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            1. Showing posts with label network effect. Show all posts
              Showing posts with label network effect. Show all posts

              Friday, August 31, 2012

              Designing The Next-generation Review And Recommendation System


              It's unfortunate that despite of the popularity of social networks and plenty of other services that leverage network effects, the review and recommendation systems that are supposed to help users make the right decisions haven't changed much.

              Thumbs-up and thumbs-down or likes and unlikes signal two things: popularity and polarization. If a YouTube video has 400 thumbs-up and 500 thumbs-down it means that the video is popular as well as polarized, but it doesn't tell me whether I will like it or not. The star review system also signals two things - on average how good something is and whether it's significant or not. There are multiple problems with this approach. An item with 8 reviews, all 5 stars, could be really bad compared to an item that has 300 reviews with 3.5 stars. Star ratings alone, without associated descriptive reviews, wouldn't make much sense if there aren't enough people who have reviewed the item. Also, relying on an average rating alone could also be problematic since it lacks the polarization element. On top of it, the review and likes could be gamed.

              Pandora's as well as Netflix's recommendations are a good example of using collaborative filtering to fine tune recommendations based on user preferences. The system aggregates the overall likes and dislikes and combines that with your taste profile and a few killer algorithms to recommend what you might like. If designed well and if it has large user population, it does work. But, the challenges with such system are missing descriptive reviews and lack of ability to perform any analysis on it. If I dislike a song on Pandora, it doesn't mean the song is bad in the absolute sense. It simply means it doesn't match my taste profile. This isn't entirely true if I dislike a blender. In this case, a descriptive context is more meaningful such as I don't like this blender because it doesn't crush spinach well. People who care to make smoothies and crush ice may not care about this issue. But, these consumers have to wade through large number of reviews to determine the product fit.

              E-commerce sites review systems use the same descriptive as well as non-descriptive review systems, commonly used at all places on the internet, without any significant modifications, even if the expected investment of a user is much higher on their site. If I don't like a song, I can skip it. If I don't like a YouTube video, I can stop watching it and now if I don't like a movie I can stop streaming it. This does not apply in the traditional world of e-commerce. I absolutely need to make sure that I buy something that I like. Returning an item is a far more involved process than stop watching a movie. It's an exception, not a norm.

              Word of mouth and passive buying

              People shop in two ways: 1) they look for a specific product, research for it, and buy it. 2) they come across a product while not looking for it, like it, and buy it.

              The second way of shopping, passive buying, is as important as active buying. There are many companies with a business model built around this impulse or "serendipitous commerce", but they don't leverage collaborative filtering. I would happily read reviews of products written by my friends and people that I trust regardless of whether I'm looking for those products or not. Think of it as Disqus-style aggregated reviews by people that I trust in my social graph. This is like an online version of a cocktail party conversation where someone is raving about a new phone that he just bought. I'm not looking for a phone, but I might, in a few days. This could create new interest or expedite my decision process. This isn't done well in the online world.

              The word of mouth is still by far the best system for following recommendations. I invariably watch movies that my brother recommends to me and one of my friends will read all the books that I recommend to her. I have non-transactional relationship with my friends and family.

              Contextualized long tail 

              One of my favorite things, when I travel (leisure or business), is to try out at least one or two recommended Indian restaurants to see how Indian food compares from city to city and country to country (so far my vote for the best Indian food outside of India goes to London). While researching for a restaurant, I typically read all the reviews that I can find. Some reviewers are Indians and some are not. Also, for the reviews written by non-Indians, some are new to Indian food and some are not. In most cases people don't identify who they are and I end up guessing based on their username, description etc. These reviews, positive or negative, don't help me much to narrow down which restaurant I should try out.

              I have always found the best food at the most unusual places. All sophisticated recommendation systems would fall short of helping me find such an unusual place. These places are not the hits. They are the long tail. Getting to this long tail isn't an easy process - a lot of asking around, digging for reviews, trying out a few awful places etc.

              Privacy concerns and connected identities

              As the debate between anonymity and identity continues, there has been a little or no effort to get to the middle-ground, a connected identity. As a marketer I don't care who Jane is in its absolute sense but I am interested in what she likes and dislikes based on her collective and aggregated behavior across the Internet and beyond. This is not an easy system to build and consumers won't sign up for this unless there's a significant value for them. The popularity of social networks is an example where even if users are arguably upset about their privacy they still use it since the value that they receive far outweighs their concern. And remember the social networks follow the power laws. As more and more people use it the network becomes more and more valuable to the users.

