With the news that web behemoth Google has launched its Google TV service, the rise in popularity of online TV site Hulu (admit it…you watched the Betty White SNL episode didn’t you?) and recent figures which estimate that TV’s share of total viewing by consumers is 99% (that’s when you add TV viewing with watching video online and on mobile devices), it’s no wonder people are still obsessed with finding something good to watch.

As part of a feature that appeared in Multichannel News in May entitled, “What’s On?  TV Techs Solve Viewers’ Oldest Angst With Recommendations,” I was asked to join some of my peers from other firms looking to unravel the mystery of how consumers, with a seemingly unlimited choice of TV programming to watch, can still sit numbly upon their couch each night aimlessly clicking through the channels searching for something decent to watch.

The article in Multichannel News notes that the availability of seemingly endless programming library of choices is just the thing that has driven consumers to this state of TV ennui.  “The need for more personalized recommendations is evident, considering VOD libraries are already approaching 20,000 titles and could grow five times as large. Add to that the prospect of millions of Internet video clips accessible on TV, and it’s obvious subscribers need a new tool to find content,” writes Multichannel News’ Todd Spangler in the story.

Here at ChoiceStream, we’ve been working to solve this conundrum for some of the leading TV providers and we’ve met with tremendous success.  For example, we’re supporting Dish Network in its goal of making their service “stickier” by offering programming recommendations that are contextually aware and relevant, while explicitly removing the possibility a recommendation maybe inappropriate (watching G -rated content will bring G-rated recos, etc.) or just plain irrelevant.

For AT&T’s U-verse TV service, ChoiceStream recommends VOD “top picks” which are based on the subscriber’s past video-rental and TV viewing history.  The story notes that, “The telco’s app also provides a list of the top 10 on-demand titles U-verse TV subscribers are renting and the ability to rate a movie you have previously rented.  The individual subscriber’s ratings are which is averaged into other U-verse TV subscriber ratings and displayed next to the title in the on-demand recommendations list.”

What’s the biggest benefit to providing VOD recommendations and TV recommendations?  Quality programming recommendations increase customer satisfaction while decreasing churn (a key metric for TV services who want to keep customers longer).   Of course, there is the added benefit of increasing revenues by recommending relevant VOD titles that lead to subscribers renting even more VOD titles.

In fact, in ChoiceStream’s experience, an operator should expect both VOD revenue and usage to increase approximately 10% after deploying personalized recommendations.   Meanwhile, leveraging personalized offers and advertisements promoting TV, video and package upgrades are up to five times more effective than generic offers.

Simply put…if you’re a TV provider looking to provide a more engaging and relevant experience for your subscribers, there’s a better way than just giving them a remote and getting out of the way.  Bring a better level of service to the living room (or wherever they’re watching TV) and put personalized VOD and TV programming recommendations in front of your customers.

You – and your subscribers – will be glad you did.

Meet Paul Mahony, Director of Professional Services here at ChoiceStream.  A native of Tipperary, Ireland he is also a graduate of the University of Limerick.  Paul initially worked in Dublin for IBM as a program manager but wanderlust and a sense of adventure took hold and Paul decided to travel the world.

He came to the U.S. where he met his wife, settled down and worked in a series of customer-facing jobs for smaller technology companies. Paul was drawn to ChoiceStream nearly four years ago because he desired to work at a small technology company with leading-edge solutions where he could again interface and service customer needs.

What made the role at ChoiceStream even more intriguing was the fact he could really learn about client needs and work with engineering, product and account management staff to satisfy those needs. “It’s really about developing solutions that drive new business for customers and that directly impact their bottom-line. Seeing the results that our personalization solutions deliver is pretty cool,” says Paul.

Fun Fact(s):

• Growing up and while at University, Paul was an avid golfer, though he admits that “work and family commitments” leave him with less time to hit the links
• Instead, Paul does manage to find more time to satisfy his other passion on the weekend – gardening.

Mike noted that these failings in integrating and deploying personalization that works are, in effect, a “black hole” – an endless void that not only sucks up energy and resources but can even increase negative feelings among dissatisfied customers (who may be seeing recommendations that aren’t relevant) while also negatively impacting revenues.

In providing personalization solutions, as in anything in life, it’s the lessons learned from first-hand experience that are most important.  The advice is based on more than the 9-years of experience that ChoiceStream has in providing personalization solutions that work for a myriad of retail clients.

There are a number of key mistakes Mike referred to in the aforementioned article.

