A new product-recommendation tool called ChoiceBot personalizes the shopping experience for your customers by offering an interactive way for them to narrow their choices down based on individual preferences, which CEO and Founder Nick Desbarats said will lead to more sales.
ChoiceBot can be integrated into a Web store in much the same way as you employ a widget or YouTube video, by cutting and pasting a snippet of code on to the pages where you want the tool to appear. Pricing begins at $99 a month.
Online Shopping Option Paralysis
Though the product just launched, Desbarats founded the company a few years ago, based on his own experience with online shopping, which he said was overwhelming in terms of product information and recommendations.
To help shoppers deal with the vast array of choices available to them within just about any product category, e-commerce companies and search companies have developed hundreds of different types of product finders and product selection tools over the past decade, and almost every modern shopping site features several such tools already, said Desbarats.
But they're not working, said Desbarats. If they worked, he said shoppers wouldn't still be spending hours studying long lists of results, and "agonizing over purchase decisions, sometimes for days." He says research shows that on average, shoppers still leave and return to a shopping site seven times before making a purchase — even if the shopping site has tools that are supposed to help them make purchase decisions quickly and easily.
"There is product information overload, so the average shopper has trouble making a decision when faced with long lists of recommendations," he said. "So what happens is a lot of times they leave because they can't make a decision, so sales are lost because there's just too many choices being recommended."
He went on to say that before ChoiceBot, this scenario left online shoppers with two choices: either spend days sifting through product recommendations based on "arbitrary filters" such as "best selling," or "price," or simply just pick one that looks like a good deal on impulse.
Why ChoiceBot is Better
To address the problem, Desbarats created ChoiceBot, which tells shoppers why a product is the best choice by allowing customers to rate different attributes based on their preference.
Specifically, Desbarats said the key differentiator of ChoiceBot is that it enables consumers to express how happy or unhappy specific product features would make them (rather than simply what their minimum feature requirements are), using ChoiceBot's provisionally patented product search interface. The company's ChoiceBot Ranking Engine then ranks products by how well they met the consumer's overall needs, all things considered — including price. Regardless of how many search results were returned, the consumer need only focus on the top-ranked three or four products, knowing that they won't find any better choices further down the list.
The technology is based on the company's Tradeoff Analysis Engine, which Desbarats said works more the way a customer's mind works when he or she is trying to settle on the best choice based on multiple personal criteria, from among an array of many choices (such as an online product catalog). Conventional product selection engines, on the other hand, are based on the "black and white" thinking that database queries use, wherein a feature is either absolutely required by the user, or absolutely not required, with no "shades of gray" in between.
The problem, however, is that shoppers aren't databases, said Desbarats. "They rarely have such binary, extreme feelings about features. For a feature such as brand, for example, they may prefer some brands over others, have a small problem with some brands and find a few others totally unacceptable. The 'you must either absolutely require each brand or absolutely not require it' model isn't the way any human being actually thinks about brand, or any other feature for that matter," said Desbarats.
Forcing shoppers to try to shoehorn their buying criteria into the binary, "black or white" paradigm of database queries explains in part why shoppers often don't trust the results returned, get zero results without knowing why, or 73 results, 68 of which aren't truly viable purchase choices for one reason or another, said the CEO.
As shoppers enter their buying criteria into ChoiceBot, ChoiceBot TAE builds a simulation of their unique decision-making processes, and runs each product through the simulation to accurately determine how much the shopper will actually like or not like it, based on all of its features. By re-running all products through the simulation every time the shopper enters new criteria, the product that the shopper will truly like the most, all things considered, quickly rises to the top of the rankings.
Because it runs on servers with gigabytes of memory, ChoiceBot can simultaneously trade off every feature of every product in an entire catalog against every other feature of every other product, according to the company.
(Continue to Page 2 for Details on Setting Up, How Customers Use It)
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