About ChoiceBot Technology
A fundamentally new, patented approach...
As you probably know, thousands of product finders, product selectors, wizards, decision trees, and the like have been developed over the past 40+ years. Probably more like millions, actually. Problem is, they don't work very well.
If they did work well, shoppers wouldn't be spending hours on e-commerce sites, pouring over long lists of "matches", trying to juggle ridiculous amounts of product information in their head (or in spreadsheets), and generally feeling that their final purchase decisions are a little more random than they'd like them to be.
ChoiceBot's fundamentally different, recently-patented approach enables users to effortlessly zero in on their truly best choice from within a database in less than two minutes...
Why ChoiceBot works, and other tools don't
Apart from ChoiceBot, virtually all product selector tools on e-commerce sites suffer from two fundamental problems:
- They aren't able to understand what your real buying criteria actually are.
- They don't interpret your buying criteria properly when sifting through a database of products.
The net result is that the products that the product selector recommends usually aren't your truly best choices, and your truly best choices are routinely filtered out altogether. It's actually fairly easy to understand how and why this happens… Consider the following scenario:
You're in an electronics store shopping for digital cameras. You ask a salesperson for help in choosing which model is right for you, and she asks you how you feel about price. Maybe you've done a bit of research already, so you answer something like this:
"I'm expecting to pay about $400 for a digital camera that meets my needs.
I might go up to $500 if I think that its other features are really fantastic, but $600 is out of the question.
$300 would be a good deal (I might be willing to put up with some minor weaknesses for that price), and $200 would be an amazing deal."
No problem -the salesperson understands exactly what you mean, asks you about some other features, and recommends an appropriate choice.
Now, let's say you're trying to make the same digital camera decision on a shopping website. You click on the site's product selector tool, and then on price. Using the site's tool, the best you can do to explain how you feel about price is usually something like this:
When you click OK, the shopping website understands your criteria for price to be as follows:
"I feel exactly the same about any price from $200 to $600 ($209… $389… $499… makes no difference to me…).
$199 or less is totally unacceptable (apparently, I don't like surprisingly low prices).
$600 or more is totally unacceptable (but $599.99 would be just fine)."
Obviously, this is NOT how you actually felt about price. In fact, these aren't criteria that any well-adjusted human being would ever have for price. The underlying problem here is that this is the way thatcomputers think about features, not people.
Because the product selector doesn't have a good understanding of how you really felt about price (or any other feature), it almost certainly won't recommend choices that reflect what you really wanted. Worse yet, it will probably also filter out choices that you would consider to be excellent (e.g., a camera with a good feature set on mega-sale for $195).
In ChoiceBot, however,you can enter your criteria in the above example scenario with perfect accuracy:
In fact, you can enter virtually any criteria that a human being could possibly have for any feature into ChoiceBot, with perfect accuracy. Just a few examples for a feature such as "price"…
"A price of $200 would almost be reason enough for me to choose a digital camera, but I'll go up to $400 if I really have to.":
"I actually prefer to pay a bit more, since this camera is a gift.":
"$600 would be a bit pricey, since I think I should be paying about $400. Anything less really doesn't change my decision, though.":
Because ChoiceBot is able to understand how you REALLY feel about the various decision factors that you care about, it can trade off the strengths and weaknesses of each choice (according to what you consider to be strengths and weaknesses), and identify the choice that represents the single best overall combination of features. Basically, it does the same thing that you do when trading off features in your head when making such decisions, but it does it on modern servers with gigabytes memory.
This means that ChoiceBot can trade off every single strength and weakness of dozens (or even tens of thousands) of choices, and recommend the one that represents your truly best choice, based on all available information, and a proper understanding of your real buying criteria -regardless of how many choices there are.
Additional information about ChoiceBot technology
For those interested in more detailed, "under the hood" information about ChoiceBot technology and the psychology behind it…
Why 99% of product selection tools filter out your truly best choices
A one-pager that explains how and why conventional product selectors almost never point shoppers to their truly best choices.
TEDx Ottawa talk by ChoiceBot founder Nick Desbarats (12-minute video)
A live presentation about the philosophy and psychology behind ChoiceBot.
8 misconceptions about ChoiceBot
Some assumptions that people sometimes make about how ChoiceBot works.