Among them are:

Beware of Jumping on the Bandwagon.
Many online retailers are making investments in personalizing their sites using mass appeal “cookie-cutter” solutions.  But, as with anything in life, you get what you pay for.  In this case, these “cookie-cutter” solutions may offer personalization at a discount but it’s usually a solution without any ability for customization.  This approach doesn’t allow the personalization solution to take into account a retailer’s unique catalogue, merchandising requirements and most importantly, customers.  That doesn’t sound like true personalization.

Avoid Making the Homepage Your Favorite Child.
Presenting personalized product recommendations on the home page can work.  However the homepage is just the tip of the iceberg.  More important are making sure your personalization vendor deploys recommendations where they can play a key role in up-selling and cross-selling on the pages that matter most: like product detail pages and product list pages.

Use What You Know About Your Consumer Behavior To Your Advantage.
Though the web provides a wealth of data, many retailers aren’t actively utilizing this data to push more relevant offers and promotions to drive more conversions and increased sales.  Effective personalization needs to utilize this data as well. Tracking what consumers search for, what pages they navigate to, which items they investigate further, what items they put in their shopping cart and most importantly what items they purchase are all key data points retailers (and personalization providers) can use to create more compelling up-sell and cross-sell recommendations.

To read about some of the other mistakes retailers make deploying poorly performing personalization on their sites, check out the complete article – “Avoiding the Black Holes of Personalization”  – today!

A graduate of Harvard University and native of Cambridge, Massachusetts (where ChoiceStream is located), Adam was drawn to ChoiceStream by the challenge of solving complex data analytics issues. Specifically, how to successfully use past purchase behavior, contextual behavior and catalog information with predictive analytics to present product and content recommendations that resonate for individual consumers.

Recently, Adam and his team worked on a challenge where a ChoiceStream client wanted to use geographic targeting to create personalized recommendations that would promote events where it makes sense.

What else is the team working on? “Right now, we’re looking at the affect on-site personalization can make in bringing users back to a site over a period of months. It’s our belief the value of personalization extends beyond the immediacy of increased customer spend as recommendations often positively increase dollars spent over a longer period of time,” says Adam.

Fun Fact(s):

• Adam is an accomplished pianist who has been playing and performing since he was 10 years old.
• In his spare time, Adam loves to read. His favorite authors include Modernists like James Joyce and Samuel Beckett.

These findings aren’t really surprising to us. Today’s consumers expect more from recommendations than they did even a year ago. They expect them to be accurate and on target, so when they’re not, shoppers notice.

The question is, then, what should retailers do about it?

Improving recommendation quality should be job 1 for every online retailer. Losing sales to poor quality recommendations is just unacceptable when you consider that by following some basic rules of merchandising, recommendations can be accurately tuned for each shopper.

Rule 1: Pay Attention to Context

If a customer walked in to a sporting goods store carrying a new, expensive tennis racquet, you wouldn’t you try to sell her another racquet, would you? No, you’d try to cross-sell her a similarly expensive bag to carry it in, or some fancy clothes to wear while playing.

So why is it, then, that when consumers shop online, retailers often completely ignore this basic rule of merchandising and make recommendations to shoppers that are completely out of context?

For example, online shoppers are bombarded with product recommendations that try to sell them more of what they already have in their carts. In a small percentage of cases (e.g., consumables like canned foods or paper products), it might make sense to try to increase order size by recommending more of what a consumer is already buying. But, for most online purchases, once a shopper has made a purchase decision — i.e., she put an item in her cart—product recommendations should no longer include ’similars’ or substitutes. Instead, they should immediately switch over to complements or cross-sells.

It sounds simple, but few recommendation providers take context into account when delivering recommendations, leading to consumer frustration with the recommendations they’re shown.

Rule 2: Learn from Past Shopping Activity

Good bricks-and-mortar retailers know their customers. They know who’s brand conscious and who’s not. Who only buys on sale and who doesn’t care about price and just wants the latest and greatest.

They know this because they know their customers past shopping behaviors and they take them into account when figuring out what merchandise to recommend.

Online retailers need to do the same thing. They need to ‘learn’ from their customers’ past shopping activity so that they can understand each shopper’s persistent behaviors and use that knowledge to recommend products for the next purchase(s).

