Tag: Google Adsense

  • Reading beyond the obvious

    As a regular user of Google Reader, I was happy to see that a couple of weeks back, Google deemed it important enough to carry out a few changes – a ‘like’ button, the ability to follow specific people (using Reader Search), and friend groups (with customisation options of who sees what content). The public nature of the ‘Like’ button meant that sharing on reader got a lot more social, though it had its share of detractors too.  Many complained about not wanting to see “likes from the unwashed masses”, Google corrected it by adding an option in the Settings, so that if you so desired, you could only see the ‘Likes’ by people you followed.

    As a regular user, I’d say that people who give only partial feeds stand to lose out a bit on the ‘Like’ part. It would also be great if the time lag between publishing and the post appearing on Reader could be reduced. As a publisher, I wish Google would tie these social features in Reader with Google Analytics, so that I can know who shared/liked my posts. One way to know the number of ‘like’ is to subscribe to your own blog, but I’m sure that Google can make it easier if they want. Then maybe a plugin that can show these details on my post (at the site). Much like the Tweetmeme plugin I have installed on my other blog.  Speaking of Tweetmeme, according to Venture Beat, the button is now shown more than 50 million times a day across the web. It has its share of competitors, and is even threatening to sue one.

    That number gives a rough idea of why Google want a piece of the sharing pie. In fact, this chart, created by AddtoAny (the same guys who gave us that awesome widget at the bottom of my posts) shows how sharing happens on the web. Facebook leads, followed by email and Twitter. Google, though dominant in search, would be looking closely at specific competition – the Yahoo-MS deal and how Bing’s interesting games shape up. But more importantly, it also has to keep an eye on how generic search and sharing (social) are changing and shaping each others’ future. Twitter just got itself a new homepage, and ““Share and discover what’s happening right now, anywhere in the world”  clearly shows the intent. I thought it even answered, to a certain extent, the oft heard question – “But what do i do on Twitter”. Call it discovery/recommendation/trend, but it is just a different perspective on search. And its not just Twitter, Friendfeed recently added a feature – ‘recommend friends’. No, silly, not the Orkut/LinkedIn type, if you feel your subscriber would also like the feed of someone you subscribe to, you can share it easily. Though its nothing radical, its helpful for new folk.

    The Nielsen Global Online Consumer Survey shows recommendations (from known people) as the most trusted source of advertising, at 90% and consumer opinions posted online at 70% next. Among Indian audience, recommendations top, but editorial is placed second. A post on Six Pixels of Separation blog talks about how the next ‘Google’ will be a referral engine, which ranks website not basis text optimisation, but basis what people have said and done there, and how the information there has been used by people. But there are challenges there too as such a system needs to incorporate relevance, immediacy, trustworthiness and have an interface that will display it in the most intuitive, easy manner possible. This post on RWW discusses the concept of Social Relevancy Rank, with five layers, where search results on streams (like Twitter, which already have real time) will be arranged basis relevance to your social graph. Friendfeed does this and provides more options in Advanced Search. The post also suggests ‘friends of friends’ as the next layer of results, and a concept of ‘taste neighbours’ (a mining of ‘people who liked this also liked’) after that. The last two layers are made of influencers and the crowd aggregate. In fact, I thought, maybe a possible visualisation would be to actually have all five layers arranged vertically side-by-side and a thumbs up/down button by the side of each search result, so that each user can contribute to filtering. Is this a perfect method? No, but then neither is Google’s Page Rank, as the author says. Which perhaps is why Google, while it is master of the algorithmic search, needs to experiment with Reader and see if it can create a social layer on top of its Page Rank search system. A new system that also incorporates the data from likes and shares beyond the optimised keywords, and is able to operate in real time too. Possible? That would be fun, and would even take Ad Sense to a whole new level. 🙂

    So what does this mean for brand and marketing? Beyond mastering the algorithm, optimising all the queries, mining all the data and connecting it, how does differentiation happen, other than the obvious product possibilities? This very interesting article (via @vijaysankaran) discusses the battle between art and algorithm. Amidst the quest for perfect targeting, and the smoothing out of our search experience, we might be losing out on serendipity. The  author goes on to say that in this ‘end of surprise’ is the opportunity for marketing – to deliver revelation along with relevance. The perfect  of left brain analytics and right brained creativity and emotions, which seemed to have been lost somewhere in between.

    until next time, search and socialise 🙂

  • What do you recommend?

    One feature that helps add weight (generally) to a LinkedIn Profile is ‘Recommendations’. I’m not getting into debates on how it’s used etc, that’s a subjective thing, but someone else acknowledging that the concerned person has certain skills does help. Facebook recommends friends, Twitter recommends users to follow. These are three layers – in LinkedIn its a human, in Facebook its an algorithm basis the user’s location, friends etc, and as for Twitter, well, Twitter just decides – no algorithms. But its ok, we recommend links to each other on Twitter. 🙂

    A few activities recently made me think of recommendations. Two from Google and one from Facebook. A TechCrunch article from a few days back states that Google Friend Connect now has a widget that can help publishers know (and display) which parts of their websites their visitors like best. So it helps both parties. I’m guessing it should also help Google figure out a little more data on who reads what where, and therefore some thing that can be used to improve Ad Sense’s effectiveness. 🙂

    One of Google’s services that uses a recommendation mechanism is Google Reader. Google has now added a feature on Reader that lets you know which of your friends are still worth following on Reader, basis your consumption of their shares. I wonder if they’ll utilise this data for new users – eg. if A and B are existing users and C joins the service, will Google use the A’s and B’s data to help C start off? I also think users should have the option of sharing their own trends data with each other, tools can be used to enhance utility – eg. if i know that 90% of my friends are following TC, then I might share less of TC items.

