Introduction

Locale recently worked with an e-commerce company, a Shopify merchant who is the business of food and beverage distribution based out of US. They operate at a huge scale, delivering upto a million shipments a day with upto 20% shipments delivered internationally! The company uses several logistics firms such as DHL, FedX etc for shipping.

Let us take you through how the team used Locale.ai internally to get visibility on the shipping costs as well as the overheads to decide the shipping fees in different parts of the world.

The Business Problem(s)

E-commerce companies and retailers have a huge amount of burden understanding shipping performance and costs across their customer geography. While Covid-19 brought with itself several challenges, a big one definitely was delaing with the demand surge without affecting customer experience. The problems they were looking to solve are the following:

  • True Cost of Shipping: The team had been grappling with the issue of paying overheads to its courier partners. They had no visibility on the true shipping costs to different parts of the globe.
  • Delays and Returns: Along with insights on base shipping costs and additional overheads, they wanted to get insights on delays, returns and cancellations in different areas.
  • Courier Performance: With these insights, they wanted to set up a "control tower" to measure the performance of their couriers and select the right partner for each location.
Locale.ai Shipments
Locale.ai Shipment Analysis
We were silently losing money on shipping but were not capturing that data because we lacked precise visibility into our true cost of shipping i.e. fuel adjustments and post-shipping accessorial charges. – VP, Logistics

The Status Quo

The biggest issue with our client was that the data is split among many different systems: UPS/FedEx/Courier Billing, Label Generation Software, Customer Support, UPS/FedEx/Courier Tracking, Shipment Auditing Systems, E-Commerce Software, etc. Additionally, when they look at performance they look at their regional P&Ls and the granularity is at best by zipcode or city. There’s very little segmentation to better understand their cart performance.

To make any business decision, a business team relies on engineering teams to pass the answers to their queries. Our partner operated on a similar model. However, while they had initially tried to build a product internally, but due to the high engineering effort and the associated costs required to do so, they were on the look-out for a tool that could help their business teams leverage location data and make decisions without over-relying on their engineering teams.

Solution? Enter Locale.ai!

locale.ai comparison
Revenue vs Cost Analysis

At Locale, we believe that any logistics companies with ground operations needs visibility through location analytics to be able to become operationally efficient. Imagine Locale as a tool that helps you get answers to your questions from country level to a building level in a matter of seconds without having to write any code!

The Hows and the Whys of Locale’s Solution

Take a look at the questions that the team asked to help them get relvant insights. This data is mostly coming from 3 sources: e-commerce software, label generation software, and courier fee uploads.

True Cost of Shipping

  • Base Fare: What is the route wise cost per shipment across different areas, warehouses and couries?
  • Overheads: What are the various overheads that are being levied upon the shipment and what are the sources of these overheads? (charged later; organized by category e.g. fuel, residential, undeliverable, redelivery attempts, custom fees). How are they split across different areas, warehouses and couries?
locale.ai iryc console
Locale Mobility Console

Courier Performance

  • Delays: Which shipment routes and couriers are associated with frequent delays? How does that relate with customer complaints?
  • Returns: Which couriers and areas have seen the maximum amount of return deliveries? Is it a warehouse that is causing the returns.
  • Cancellations: Which couriers are associated with the highest cancellation rates in different areas and SKUs? Is this linked to a delivery location?

Outcomes

With these insights, the two decisions that our client made:

  • Adjusting Shipping Fees: For the areas where they were losing out money, they adjusted their shipping charges to maintain their margins and improve their topline directly by 2.67%! In areas where they were profitable, they penetrated further to better serve their existing customers and acquire new customers.
  • Finding the Right Provider for the Right Area: With the presence of multiple providers with different pricing and delivery capabilities, evaluating their performance & having visibility is critical to find the right provider for the right area, after all. Hence, with Locale's "Control Tower", they could ingest shipment information across all couriers and decide which courier is the best in all areas.

Locale Use Cases in E-Commerce

The previous decade has just laid the seeds for a burgeoning e-commerce industry and the results will show how the next decade shall see this sector explode into an even bigger market. Currently, what are the issues that are causing challenges for business teams in e-commerce companies from a geospatial lens?

  • Shipping Cost Visibility: Currently teams are facing uphill tasks with respect to gaining clarity into the spread of user demand, locating bottlenecks in the supply chain and capitalizing on latent demand with their location data. What’s most important is understanding pure shipment data to better understand what’s the total true cost of shipping to different parts of the world.
  • Going Hyperlocal: When you can understand your customer geography with more granularity, it becomes much easier to allocate marketing & operation spend. Retailers and especially e-commerce companies can better understand their most profitable regions and start pursuing hyper-local marketing strategies that will increase sales & reduce their overall operational spend.
  • Customer Support: Companies with a large user base are always trying to visualise how the demand is spread, which areas have a high churn rate, and where complaints are coming because of ETAs being breached, where people have the most problems with the product, where late shipment anxiety is occurring,where people are losing shipments most, etc.

Often, companies search for tools that can be used to solve these problems for them, by using their location data. Luckily, that's exactly what we love to do!‌‌ If you are an e-commerce company using a third party courier service and are excited about these problems, contact us to set up your Locale today. ‌‌

To know more, get in touch with us on LinkedIn or Twitter or dive deeper on our webiste.

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