After attending the event for four years, I’ve had the opportunity to see first-hand how the market has shifted over time. The discussions at eTail West in the earlier years were primarily about how to manage, measure, and increase transactions. But most retailers have this figured out by now, so their focus has shifted to maximizing their revenues in new ways.

Naturally as the market has matured, retailers have grown to be more concerned with customer experience and service, so it’s no wonder that the three consistent themes at this year’s event were multi-channel customer experience, personalization, and recommendations. Online retailers are looking for new ways to increase their revenues and to achieve better personalization and customer targeting. They are also looking for new ways to maximize revenues by deploying the recommendations they already have in place in a much broader sense. Now that retailers have reaped the benefits of traditional product recommendations, they understand the capabilities these technologies have to tackle the newer issues, such as navigating social elements of their sites and the ongoing quest to improve search.

Just as the market has matured, so has Baynote. Each year at eTail, we’ve seen interest in our approach grow. Listening to the conversations of the attendees and the other speakers this past week, it was clear to me that Baynote’s time has come as retailers hone in on providing a superior customer experience and ultimately how to create happier, more loyal customers.

Perhaps the best evidence of this was a survey I conducted during my presentation. I asked the crowd: “Raise your hand if you think your best salesperson can outsell your best customer?” The result? Not a single person in the room raised their hands. When I asked another question: if the happiest customers are the most important to increasing their revenues; almost every single person in the room agreed. This demonstrates just how powerful peer-to-peer brand advocacy has become to retailers and the bottom line.

I left Palm Desert thinking about what an exciting time it is to be involved in the e-commerce industry, and how proud I am that Baynote’s customers are setting the standard with more sophisticated personalization approaches that are transforming the customer experience as well as their online businesses.

Coined by the National Retail Federation a few years ago, Cyber Monday offers retailers a way to organize sales and promotions in an online version of Black Friday, the Friday after Thanksgiving Day. The promising news for retailers is that Cyber Monday hasn’t typically been the largest online shopping day of the year, meaning this season’s peak is likely still yet to come.

I thought readers of this blog may also be interested in my guest article for BusinessWeek, where I share five rules that savvy online retailers already had in place heading into Cyber Monday. For those of you not yet incorporating these practices, fear not. They’re easy to implement and each can help your business year-round.

You see, the NASA.gov website uses Baynote to understand its visitors’ true intent and produce social search results as well as content and video recommendations that are most appropriate to each individual visitor. So every time NASA launches a manned mission or deploys a rover or slams something into the lunar surface at twice the speed of a bullet, a little bit of Baynote is out there, too.

This morning’s culmination of the LCROSS mission marked the second busiest day NASA’s website has ever weathered, with millions of concurrent users around the world watching live video and reading about the mission, and Baynote’s recommendations never missed a beat. So congratulations to NASA on another job well done, and thanks for taking us along for the ride.

The post, written by YouTube product manager Shiva Rajaraman, explains that the majority of YouTube users who rank videos give them a perfect 5-star ranking. He continues:

Seems like when it comes to ratings it’s pretty much all or nothing. Great videos prompt action; anything less prompts indifference. Thus, the ratings system is primarily being used as a seal of approval, not as an editorial indicator of what the community thinks about a video. Rating a video joins favoriting and sharing as a way to tell the world that this is something you love.

Rajarman goes on to solicit the community for feedback on how useful the current ranking system is and what can be done to improve upon it.

We’re really glad to see that YouTube is finally examining its rating system with an eye on delivering more value to its community and look forward to seeing how the system evolves from here. Ratings and user generated reviews, though often misleading, have become an expected part of the online experience and encourage deeper engagement. I don’t think anyone would take away points from YouTube on their ability to engage an incredibly large, diverse and influential community of users. However, YouTube’s review system- and others like it –  must also find ways to inform ratings based on valuable sentiment and implicit feedback gathered from the vast majority of their site visitors. Not the loud minority.

With a truly integrated approach to recommendations that blends both implicit and explicit feedback, companies can expect to improve engagement and overall user experience by directing site visitors to the best content based on their intent.  I talk a lot about this concept in my paper, entitled “7 Deadly Biases”.

In the end, explicit versus implicit user feedback shouldn’t be viewed as an either/or scenario. Please let us know your thoughts on the matter and share examples of sites that are doing it right.

While many marketers, website owners, and other business owners already know this, you’d be surprised how many of them use tools that rely on this overused and inaccurate metric. Many analytics, and even recommendation vendors, are relying on clicks as a KPI to either display to their customers or in the case of recommendations, to power their algorithms. The quality of recommendations or any kind of targeting based on user observation is no stronger than its ability to understand when and how a user has succeeded. Bounce rate, as Avinash points out, is just one of those metrics. At Baynote we track dozens of them, and clicks are by far the least utilized when validating success or failure.

Bottom line: When you are talking to analytics vendors, ad networks, or recommendations vendors ask them what KPIs their algorithms are relying on. If they say hits or clicks, they are idiots by Avinash’s definition, and he’s a smart guy.