Amazon Once Sold a ₹185 Surf Excel Pack for ₹82,740 After an Excel Error

A spreadsheet mistake on Amazon India once turned an ordinary ₹185 pack of Surf Excel into an ₹82,740 listing. Within about 40 minutes, 90 customers had ordered the product, creating nearly ₹74 lakh in transactions that Amazon then had to reverse.

The unusual 2015 incident was recently recalled by Anubhav N, Business Head at Amazon, in a LinkedIn post describing one of the more unusual pricing and fulfilment problems he encountered during his tenure at the company.

How a ₹185 Surf Excel Pack Became an ₹82,740 Product

According to Anubhav’s account, Amazon India had introduced its household supplies and personal care category only a few months earlier.

At the time, Cloudtail, which was among Amazon India’s major sellers, was handling products and pricing for the category.

The problem began when an Excel spreadsheet was uploaded with a data-column error. The date column effectively shifted into the price column, converting a date-related value into a numerical figure.

The result was an extraordinary price change.

A Surf Excel pack that normally sold for around ₹185 appeared on Amazon at ₹82,740.

The listing went live at around 6 pm.

What followed was not what the team expected.

The ₹74 Lakh Detergent Rush

An unusually high price might normally be expected to discourage customers from buying a product.

Instead, the listing was reportedly circulated on Twitter, accompanied by suggestions that customers could place orders, retain their invoices and potentially approach a consumer forum seeking compensation.

Orders began arriving rapidly.

According to Anubhav’s account, 90 packs were ordered at ₹82,740 each within roughly 40 minutes.

That translated into approximately ₹74 lakh in order value for a product that ordinarily cost around ₹185.

On paper, it looked like an extraordinary sales performance.

In reality, it created a major operational problem.

Amazon had to correct the price and, more importantly, prevent the incorrectly priced products from being delivered.

Why Cancelling the Orders Wasn’t Easy

Amazon’s fulfilment system was designed to move products quickly from warehouses to customers. Stopping incorrectly priced orders therefore became increasingly difficult as each order progressed through the logistics chain.

Anubhav said the team spent around 12 hours dealing with the 90 orders.

The orders were at different stages of fulfilment:

• 55 orders had not yet reached the warehouse and could be cancelled relatively easily.
• 15 orders had reached the warehouse and required additional managerial approvals to stop.
• 12 orders had already been packed and were ready for dispatch.
• 8 orders had left the warehouse for morning delivery.
• 2 orders were already with delivery personnel preparing to begin their routes.

The final two shipments required Amazon’s operations team to track down the delivery personnel and instruct them not to deliver the products.

The incident illustrates how a seemingly simple pricing error can become significantly more complicated once an order enters a large-scale fulfilment network.

A 1 AM Phone Call and Emergency Approvals

The situation became particularly difficult for the orders that were already close to customers.

According to Anubhav, he had to wake his category director at around 1 am to obtain approval to stop shipments that had already been packed.

The eight orders that had already left for delivery required further intervention, including approval from Amazon’s country head to intercept them.

By the time the operation was complete, none of the 90 incorrectly priced Surf Excel packs were delivered to customers.

What Caused the Amazon Pricing Error?

The underlying problem was not described as a deliberate price change.

Instead, it was a spreadsheet formatting or column-positioning mistake in which a date value effectively ended up in the price field.

Excel’s treatment of dates and their underlying numerical values can produce unexpected numbers when data is moved between columns or imported incorrectly.

In this case, that apparently transformed a normal detergent price into a figure of ₹82,740.

The episode demonstrates one of the risks of relying on manually maintained spreadsheets for commercial data: a small data-structure error can have consequences once the information is connected to an automated retail system.

When an Excel Mistake Meets E-Commerce Automation

The Surf Excel episode is notable not simply because of the unusual price, but because of what happened after the error reached Amazon’s marketplace.

Once the incorrect price became publicly visible, customers could place orders through the normal purchasing process.

The company’s logistics infrastructure then began treating those orders like legitimate purchases.

That created a race against Amazon’s own fulfilment system.

The further an order travelled through the supply chain, the more difficult it became to stop.

This is a useful example of the trade-off inherent in highly automated e-commerce: automation can make fulfilment exceptionally fast, but correcting an error can become more complicated when an incorrect transaction has already entered the system.

The Unusual Lesson Anubhav Took Away

For Anubhav, the episode also resulted in a personal lesson.

He said the experience made him wary of using Excel for dates.

There was also an ironic outcome to the incident: during his time at Amazon, he recalled being praised for making sure products did not get delivered.

The episode ultimately became an unusual example of how a tiny spreadsheet mistake could trigger a chain reaction involving customers, warehouse teams, managers, delivery personnel and senior executives.

More than a decade later, the story remains a striking reminder that even sophisticated e-commerce operations can be disrupted by something as ordinary as a spreadsheet error.

Key Facts at a Glance

Detail	What happened
Normal Surf Excel price	Around ₹185
Incorrect Amazon price	₹82,740
Orders placed	90
Approximate order value	₹74 lakh
Year	2015
Reported cause	Excel spreadsheet column/data error
Time taken to resolve orders	Around 12 hours
Products delivered	None