              Why not design review and recommendation systems that are based on connected identities? Users don't want ads, the marketers do. If companies can focus on building good products, incentivize users to write reviews, and rely on great recommendation systems to connect the right users with right products they wouldn't need ads. The marketers are chasing the illusion of targeting the right users but the inconvenient truth is that it's incredibly hard to find those users and if they do find them, they don't really want ads. What they really want is value for their money. That is the inherent conflict between the marketers and end users.

              Using connected identities beyond reviews and recommendations

              Connected identities are also useful beyond reviews and recommendation systems. Comcast support is one of those examples where using connected identities could greatly improve their customer support.

              Comcast started using Twitter early on to respond to customers' support issues. It was a novel concept in the beginning and they really understood Twitter as an effective social media channel, but lately that model has turned out to be as bad as their phone customer support. When I tweet to @comcastcares someones gets back to me asking who I am and what issues I have. You follow me, I follow you, you DM me, I DM you my info, and after few minutes, we are nowhere close to resolving the issue. What if Comcast allowed me to attach my Twitter account to my Comcast profile? I will OAuth that, for sure. When I tweet, they exactly know who I am, what problem I am experiencing, and how they might be able to help me. This is an example of using a connected identity without compromising privacy. Comcast knows their customer's billing information; it's transactional information. But they attempt to use Twitter to communicate with you without connecting these two identities.

              I don't want to "like" Comcast or "follow" Comcast to be a victim of their spam and indifference. Comcast is easy to pick on, but there are plenty of other examples where connected identities could be useful.

              Users don't like to be sold at, but they do want to buy. Let's build the next-generation review and recommendation system to help them.

              Monday, June 25, 2012

              With Yammer, Microsoft Begins Its Journey From Collaborative To Social


              Confirming what we already knew, today Microsoft announced they are acquiring Yammer for $1.2 billion in cold cash. Here's a blog post by David Sacks, the CEO of Yammer.

              Microsoft doesn't report a revenue breakdown for their individual products but SharePoint is believed to be one of the fastest growing products with annual revenue of more than $1 billion. Regardless of how Microsoft markets and positions SharePoint, it has always been collaboration software and not really social software. Microsoft does seem to understand the challenges it faces in moving their portfolio of products to the cloud, including SharePoint. Microsoft also understands value of having end users on their side even though SharePoint is sold as enterprise software. Microsoft's challenges in transitioning to the cloud are similar to the ones faced by other on-premise enterprise software vendors.

              But, I really admire Microsoft's commitment by not giving up on any of these things. Skype's acquisition was about reaching those millions of end users and they continue to do that with their acquisition of Yammer. Going from collaborative to social requires being able to play at the grassroots level in an organization as opposed to a top down push and more importantly being able to create and leverage network effects. It's incredibly difficult to lead in with an on-premise solution retrofitted for cloud to create network effects. Native cloud solutions do have this advantage. Yammer will do this really well while helping Microsoft to strengthen SharePoint as a product and maintain its revenue without compromising margins. If Microsoft executes this well, they might unlock a solution for their Innovator's Dilemma.

              With Yammer, Microsoft does have an opportunity to fill in the missing half of social enterprise by transforming productivity silos into collaborative content curation. As a social enterprise software enthusiast, I would love to see it happen, sooner rather than later.

              At personal level, I am excited to see the push for social in enterprise software and a strong will and desire to cater to the end users and not just the decision makers.  I hope that more entrepreneurs recognize that enterprise software could be social, cool, and lucrative. This also strengthens market position for the vendors such as Box and Asana.

              It's impressive what an incumbent can do when they decide to execute on their strategy. Microsoft is fighting multiple battles. They do have the right cards. It's to be seen how they play the game.

              Tuesday, January 31, 2012

              To RIM: Don't Change The Strategy, Change The Rules


              A lot has been said and discussed about RIM's downfall: indecisive leadership, inability to innovate at fast pace, and no clear path to recovery. I don't disagree at all with the analysis and the interpretation of the situation, but I do disagree with the conclusion that many people are drawing and vehemently disagree with their advice to RIM to keep trying to regain the smartphone market share. That train has left the station and RIM doesn't have a chance to catch up, even if they do everything that they could.

