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Peter Yared is the CTO/CIO of CBS Interactive, a top ten Internet destination, and was previously the founder and CEO of four enterprise infrastructure companies that were acquired by Sun, VMware, Webtrends and TigerLogic. Peter's software has powered brands from Fidelity to Home Depot to Lady Gaga. At Sun, Peter was the CTO of the Application Server Division and the CTO of the Liberty federated identity consortium. Peter is the inventor of several patents on core Internet infrastructure including federated single sign on and dynamic data requests. Peter began programming games and utilities at age 10, and started his career developing systems for government agencies. Peter regularly writes about technology trends and has written for CNET, the Wall Street Journal, BusinessWeek, AdWeek, VentureBeat and TechCrunch.

Many thanks to Bob Pulgino, Dave Prue, Steve Zocchi and Jean-Louis Gassée for mentoring me over the years.

Wednesday, March 30, 2011

Google: +1 on Search Links, -1 on Ad Clicks


This post was also published in VentureBeat.


Google has finally unveiled its +1 social initiative, largely aimed at stemming Facebook’s ability to learn what links are relevant to others in a social graph. The Google +1 implementation, where people can recommend individual items within search results, is definitely a step in the right direction. However, it could also hurt Google’s revenue stream — I predict that adding a +1 option to keyword ads will have a negative effect on clickthrough rates.

Google has been gradually embedding interactivity in search results, lately even asking directly in search results if a particular Twitter handle is yours. The new +1 feature harkens back to a 2008 Google experiment that mimicked Digg’s interface and let users move search results up and down, and even comment on them.



This new feature where users can directly like particular search result links definitely will help Google better rank search results by involving crowdsourced humans instead of algorithmic computing, which have been increasingly gamed by search marketers.

However, Google +1 seriously begs the question as to why Google isn’t simply ranking results based on what people are clicking on. If a user clicks on one link and doesn’t come back to click on other results, that indicates they have found what they are looking for. A future Google +1 will likely let you rank any page on the Web using the Chrome browser whether or not it has a “Google +1” button on it, and therefore present a serious threat to the newly emergent StumpleUpon.

What Google doesn’t appear to have thought through seriously is the +1 integration with Google AdWords. It is a cardinal rule of advertising that you present the user with one call to action. Clicking on a +1 next to an AdWords ad makes no sense at all – it is already hard enough to get people to click on an ad without adding confusing paraphernalia around the unit.

A store selling futons in San Francisco that pays for a targeted ad to people in the bay area searching for futons wants people to click on the ad, not + 1 next to the ad. The Google + 1 AdWords implementation is an obstacle to conversions with very little upside. Google Instant is already impacting click through rates by automatically populating search results as users type, and Google + 1 is going to make the problem worse.

Google is clearly attempting to mimic the popular Facebook ad feature where people “Like” a Facebook page. However, in Facebook, Liking a page is essentially opting in for newsfeed updates — the Facebook equivalent of a mailing list opt-in — which is why marketers are willing to pay for ads that incent users to Like their Facebook page. Google +1 offers no such benefit. In addition, while users are happy to “Like” Disneyworld, chances are they are not going to like “25 percent on futons today only!”

Google +1 is a great step forward for Google as it is finally admitting that perhaps humans can be smarter than machines when it comes to detecting relevant content. But Google has already nailed how people like ads: By clicking on them.

Wednesday, March 23, 2011

How Friend Clusters Could Make Facebook Intimate Again


This post was also published in VentureBeat.


For a so-called social utility, Facebook has been getting more and more useless.

At first, Facebook friend overload was an early-adopter problem for overnetworked Silicon Valley insiders. But now, friend overload is hitting the mainstream consciousness. Many people who have been using Facebook for a few years find themselves inundated with friend requests by everyone from elementary school classmates to work colleagues. The resulting mess of casual acquaintances on Facebook has quickly overwhelmed newsfeeds with uninteresting minutiae and people you really don’t care to see.

In response, there has been a lot of recent activity by startups exploring concepts related to small groups of friends. Foursquare CEO Dennis Crowley has long talked about how his location-based service has a more “real” social graph — people with whom you’re willing to share your location. Path is run by Dave Morin, a well-known ex-Facebook employee, and is delivering a mobile photo sharing network for your 50 closest pals. Newly popular startups like GroupIn are bringing group texting back into vogue. Even Mark Zuckerberg has come to the conclusion that “most people don’t want to create lists of things, but the act of adding friends is a very nice feeling. No doubt it would be better if everyone had these friend groups [automatically] created.”