    Meanwhile, RWW thinks that Facebook has to be working on some recommendation technology. With those thumbs up and down signs on ads, I won’t be surprised if Facebook uses that on friends – ‘Manu liked this ad’ (so we’re serving this to you, since you’re his friend) and one more ‘rebellion’.

    Also, from RWW, a related topic, for a larger perspective – Linked Data. “Sir Tim Berners-Lee, the inventor of the Web, gave a must-view talk at the TED Conference earlier this year, evangelizing Linked Data. He said that Linked Data was a sea change akin to the invention of the WWW itself.” We are moving towards a web that’s increasingly inter connected.

    That made me think – we’ve reached a state where you can now login to Facebook with your GMail id (not vice versa yet), thanks to its working with OpenID. There are tools on existing social networks (and new services) for location based social networking. Made me think of the potential of a larger recommendation based web experience, that can then spill over on to real life. Recommendations are already being used, even in online commerce.

    But what it actually made me think is about a larger system where say, Facebook, the ad publisher and I will all share revenue if the friend does some positive action on the ad served to him, thanks to me. And of course, Google will then use this info to serve ads to me later, or utilise this on its own Friend Connect + iGoogle+ AdSense . 😉

    Virtually connected lifestreams and real money. The friends of friends of friends connection utilised upto a huge degree (with privacy controls) – its not a real social connection, only an algorithm that would calculate relevance basis the degree of separation and the history of activities. Recommendations of ideas, links, ads, people, jobs, music, books and any kind of products, services etc.. an algorithm boost to ‘serendipity’, if you will 🙂 It even works the other way, so  if you say, log in to a site to check out products, it immediately searches to see if there’s a recommendation it can push at you. Trust automatically plays a key role, and how well past recommendations have worked for you.

    Meanwhile, let’s hope that Google doesn’t make a social algorithm to top the one they’re working on now – to identify which of its employees are likely to quit. A recommendation feature that allows one employee to suggest another would be a Google killer. 😉

    until next time, ahem, some social advertising -I’d recommend watching this space – for a virtual interview 😉

  • “What will you do when the money goes?”

    Even as stories abound about a Google acquisition of Twitter, Adage had a story on how Google is already making money out of tweets. According to the article, Google is offering ad units that display the client’s five most recent tweets across the AdSense network. The link leads straight to the client’s twitter account, and the campaign is measurable by the increase in follower count. One could say that Twitter gets some publicity out of this, but its obviously not getting any money.

    The ad network Federated Media recently launched ExecTweets, a site that aggregates tweets from business executives. The site is sponsored by Microsoft. With a twitter account, you can join the conversation, receive tweets from the community and vote for tweets and execs. At least on this one, Twitter will make some money.

    Since we have mentioned two biggies, might as well mention the third too, though what they’re doing is different from the above. Sideline is the desktop app from Yahoo, that runs via the AdobeAIR platform. It can do custom search groups, advanced queries and auto refreshes by pulling in data from tweets. There are other services that offer similar features, but maybe there’s more coming. And it does promise 20% more awesomeness. 🙂 On a tangent, a service called Say Tweet, which I have used in my personal blog to display my Twitter status, does give a sense of what Yahoo could do with Flickr and Twitter.

    In addition to the biggies above who’re using Twitter, there are numerous applications and services being built based on Twitter, and several others inspired by Twitter. A few examples. Tinker, from advertising and publishing network Glam Media, allows users to track real time conversations (from facebook and Twitter) happening around TV shows, entertainment events, conferences, and so on. It gives information on events by showing most followed and most discussed streams, popular events, and on trends with charts and historical data.  It also has embeddable widgets, which can be used to view a feed as well as update. They already have advertising and featured events and have further monetisation plans. iList Micro, from the iList service that alllows you to broadcast your listing to friends across networks, is the Twitter version and uses the hashtags #ihave and #iwant to create a simple process of classifieds. I have already mentoned Yammer (which now offers integration with Twitter), and Blellow in earlier posts, which are renditions of Twitter for more niche/enterprise uses, there’s also status.net arriving in a couple of months time.

    In spite of the several ways in which business are using Twitter, and the potential, I actually get worried when such services pop up on a regular basis, because I fear that when each service figures out a revenue model, one door could possibly be closing for Twitter itself. For instance, recently Jeremiah Owyang had a good post on social CRM being the future of Twitter, and within a few days, I read about Salesforce adding Twitter analytics to its CRM offering, and about CoTweet, a part marketing-part CRM tool.

    Twitter hasn’t been idle. From experimenting with advertising on profile pages (for third party and own apps, free for now) to tweaking title tags for better Google results, to hiring a concierge for celebrities (yes, really!) a lot is being done. And there’s also a new homepage design (limited roll out) which gives more prominence for the search function and increases homepage stickiness. It will also display popular trending topics (like in the current search homepage). (Hmm, perhaps one ad every 5 items, I wouldn’t mind that when i search)

    With the new funding, perhaps they have enough money in the bank to wait, watch new services, and incorporate the popular ones into their own functionality, in order to provide a diverse and robust service to all kinds of users.  Twitter is so open ended that it is different things to different people, but I wonder if identifying a few areas that they’d want to develop for revenues is of prime importance now. What I’m worried about is other services staking out potential revenue models, and whether addition of features towards no particular intent might result in everyone else but them making money out of these very features. But hey, maybe they have a plan. 🙂

    until next time, tweet dreams

    PS. the lyrics of the song mentioned in the title 🙂