              But RIM may have stumbled upon something that they probably least expected. It's the BlackBerry Messaging, popularly known as BBM. We got to see the power of BBM during the London riots. During my recent trip to India, I firsthand witnessed how much of people's lives depend on BBM. These people were sad, upset, and depressed due to a RIM infrastructure outage. This is a phenomenal success. The recipe behind this success is quite simple: provide free messaging that looks likes SMS that supports groups in a network. RIM has significantly leveraged network effects; BBM got better as more and more people used it. The sale of BlackBerry in India has gone viral. The consumers buy Blackberries since their friends have it so that they can chat with them for free and perhaps do their emails. These consumers don't use any apps at all! Their needs are quite simple. These phones are also priced well - the median price is somewhat around $200 for an unlocked phone. The Indian middle class and upper middle class have no issues shelling out this money to buy a BlackBerry. I talked to quite a few people and they are moving away from Android and iPhone to BlackBerry. Yes, that's right. If RIM can manage to introduce lower end versions of BlackBerry this will further fuel the growth.

              May be, just may be, there's a category between smart and non-smart phones. For a large number of people in emerging economies making a phone call and staying in touch with their friends and family via text messages and email, and not paying too much for doing that are the driving reasons to purchase a right kind of a phone.

              Let's briefly look at the history of RIM. It was the device of choice for email and calendering and perhaps still is for a lot of people. RIM myopically focused on going after the enterprise customers while iPhone and Android pulled the rug underneath them. RIM initially ignored and later underestimated the disruptive nature of this innovation. What started out as a consumer market, iPhone and Android easily crossed the chasm and entered into an enterprise and started replacing BlackBerry. We all know this story. But, something happened during this era of RIM: they ended up building a massively scalable and reliable enterprise class messaging infrastructure. This is an amazing feat of technical excellence. Building BlackBerry Messaging was a logical extension of leveraging this infrastructure. What if RIM uses this as a strength and not worry about competing in the smart OS area.

              It's time to pivot.

              Build a robust phone that is primarily driven off by BlackBerry Messaging and double down in emerging economies. Change the rules of the game and beat Nokia at its own strategy. Even better, spin off BlackBerry into two separate businesses: one that exclusively focuses on this strength and the other that embraces innovation by OEMing either Android or Windows or both and defend the handset as well as the services market share. I don't believe BlackBerry is cut out to innovate on a new smart phone OS quick enough to beat iOS or Android or an emerging contender, Windows phone. That would mean playing by your competitors' rules. If you learn one thing from Apple, it would be not to do this.

              I don't need to tell you how many cellphones the Indians own and how many of those can buy a BlackBerry. This may not be an intended move, but this social effects driven business in emerging economies such as India as well as in other developed countries could be the second act for BlackBerry. Can other vendors replicate this? May be. Not many companies in the world can do what BlackBerry does with emails and messaging in general. Group messaging on a mobile device is a killer app in itself to drive the sales of handsets. Also, this works across the carriers and the geographies, essentially allowing RIM not to be threatened by a provider. SMS GupShup in India has been an extremely popular group messaging service. It's a validation that there is significant untapped potential for RIM.

              Photo courtesy: NoHoDamon

              Thursday, July 28, 2011

              Plotting for serendipity


              I rarely eat lunch at my desk. Eating lunch in a cafeteria is such a precious opportunity to waste. I plot for serendipity. That's right. Some of the best conversations that I have had with people — on my way to a cafetaria or in the cafeteria — are purely serendipitous, but they're not purely accidental. I even pick a cafeteria that requires me to walk a little more. I believe you can always create opportunities for good things to happen to you. When people say "It's a small world", they are so wrong. The world isn't small but they're at the right place at the right time to think it's a coincidence. The coincidences do happen but there's a larger force behind orchestrating the possibilities for such coincidences to occur.

              The same applies to creativity. You can design an epiphany.

              I have heard people say that they had an epiphany while they were in shower. It's not the shower but it's illumination followed by a prolonged incubation, two phases of creativity. The other two phases are preparation and verification. Preparation is a phase where you decide that you want to solve a specific problem. When you continue to work on a problem over a period of time, your brain, the unconscious, never stops working on it even if consciously you're not spending any time on it. This is called incubation. This lasts for a while. The "shower moment" is the illumination phase where you finally figured out a solution, after your brain unconsciously kept solving it for the entire night, and hence the metaphor of glowing bulb for innovation. What remains is the verification phase to prove that the solution works. We all do this, but we don't spend enough time on the incubation phase and hence many ideas don't go beyond that. You can plot for this epiphany by not letting a problem go for a while even though you think that you don't have enough time to work on it. I tell my students to start working on their projects early on for better results for that purpose. It feels counterintuitive that you could solve a problem by spending less time on it as long as you keep solving it for a longer duration off and on.