The next attempt, Facebook Groups was a resounding disaster. Since anyone could add friends to a group, they quickly grew into large, amorphous collections of people. Your entire high school class may now be a group, but not your real friends.



So here’s the fix, according to my sources: Facebook engineers, longtime fans of graph theory, are starting to derive “friend clusters,” or tight interconnections amongst a group of friends. For example, Facebook knows when a substantial number of coworkers have friended each other, and even knows that there are more people on the periphery that are close to parts of the company. Facebook has been incrementally adding this friend clusters feature in subtle ways. When you pull up a photo album from a friend, in the “people you may know” section to the right will often recommend people that you probably know in common with that person. This is because Facebook knows not just that you have friend in common with the person you are looking at, but who else has a lot of commonality but is not currently in your friend list.

It is likely that Facebook will soon introduce automated lists, and present user with lists of people and ask them questions like “Are these your coworkers”? By adding heuristics like how often users message, comment, and tag each other in photos, it will figure out who are tight clusters of friends. Even further, as evidenced by Facebook’s acquisition of the group messaging service Beluga, by watching how quickly people respond to each other — a feature I like to call “response velocity” — Facebook will start to figure out who your real friends are.

There are people you answer the phone for, write back to immediately and comment and like their posts; and there are people you don’t do that for. Facebook is uniquely positioned to learn which is which — an advantage Google and other rivals can’t match.

Now that’s a real social utility.

Sunday, March 20, 2011

Why Sentiment Analysis is the Future of Ad Optimization


This post was also published in VentureBeat.


Sentiment analysis is a hot new trend in social media, with the promise of helping brands understand what consumers are thinking and saying about their products. Products including early contender Radian 6, newcomers such as BuzzLogic, and my own company’s Webtrends Social Measurement product are becoming pervasive in marketing organizations. But while consumer sentiment is important, what’s much more important is revenue.

When revenue is down 10%, “but people like us!” is not an acceptable response from the head of marketing. Sentiment analysis isn’t a solution unto itself, but it can be highly useful as a realtime feedback loop for advertising effectiveness and may soon be able to predict advertising results.

In the Mad Men-era heyday of mass marketing, marketing spend was impossible to quantify. TV, magazine, radio and billboard ads were purchased, and it was very difficult if not impossible to track exactly the return on investment of various slices of the marketing spend. Marketers would focus on issues like branding, messages and color schemes, with virtually no feedback loop other than the occasional focus group.



With the advent of digital marketing and online commerce, marketing spend and effectiveness is now tracked at the most minute level. How many ads are clicked on, how they convert, what is working and what is not is tracked at every level and segment. Even traditional legacy advertising is voraciously tracked, from Nielsen tracking how many consumers see a TV spot to QR codes on billboards acting as an effective realworld clickthrough.

In stark contrast to marketing of the past, today’s marketers are measured by how much revenue they bring in per dollar spent. What “sentiment analysis” does is give those marketers an alternative way to measure their effectiveness — tracking how customers feel about and how much they are talking about a brand. All that effort on branding, messages, and color schemes can finally be validated!

However, the number of positive mentions you generate is simply a step towards revenue. If more people are talking about Pepsi than Coke, but more people are buying Coke than Pepsi, there is something seriously wrong in the conversion funnel towards a purchase. To make sure you’re turning positive sentiment into revenue, you need to make sure you’re making proper use of the analysis you do.

For bread and butter products like Wheaties and cable TV, sentiment analysis is more customer service — dealing with customer complaints that occur in social media and routing the complaints to the particular department that can handle it, before the complaints spread. Comcast, a company that many folks love to hate, has been particularly pro-active at responding to customers on Twitter, and even Salesforce is jumping into the game with its Service Force social CRM offering.

For product and company launches and other new offerings, sentiment analysis can help you track in near realtime how a new product or piece of content is spreading and decide what opinions to re-promote to grease the wheels of message spread. Products like Klout and PeerIndex help further by quantifying the viral influence of people tweeting about your product, so you can prioritize retweets of positive mentions and quickly attempt to neutralize negative sentiment.