For example, suppose you have a budget shopper who consistently buys lower-end or sale merchandise. But, in her current session, she’s looking at expensive, status-label products. A recommender that only looks at the current session data would label her a luxury shopper and recommend only high-end products to her. A recommender that also incorporates knowledge about this shopper from her previous sessions knows her better and might recognize this as a gift purchase or a splurge and provide a more balanced set of recommendations.

There are recommendation providers out there, like ChoiceStream, that follow these rules; but there are many more that don’t. When you evaluate recommendation vendors, be sure to ask about context and past purchase behavior. If a provider doesn’t factor these into their product selection process, you should probably move on and look elsewhere. If you don’t and you end up providing poor quality recommendations, your shoppers might just move on instead.

Schuman contends that we missed the point because social networking sites were never designed to be e-commerce sites. They’re places where friends discuss their lives, work, hobbies and, in the process, end up influencing each other’s shopping decisions that take place outside of the network. He claims that just because shoppers aren’t physically clicking ‘buy it’ from within a social network, retailers shouldn’t ignore social networks as a place to have a presence.

We actually couldn’t agree more that the interactions shoppers have with each other on social networks influence their shopping behavior and purchases. What the survey indicated is that retailers need to think long and hard about the kinds of investments they’re making in social network advertisements and product recommendations, specifically. The numbers showed that while some people do happen to make a purchase while engaging in social networks, most are not ready for retailers to push product recommendations at them.

That’s not to say a purchase isn’t influenced by the things they are seeing from friends, fan sites and brand engagement campaigns. It simply means they don’t want retailers bombarding their pages with links and ads, as is pointed out in the story. Thus, it remains our advice to retailers that they not invest in this type of direct-response marketing initiative right now, allowing consumers to engage with the brand on their own terms. For 2010, personalized recommendations and promotions are better suited where consumers are actually looking for them — online and mobile.

What are your thoughts? Would love to hear from retailers how they’re leveraging social networks. How is your social networking strategy playing out?

So, what does all that have to do with personalization and recommendations? A lot, actually.

We just released the results of the 2009 ChoiceStream Personalization Survey and one of the most interesting findings to come out of it was the fact that consumers want product recommendations on their smartphones to help them find products to buy. 65% of respondents said that they would buy more products on their devices if they got recommendations on them from retailers they trust.

Given the small screen size, it makes sense that shoppers don’t want to have to surf lots of pages to find merchandise. Now that the consumer demand is there, it’s up to retailers to improve the m-commerce experience and put relevant products and promotions at consumers’ fingertips — literally!

Shop.org 2009 proved that online retail has survived — and even thrived — the economic storm and is beginning to feel reinvigorated as the holiday shopping season approaches. One of the more compelling stats underscoring this sentiment is that Shop.org’s organizers confirmed registered attendees were up 10% year-over-year from 2008.

At ChoiceStream’s booth, we saw a steady stream of interested retailers seeking to learn more about how ChoiceStream RealRelevance® Recommendations and Advertising solutions are increasing average order size, conversions and revenues for leading retailers while creating a relevant experience for shoppers that builds loyalty over time.

One of the highlights of the week was a guest appearance by Zappos.com’s Director of User Experience Brian Kalma where he discussed how vital personalized product recommendations are for Zappos.
Brian noted that not only do personalized product recommendations create a better user experience but they also drive measurable lift in incremental sales. Brian pointed out that recommendations driven by ChoiceStream have helped Zappos see a “nearly 30% increase in pages viewed per visit, a 12% to 13% click-through rate on recommendations and nearly a 3.5% lift in sales.” And that’s with recommendations deployed on only 40% of the site for a mere four weeks!

It was clear retailers both large and small are committed to providing a more personalized experience for their shoppers in 2010. And, as the “largest and longest-standing of the ‘pure-play’ personalization engines,” (according to Forrester’s Sucharita Mulpuru) ChoiceStream is uniquely poised to help retailers succeed by delivering personalized product recommendations and advertising that ultimately increase revenues!

One final note — many retailers said personalization was on the roadmap for the future — but it’s not too late to deploy personalization to positively impact holiday sales this year! Contact us to find out how.

