Crystal Balls Anyone who suggests and guarantees specific results should be questioned. Ask them how they arrived at that conclusion and how they can support their claim. Because for any scientific claim to be credible, it must be testable and yield consistent results, regardless of who conducts the experiment or

If it sounds too good to be true, then it likely is. Trust your intuition; it’s woven into your biology and has been used since the beginning of time. If an agency has a sales team, their job is to close deals. If they have a sales team, they will

Welcome back to another insightful episode of Seller Sessions, hosted by Danny McMillan. In this episode, we are rejoined by Mels Terlouw, a seasoned entrepreneur peaking at 9 figures in sales. Together, they delve into the critical but often overlooked topic of addressing customer objections, a vital component of successful sales strategies. Key Insights from Mels

Enhancing Amazon’s A9 with Advanced Semantic Search Capabilities Make sure you read the articles “Demystifying Semantic Matching: How It Powers Amazon and Beyond”, “The Evolution of Matching Products to Search Queries” and “Improving Seasonal Relevance in Amazon Product Search.” Where I cover BERT, BERT SE and Semantic and Lexical Matching. 

Key aspects of Multi – Objective Ranking: 1. Relevance in search rankings is complex and multi-dimensional, encompassing factors like topical similarity, popularity, personalization, and diversity. Defining quantifiable optimization objectives is very challenging. 2. Single-objective optimization models often fail to provide holistic search rankings, leading to the need for multi-objective optimization

Introduction Autocomplete, also known as query auto-completion (QAC), is an essential feature in e-commerce platforms and search engines, and Amazon is no exception. It provides users with suggested search terms and queries based on the characters they have typed so far. Autocomplete enhances the search experience by helping users articulate

Researchers have developed a new technique to help computers automatically understand product photos from the likes of Amazon.com. This saves time from manually labelling product details like brand, size, colour for every item. The goal is getting computers to extract attributes from all types of product photos. Here are a

The Problem Many online shopping sites allow customers to ask questions about products, which other customers then answer based on their experiences. This helps shoppers make informed decisions. However, new or uncommon products often have few or no answered questions. The Proposed Solution To address this problem, researchers propose an

How Amazon’s A9 Search Engine Stacks Up Against Google and Bing Search engines like Google, Bing, and Amazon’s A9 utilise the internet to provide relevant information. Under the hood, their technologies are more similar than different despite being made by competing companies. This article examines how Amazon’s search engine A9

Introduction Pricing consistency across different sizes of the same product is critical for customer experience and perception of value. However, maintaining rational price ladders (Pricing ladders relate to prices across different sizes) for size variants is challenging with large product catalogs and dynamic pricing. This paper studies techniques to measure

The premium priced product conundrum. Shopping online is now the norm for many people. Without the ability to physically examine products, online shoppers rely heavily on product information provided by sellers and other customers to evaluate quality. But how do people really perceive product quality online? What information do they

Searching for new and relevant products online often leads to frustrating, irrelevant results. This “cold start” problem has persistently challenged e-commerce companies for years. However, significant progress has been made between 2016 and 2021 in developing solutions to overcome this issue. This in-depth article traces the key milestones researchers have

A study reveals how Amazon’s A9 search algorithm can be enhanced to better connect shoppers with relevant seasonal products. By optimizing listings for seasonal search patterns, sellers stand to significantly boost visibility and sales of seasonal goods on Amazon. The Problem On Amazon, shoppers use the same search queries year-round,

Generic, high volume search queries are the bread and butter of any e-commerce site. But a big chunk of Amazon’s searches come from obscure long tail keywords searched rarely if ever before. These long tail queries create unique challenges for Amazon’s search algorithms and third-party sellers trying to rank well.

Searching for products online has become a regular part of our daily lives. With just a few taps or clicks, we can conveniently browse and purchase items on our phones or laptops. But providing this seamless shopping experience requires immense technological innovation behind the scenes. At the core of online