However, the more important story here goes beyond what people are saying about a single brand or product launch. For the first time in history, we can look back in time and see how word of mouth and opinion about a product spreads, turns negative, or simply vanishes. Tying historical shifts in sentiment to external factors such as ad campaigns will show exactly what has worked, what hasn’t worked, and what can inflect a campaign towards viral success.

Much like Wall Street tests its predictive algorithms by analyzing past stock market trends and the impact of externals factors such as news stories and government reports, companies like Topsy and Infochimps that store tweets and connections between tweets are sitting on a ton of data that can analyze past sentiment in order to predict future sentiment.

In the Mad Men era of marketing, marketers had no idea how their campaigns were doing. Nowadays, marketers can track how campaigns are performing in real time and get an idea of what people are saying about their brand. And soon, by analyzing past sentiment, marketers will be able to predict exactly how a campaign will perform, and in realtime place ad units in to tilt campaigns towards virality and conversion. Knowing that you should buy some Facebook ads targeted at a particular demographic when a multichannel campaign has had a certain amount of success on YouTube is invaluable. After all, there’s no better sentiment than having a customer’s money in your bank account.

Tuesday, March 01, 2011

FarmVille 2? Why Zynga Needs to Start Making Sequels, Fast


This post was also published in VentureBeat.


Do your best impersonation of a movie-trailer voice-over artist and say it: “FarmVille 2. This time, it’s agricultural.”

That’s right: Like the Hollywood studios of old, like the stodgy makers of console games before it, Zynga, the San Francisco-based publisher of social games like CityVille, Mafia Wars, FrontierVille, and FarmVille, is inevitably going to get into the sequel business.



Zynga has been a phenomenal success story with continuing growth, incredible profits, and big investments from major players. If things continue, it will soon be the most valuable gaming company — even though it’s still privately held and rivals like Electronic Arts and Activision Blizzard are publicly traded. Despite the carping from some corners, Zynga’s success is well deserved, as it figured out the twin precepts of the new era of casual gaming: incremental gameplay through virtual-good acquisitions and asynchronous cooperative gameplay with friends.

Zynga has added phenomenal gaming talent to its ranks, and although it had some missteps such as Treasure Isle, it evolved the gameplay from FarmVille, its first breakout hit, into CityVille, an even more successful game in terms of user ramp and monthly active users. CityVille reached 100 million users in just 43 days last month. However, CityVille is now quickly peaking after its stellar initial growth, and lost almost 5 million monthly active users in February alone, just three months after launch. CityVille is still increasing daily active users, but the writing is on the wall: CityVille will follow FarmVille’s decline, only faster.



At some point, each simulation game hits an end. A farm or city becomes too large to manage. Zynga has stayed ahead of this problem by continually feeding new simulation games to the market, but we are very close to the point where moving on to yet another simulation becomes tiresome, just as the wave of simulation games in the 1990s ranging from roller coasters to railways to the Sims eventually faded away.

Entertainment is entertainment. Even Hollywood movies go through waves like this. In the late 1980s and early 1990s there was a wave of movies glamorizing competitive professions. What started out as great movies like Chariots of Fire that featured runners moved on to average movies like QuickSilver that featured bike messengers, and then quickly degraded into Over the Top, with Sylvester Stallone starring as a professional arm wrestler. After shaking itself off, Hollywood went back to the staples with movies featuring cops, firemen and lawyers.

So what should Zynga do now? It has completely mastered social gameplay and the launch of new social games. Its titles, even after declining, dominate the social gaming scene, with four of its titles totaling up to 202 million monthly users. However, as the fast cycle on CityVille from launch to massive growth to decline, all within 3 months shows, perhaps another simulation game will not maintain sufficient momentum to sustain Zynga’s growth.

As I pointed out last May, the answer is gaming franchises. It is useful to see how previous generations of entertainment companies handled this problem for a taste of the future. Rather than inventing yet another first person shooter, Activision Blizzard revamps an existing franchise, Call of Duty: Modern Warfare 2, with new graphics and gameplay, and hits $1 billion in sales within three months.

Zynga is sitting on multiple gaming franchises that are seriously due for graphics and gaming refreshes: Mafia Wars, FarmVille, and Texas Hold ‘Em Poker. Each of these games has an audience that has played it before and would be very willing to check out a new version. Just when you thought FarmVIlle would go away, here comes FarmVille 2!