We invited Nathalie Nahmias, an expert in customer relations and customer experience, to discuss post-purchase data and its activation. Here’s a summary of the webinar, which you can find here.
Understand customer expectations and identify areas of friction
Delivery by appointment: choose the delivery date by appointment
Benefits
Customers’ delivery expectations have changed considerably in recent years. One of the most widespread requests is the possibility of choosing a delivery date. According to the latest FEVAD survey, 48% of online shoppers want this option. Indeed, with telecommuting also more widespread than ever before, consumers are increasingly appreciative of the option of having their order delivered when they are sure to be at home.
Initially, appointment scheduling was mainly used for bulky parcels requiring a physical presence for reception. Today, this flexibility extends to smaller parcels, thanks to the rise of interactive delivery. Customers can now choose a fixed date, or change the delivery on the fly.
Disadvantages
However, this flexibility introduces a new complexity into the management of data and appointments. Ideally, both parties should adhere to a fixed time slot. In practice, delays frequently occur, either at the customer’s or the carrier’s initiative. This poses a challenge when it comes to measuring customer satisfaction: a customer who postpones an appointment by choice generally remains satisfied, whereas a postponement imposed by the carrier often leads to frustration. It therefore becomes essential to trace the origin of the rescheduling in order to evaluate satisfaction more accurately.
Master the calculation of the delivery date
In order to provide the best possible customer satisfaction, it is necessary to determine the delivery date reliably. When placing an order, there are two main approaches to determining the delivery date:
- Direct selection by the customer in the order tunnel: the customer chooses the date and time slot that suits him best.
- Post-shipment proposal: once the order has been shipped, the customer receives an e-mail or SMS notification proposing a default date, with the option of modifying it.
The second method is increasingly becoming the norm.
Asking customers to choose a date when they place an order often leads to abandonment or the need for reminders. Proposing a default appointment, while leaving the customer free to modify it, improves the conversion rate and reduces friction.
Logistics impacts
There are several key steps in calculating a delivery date:
- Order taking: the merchant estimates the preparation and dispatch date.
- Transport plan: each carrier applies its own schedule (24 to 48 hours) to route the parcel.
Any change of date en route has a logistical impact. Transport agencies have limited storage space in m2. A date change of more than 5 days, for example, can saturate these infrastructures. For this reason, relay points generally do not keep parcels for more than a few days.
Connecting and analyzing data to transform it into concrete action
Today, many companies operate in silos: logistics on one side, customer relations on the other, and finally the digital teams. The challenge is to consolidate this data to create a smoother, more proactive customer experience.
Here are the various data analyzed and calculated and the resulting actions:
Transport and logistics
- Package tracking: departure, transit, arrival, delay or incident.
- Calculation of KPIs to trigger proactive actions (notification of package status, delays, etc.).
Customer satisfaction
- Sending satisfaction surveys after confirmed delivery.
Customer service contacts
Analysis of contact patterns (e.g. “Where is my order” – WISMO) to identify friction points.
Case studies
Example 1: Cross-analysis of time and satisfaction (NPS)
An e-tailer compared two carriers he worked with: one delivered in 2-3 days, the other in 6 days. Analysis of the NPS scores revealed a similar level of satisfaction, despite the difference in delivery times. This type of analysis avoids hasty decisions based on speed alone.
Example 2: Analysis of customer service calls
By cross-referencing calls with transport data and notifications, one company discovered that :
- Customers were calling in despite receiving notification of a delay.
- Others called without having received notification.
This highlighted the need to optimize message content and timing.
Real-time information: a crucial lever
Receiving live information enables immediate action. For example, if a delivery is dropped off at a neighbor’s, the information sent in real time means the customer can be notified instantly. This reactivity becomes essential for express deliveries within the hour.
However, real-time information feedback also poses an ecological problem. Querying systems every 30 minutes consumes a lot of resources with limited efficiency. A balance needs to be struck between update frequency and environmental impact.
Artificial intelligence: between promise and reality
While AI is often seen as a miracle solution, its application in transportation remains complex. Generative AI is limited in its ability to provide precise location information in real time. What’s more, chatbots often give inconsistent answers when prompted several times.
Predictive AI, which is supposed to estimate a delivery time, is still struggling to deliver reliable results. Human experience therefore remains essential for adjusting routes to deal with unforeseen events in the field.
Intelligent automation: RPA as an alternative
Before betting on AI, RPA (Robotic Process Automation) offers concrete solutions. It enables repetitive tasks to be automated. For example, if a scheduled delivery to a large surface area fails, an automatic rule can reschedule the delivery without human intervention.
Real-time data and its exploitation pose technical, ecological and human challenges. The challenge is to combine technology and human expertise to deliver a fluid, responsive and reassuring customer experience.