these variables automatically. Our Predictive Promising still considers your fixed rules based on item or node restrictions (such as only shipping these products from DC’s, for example). 

The results speak for themselves. Based on our work with leading omnichannel retailers, our analysis shows that Predictive Promising can reduce your average delivery promise by 2.5 days. That's a significant improvement that can directly translate to happier customers and a competitive edge. 

And the accuracy of a predictive promise based on actual historical shipments? An amazing 99% accuracy rate.

If you rely heavily on drop-ship vendors in your network, the potential benefits are even more substantial. Traditionally, retailers use contractually set shipping lead times from these vendors, which may not reflect reality. Predictive Promising bridges this gap by analyzing actual performance. In one instance, we saw a retailer achieve a 6-day difference between their current promises and those generated by predictive promising.

Check out what goes into our Predictive Promising ML model right here:

In addition, our Predictive Promising engine comes with a full explainability feature set. You’ll be able to look at any promise the solution made and see the factors and weights used to determine the outcome.

Are you ready to leapfrog the promising problem? Check out our ROI calculator tool to see how much a faster, accurate EDD is worth to your organization.