Earlier this week one of Belkin’s employees has been caught manufacturing product reviews on Amazon.com(In fact, he paid for them). Many customers rely on these reviews to make purchase decisions, but as stated in Scott Brave’s Seven Deadly Biases article posted below, these reviews are frequently a subject of gaming.

Gaming Bias

Another type of reviewer is someone who is “gaming” the system. Sometimes such gaming is malicious, but often it’s altruistic. While writing this article I went onto Amazon (Nasdaq: AMZN) to look at the reviews of a book I co-authored called Wired for Speech. The first one was very positive; perhaps someone my coauthor knows. But I have no doubts about the second 5-star review, titled “Amazing Insight.” To my surprise, it was from my dad! Enough said.

Gaming such as this is actually the rule, rather than the exception on Amazon and other media sites where products have authors or artists and personal connections abound. I admit to having given 5 stars to articles on my company … heck, if I can do it for this one, I will. Go ahead, try it out, give this five stars if you can!

For more of this whitepaper on The Seven Deadly Consumer Biases click here.

The irony is that the guy used Amazon’s Mechanical Turk to game Amazon.com. Here’s a link to the full article.

I read a great primer on Social Search yesterday on the Rise to the Top Blog. While Social Search is often poised as a replacement of keyword based search, we prefer to take a less cannibalistic approach and position Baynote Social Search as a compliment to traditional keyword search as proven with our recent partnership with Google Search Appliance..

The blog post correctly identifies two types of Social Search:
1. Explicit-based – Solutions where search results are powered by “simple [influencers like] shared bookmarks or tagging of content with descriptive labels.”
2. Implicit-based – A solution that is powered by the uncovering social intelligence with complex computer algorithms.

Baynote Social Search is closely aligned to implicit-based Social Search description given, as we do not utilize explicit information like bookmarking or tagging to derive our search results. And according to the post this turns out to be the differentiator that immunizes us from the pitfalls of social search mentioned:

Social Search Cons

Despite the obvious benefits social search has some glaring defects too. As said earlier social search hinges heavily on human judgment. But the web today is growing at a pace which humans simply cannot match and this means there will be a lot of content that would remain unnoticed and hidden from the user. Also the tagging method through which the search works is not the ideal way of organizing web data. There is also the risk of spam because users have the freedom to directly add results to a social search engine which can be misused. We all know the way some SEO’s behave!

However, Baynote Social Search does offer the same benefits that are mentioned by the author:

Social Search Pros

Social search engines have potential benefits deriving from the human input qualities of social search. Some of these include:

• Relatively free from link spam as there is less reliance on link structure of webpages
• More relevant search results as each result has been selected by users
• The user gets more current results
• The user gets his precise perspective reflected in the results
• The human judgment that social search uses is more accurate than computer’s ability to analyze a webpage

It was great to see Baynote standing out as the only company mentioned that is both bringing social search to websites rather than just a general web search engine and avoiding the negative pitfalls of explicit-based social search.

For any additional information on the Baynote Social Search Methodologies, check out our whitepaper “In Search for the Human Element.”

Product reviews have been around for a while and are likely going to stay around. However, its important to understand it’s place and where it can go wrong. Baynote CTO Scott Brave, wrote up a whitepaper on the seven deadly biases that detract from the effectiveness of user generated product review and rating systems. To test this hypothesis, I decided to write up a survey to see which biases impact the reviews and ratings given by our readers. Please take a minute to take the survey, it’s only 7 brief questions. Thanks!

Click Here to take survey!

A good buddy of mine gave me a iTunes gift card for Christmas, and with my upcoming trip back to my hometown for Christmas I decided to pick up a few movies for the trip. My first choice was “Death Race.” I pondered seeing it in the theaters, but decided to wait till it came out on DVD/iTunes. I’m a car nut so it was an easy choice. Then I looked to the music recommendations at iTunes which are driven by other users that purchase for other movies similar to Death Race. As shown by the screen shot above I didn’t get the results I was hoping for… I’m open to suggestions for a list of shared qualities between “Death Race” and “The House Bunny” because I couldn’t find any.

I’m not exactly sure went wrong here, but there are a few problems with recommendations driven by previous user purchases that are likely culprits in this disaster. Often multiple users on the same account that purchase different products. This creates a pretty useless source for data. Here is a link to the full image.