ChoiceStream’s marketing and advertising team celebrate with OverStock’s Rob Gallaugher (center) and Nick Taylor (right)

Brian Kalma of Zappos (in checked shirt) details the positive results from personalized product recommendations using ChgoiceStream RealRelevance

Another Lucky Winner at Shop.org with ChoiceStream’s Amy Vener

In-Booth Candid Photo (l to r) – Bryce Neal (ChoiceStream), Derek Mellencamp (Dell) and Bruno Sarda (Dell)

Some of the Zappos team savor their winnings at ChoiceStream’s booth during Shop.org

Zappos Brian Kalma discussing personalization with a representative from Gap Direct

And don’t miss our ChoiceStream Chip Giveaway! We’ll be giving away hundreds of cash prizes. No purchase necessary. ;-)

See you in Las Vegas. And remember…what happens in Vegas, appears on YouTube. So, be careful out there…

As a reader of ADOTAS, you’ve no doubt heard the recent buzz around performance display advertising.
A striking departure from classic ad campaigns measured via clicks and impressions, performance ad campaigns rely on metrics that really matter to retail advertisers, namely conversions and revenue. To boost those metrics, today’s retailers are applying recommendation and targeting technology to display ads. With the in-market relevance of search and the reach of display, this type of performance display advertising is quickly becoming the preferred way to spend ad dollars — and new ‘performance metrics’ the only way to truly measure ROI.

There have been several ADOTAS articles recently that brushed the subject of performance advertising (articles by Zephrin Lasker and Chris Neuner come to mind) but it’s time to go a little deeper into what actually makes this type of display ad perform better, how best to measure its effectiveness and why advertisers need to welcome new attribution models. The holiday shopping season is nearly upon us – there is no better time than the present to get up-to-speed and start testing to find what works for you.

Contrary to what some might say, better display ads are not all about size, better placement and clever campaigns. Grabbing attention is only half the battle. The other half – the half that drives sales—is taking those creative display ads and making them relevant to each consumer who views them. What good is a perfectly branded, perfectly placed, creative ad if it’s for a product the consumer doesn’t need or want?

Regardless of the negative attention on behavioral targeting, research shows that consumers do want personalized recommendations to help them with their purchase decisions. The best performance solutions on the market today are the ones that merge personalization technology with display ads. These solutions rely on actual shopping data from advertisers to create ads with immediate, in-market relevance for each individual shopper. As more shoppers go online to look for deals and to research their purchases, e-retailers (Overstock, Zappos) and multichannel retailers (JC Penney’s, Staples) will look to this breed of technology to drive conversions and boost their sales both online and off-line.

The case for performance ad technology is clear, but it’s not only about finding the right performance solution. There are two other key factors that advertisers need to embrace in order to truly make an impact on ROAS:

Advertisers must make better use of shopping data to learn from every interaction with consumers. To capitalize on performance technology, you need to really understand each shopper’s tastes and preferences by analyzing all of the behavioral and shopping data you have available. That includes purchase data (both online and in-store), loyalty card transactions, online click and browsing behavior, etc. You’re missing a huge opportunity if you’re not learning from every engagement a customer has on your site, in your store and with your brand. It’s that precious data that enables personalization and creates unique occasions to purchase for each shopper.

Advertisers must use more robust performance metrics and models of attribution. Advertisers that focus solely on traditional metrics like clicks and viewthroughs are missing the big part of the revenue picture. Those metrics do impact ROI; but there are also other, less direct, metrics that are just as important. While every campaign should stand on its own in terms of direct performance metrics, understanding the indirect impact of display advertising is critical to making the best investment decisions when allocating dollars.

Quantifying metrics such as an ad’s impact on search engine traffic, social media buzz and message boards are all important in valuing ads correctly. For example, according to a recent study by Forrester Research, almost as many Internet users respond to online display advertising by performing a search on a search engine (27%) as by clicking on the ad itself (31%). This finding speaks to the symbiotic relationship between the two channels, and the power of display advertising to boost search engine traffic. If marketers are going to invest in online display, they should consider the broader impact of their campaigns to help them track their full value.

Unfortunately, this type of comprehensive attribution tracking is not the norm for online display advertising. These metrics can be hard to measure, but they’re not impossible. Online advertisers need to understand the value of measuring immediate, ad-specific actions (e.g., clickthroughs) as well as in-direct behaviors (e.g., performing an ad-related search on a search engine or message board). This will help advertisers come up with a system that provides correct attribution to their web marketing initiatives across the board.

There have been a lot of changes this year in the industry – it’s great to see performance-based advertising help advertisers go beyond the click and start paying attention to what actually drives results. The next steps are to ensure that we use all the data available to us to put the right products in front of the right shoppers and to fine-tune revenue attribution so that it provides a more comprehensive view of the impact of display ads. Once we do that, we’ll all be seeing display advertising in a whole new light.