              I have blogged about cloud being a natural platform to design tools that could create network effects. The tools that create network effects also offer an opportunity for digital serendipity. I have discovered many people through Twitter and learned quite a few things that I would have never explicitly made an attempt to learn. And, I'm not the only one who has had such an experience. I'm a big fan of social tools and platforms that enable opportunities for such serendipity to occur. There're only so many cafes and water fountains in the physical world; the digital world is far bigger in that sense.

              Design your routine to plot for serendipity and epiphany and credit yourself instead of the shower. Creativity can be tricked. You will be positively surprised.

              Cross-posted on my personal blog

              Monday, December 1, 2008

              Does Cloud Computing Help Create Network Effect To Support Crowdsourcing And Collaborative Filtering?

              Nick has a long post about Tim O'Reilly not getting the cloud. He questions Tim's assumptions on Web 2.0, network effects, power laws, and cloud computing. Both of them have good points.

              O'Reilly comments on the cloud in the context of network effects:

              "Cloud computing, at least in the sense that Hugh seems to be using the term, as a synonym for the infrastructure level of the cloud as best exemplified by Amazon S3 and EC2, doesn't have this kind of dynamic."

              Nick argues:

              "The network effect is indeed an important force shaping business online, and O'Reilly is right to remind us of that fact. But he's wrong to suggest that the network effect is the only or the most powerful means of achieving superior market share or profitability online or that it will be the defining formative factor for cloud computing."

              Both of them also argue about applying power laws to the cloud computing. I am with Nick on the power laws but strongly disagree with him on his view of cloud computing and network effects. The cloud at the infrastructure level will still follow the power laws due to the inherent capital intensive requirements of a data center and the tools on the cloud would help create network effects. Let's make sure we all understand what the powers laws are:

              "In systems where many people are free to choose between many options, a small subset of the whole will get a disproportionate amount of traffic (or attention, or income), even if no members of the system actively work towards such an outcome. This has nothing to do with moral weakness, selling out, or any other psychological explanation. The very act of choosing, spread widely enough and freely enough, creates a power law distribution."

              Any network effect starts with a small set of something and it eventually grows bigger and bigger - users, content etc. The cloud makes it a great platform for such systems that demand this kind of growth. The adoption barrier is close to zero for the companies whose business model actually depends upon creating these effects. They can provision their users, applications, and content on the cloud and be up and running in minutes and can grow as the user base and the content grows. This actually shifts the power to the smaller players and help them compete with the big cloud players and yet allow them to create network effects.

              The big cloud players, that are currently on the supply side of this utility mode, have few options on the table. They either can keep themselves to the infrastructure business and I would wear my skeptic hat and agree with a lot of people on the poor viability of this capital intensive business model that has very high operational cost. This option alone does not make sense and the big companies have to have a strategic intent behind such large investment.

              The strategic intent could be to SaaS up their tools and applications on the cloud. The investment and control over the infrastructure would provide a head start. They can also bring in partner ecosystem and crowdsource large user community to create a network effect of social innovation that is based on collective intelligence which in turn would make the tools better. One of the challenges with the recommendation systems that uses collaborative filtering is to be able to mine massive information that includes users' data and behavior and compute the correlation by linking it with massive information from other sources. The cloud makes a good platform for such requirements due to its inherent ability to store vast amount of information and perform massive parallel processing across heterogeneous sources. There are obvious privacy and security issues with this kind of approach but they are not impossible to resolve.

              Google, Amazon, and Microsoft are the supply side cloud infrastructure players that are already moving in the demand side of the tools business though I would not call them the equal players exploring all the opportunities.

              And last but not the least, there is a sustainability angle around the cloud providers. They can help consolidate thousands of data centers into few hundreds based on the geographical coverage, availability of water, energy, and dark fiber etc. This is similar to consolidating hundreds of dirty coal plants into few non-coal green power plants that can produce clean energy with efficient transmission and distribution system.
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