For budding Internet entrepreneurs Andrew Holt and Rishi Khaitan, building a better mousetrap was the key component in their vision of the upstart comparison search engine Behind the sparse front page is a wealth of products, information and consumer recommendations on a wide array of consumer and business electronic goods. Searchers are offered a number of comparative tools to change and narrow results, ranging from general price and product-specifications, to much more specific details relevant to each product type.

Like many other IT engineers, Andrew and Rishi are electronics enthusiasts who know how to find product information quickly and can rap tech-specs off the tips of their tongues. They are therefore considered experts in all things electronic by their friends and families, an honor of sorts that can quickly become a major burden around Christmastime or when a product recommendation goes awry.

Andrew and Rishi saw a significant hole in a growing marketplace and decided to develop a search engine that provides “product recommendations in the same manner a highly knowledgeable friend might.” Faced with a hole in the market, they did what any talented risk-taking techies should do; they built their own solution. In the process, they developed an engine designed to consider a question based on how they themselves would work through a product recommendation. This month, they felt they had finally reached their goals of creating an easy to use product comparison engine which is also complex enough to offer excellent advice to almost any individual user.

As their thinking goes, they would first consider what other people had told them about a specific product. They would then likely recall and reread articles they had spotted that mentioned the product. The personal needs and preferences of the person asking for the recommendation would also be fuel for consideration.

The best way to describe the search tool is to invite readers on a product search tool. I am looking for a new laptop computer. Fortunately, this is one of the ten most searched for product types and has a handy icon representing its laptop category on the front page. I click on it and am taken to a page that is divided into three columns. The left hand column contains tools to narrow my search. The center column contains search results. The right hand column contains two ranking scores, rated on a scale of 1 – 10, generated by users and reviews found on the web.

Let’s start with the center column, which for my initial search displayed 9 immediate results with images to the left with product information in the middle and to the right. This column was divided into three rows. The first offered 20 results for Ultra-portable laptops, displaying the first three. The second row offered 71 results for mainstream or typical laptops, again displaying the first three. The third row offered 30 results for desktop replacement laptops with the top three results displayed.

The column to the right shows product ratings derived from direct-user reviews and from reviews published in 200-odd sources drawn from the tech-media. Scoring user and professional reviewer opinions on a scale from 1 – 10 might seem easy, if the reviewers wrote their reviews using a numeric system. Unfortunately for Holt and Khaitan, they don’t. That necessitated the creation of a complex algorithm referred to as TotalRank.

TotalRank finds and extracts keywords and phrases used to express an author’s opinion of specific products and their attributes. These phrases are quoted on product results pages. They are also assigned a value based on how the author describes a particular product or product attribute, the stated battery life of a particular laptop for example. Using a simple scale consisting of, “Very Negative, Negative, Neutral, Positive, and Very Positive”, a numeric value is assigned to that phrase in relation to the product. All ratings for all attributes of a particular product are then mixed, sorted, weighted and scored to produce the TotalRank score.

Search results are altered and ultimately narrowed using the features found on the left hand side of the screen. The first is the price range slider that allows the searcher to sort search results based on the cost of items. The second is a general attributes box that asks the searcher to specify product attributes that are of particular importance to them. For example, I am very concerned with how long the batteries on my laptop can operate between charges. I am also concerned with reliability and with ergonomics. By selecting the general attributes I am most interested in, my search is narrowed considerably.

DontBuyJunk takes the narrowing of search results much further than general attributes, allowing me the option of telling it exactly what I need in a laptop. Another feature allows me to choose results that based on: Screen size, resolution, aspect ratio, processor class, processor speed, installed memory, wireless attributes, stated battery life, h/d capacity, optical drive type, USB ports, peripheral connectors, OS, and the manufacturer. Surprisingly, colour and flavour weren’t options.

Just to remind folks, my birthday is coming up in a few weeks. By using, I have found the new laptop I truly need and have conveniently distributed the search results page the engine produced to family and friends. That page will be very helpful to them as it lists a great deal of product information, laid out using five easy to follow tabs.

The first tab shows general product information under four headings The Good, The Average, The Bad, and Not Sure. Each of these headings shows where specific attributes of the product might fall. For instance, while the laptop I found excels in battery life and reliability as noted under The Good heading but the gaming performance seems to fall under The Bad. The business performance is Average as is the audio quality. The second tab is labelled specs and offers highly detailed technical specifications. The third tab displays user reviews and the fourth displays web reviews. The fifth and final tab lists a number of places to purchase the product online. Shopping.Com currently feeds this information.

DontBuyJunk.Com is a better mousetrap. Having built what is arguably the most complex product comparison engine to date, Holt and Khaitan hope to see it adopted by electronics consumers who want a simple and quick solution for finding exactly the right products.