ReadWriteWeb just posted an in depth article stating that the contextual web is the next stage in the development of the web. The article states that technologies like open API’s and web services like those offered by Baynote’s contextual targeting platform have paved the way for a more personal and contextual user experience. While many of these new products designed to target the user’s context are being guided by similar methodologies, the data they use to drive relevant content is often quite rudimentary.

Given the state of the economy, this shift to the contextual web makes perfect sense. The last few years have been about finding new ways to spend your money to drive more people to your website like determining the best viral marketing techniques for getting 5 million unique users per month. This next step is constructing a more efficient web. A web where websites need less visitors to produce the same number of conversions, and to use those conversions to attract new visitors within the same context.

Another sketch: what ordering breakfast might be like if your waiter only listened to the words you were saying, instead of the intent behind the words. Of course, this would never happen in real life, but it happens with website search all the time. If only there was an intent-aware search system…

Check out our two minute trailer from last week’s “Mob Commerce” webcast featuring Forrester Analyst Sucharita Mulpuru.

In this webcast, Sucharita ties the Forrester Consumer Forum’s uber-theme of the universal needs of consumers (Connection, Uniqueness, Comfort and Variety) to what we do at Baynote.  She made us realize that product recommendations can tap into all four needs.  Sometimes recommendations provide an online shopper the reassurance that a particular product is “mom-tested” or “peer-validated”, meeting our need for connection and comfort.   In other contexts,  recommendations might allow someone to explore their need for variety and uniqueness by exposing long-tail niches like “third-person shooter” games.

For another angle on how human needs and desires affect how and why we buy, you might want to check out Martin Lindstrom’s recent book buy.ology -truth and lies abut why we buy.  Of particular interest and the direct tie to the Forrester material and our webcast is Chapter 3 I’ll Have What She’s Having — Mirror Neurons at Work.  It talks about how our need for connection is wired into our brain structure.  Mirror neurons drive us to imitate and, interestingly, work in conjunction with dopamine to make that imitation feel good.  It’s no wonder then that people who use recommendations buy more and feel good doing it.

Another interesting point of the book is the difference between what people say they want to buy, as uncovered through market research, surveys, or focus groups and what they actually buy.

Apple’s MacWorld Expo has become wildly famous with the technology community worldwide. Each year Steve Jobs gets on the podium and delivers a keynote that introduces another innovative product to his ever growing customer base. Today Apple’s website announced that this upcoming January will be the final MacWorld. What’s their reason? Their website is just that powerful.

Websites are now the primary way to get in touch with your customers, at least thats what Apple says and I agree. I’m not declaring the death of trade shows as a way to reach customers, but I am marking today on the calendar as the day where one of the biggest marketing machines in the world declared just that. This is a powerful message that will be heard around the world. Apple is usually the company that epitomizes a customer-centric company. Their company ideologies and methodologies have created arguably the most loyal and passionate customer base on earth.

That said, ensuring that your website users have the “Apple customer experience” should be a high priority for a company’s web strategy team. Enhancing the user experience means something different to all different types of businesses. A few months back I wrote up a post on just that. Bottom line, greet your customers with relevant information immediately and stay in touch with them on their terms(no irrelevant email blasts).

A new post on InternetNews.com reveals the findings of a new report released by Verizon advising companies on technologies to leverage to cut cost for surviving in the 2009 economy.

Software-as-a-service (SaaS) is one of the technologies the company [Verizon] picked. Many businesses are turning to the category of product to cut costs, avoid the expenses of installing and maintaining on-site software.

Check out the latest Baynote Mob Commerce webinar on how eCommerce companies can reduce costs and increase revenues with the Baynote SaaS platform.

Amazon’s recommendations frequently make me giggle.  I love to demo my “personal recommendations” at tradeshows to illustrate the point that we aren’t what we were yesterday.  We say this in all our presentations, we talk about the importance of context but sometimes a good example is worth a thousand words.

When I was pregnant,  Amazon kept recommending me books on exotic locations my husband and I had planned to travel like Cambodia or Patagonia.  Oh cruel Amazon and you won’t even fetch me ice cream!

I haven’t done a lot of shopping this year on Amazon.  If I had it would start showing me crazy recommendations based on some esoteric book I bought my physicist stepfather.  That was his wierd niche, not mine, not mine!  Let it go!

So this morning, I log on and what do I see but an Amazon recommendation for a book on losing weight while breastfeeding.  Not only is my youngest now a year and a half and I am waaaay past that phase but it seems, again, eerily cruel that Amazon finds a way to remind me that during the holidays I am eating more than I burn.  Now that’s just cruel.