Monetizing Facebook : Looking beyond Advertising

A lot has been said and discussed about the recent $50b valuation for Facebook. Analysts on both sides of the camp are speculating the revenue potential of Facebook to justify such a high valuation. While I do agree that Advertising will be a major part of revenue for Facebook, I also think that monetizing through only existing ppc/display advertising is the least creative way of making money. 

In the long term, I think Facebook has the potential to become the defacto search engine probably partnering with Bing, with search results more relevant and personal, and rake in all the ad revenue. But that is far away. In the medium term to long term, I think Facebook's Instant Personalization feature has a brighter potential. 


Think of Facebook as an information bank, your information bank. You have stored your info about friends, photos, likes, dislikes etc) in Facebook. This data is persistant, and as you browse through the web over time, a trail of your likes, fan pages, etc, if mined and organised according to context, can give a wealth of information. If you store your money in any bank, (in a savings account), you get interest. What do you get for storing your information in Facebook? What will Facebook get by allowing you to store your information and keeping track and organising your information? The answer to that lies in facebook's potential to make the web infinitely more relevant to you, for the given context at every point in time. As a facebook user, you will get relevancy, and trusted information to consume as browse through the web. Facebook will monetize from the business houses that need this information about you; I think this is a more stable strategy for Facebook. 

Example: Take Yelp. One of the partner sites for Instant Personalisation.

As a Yelp user, if I search for Indian restaurants, I am confused by all the reviews I get to read, (organised by time). I dont know who is who, and I dont even know who is real. But, say somehow, when I search for Indian Restaurants in bay area, in Yelp, I get reviews organised by those written by my friends, and ordered by those written by Indian users (who share the same taste sense that I do), would it be more useful to me or not? I think yes. So how can this magic happen?

Facebook's instant personalization. Facebook could charge for this data. Facebook, shares your data only if you have explicitly authorized. You will authorise facebook, only if there is value for you - in this case, more relevancy in reviews leading to a happier dining experience. This information about you is dynamic. It will keep changing - you will keep adding friends, have more likes, do new things. So Facebook will continuously organise your information in a way useful to the businesses and share it with them so that they can then make the web and life more relevant for you because you want it that way. And businesses could pay Facebook a contracted amount, or per server call (each time the site makes a call to Facebook servers to request information about the user);

Privacy Concerns - What about them?

Of course, there are going to caveats and road blocks. Facebook cannot share all the information about you, and all the privacy concerns are going to be there. But they will soon fade away. See the trend about privacy concerns in the last 10 years. People are more and more willing to trade their privacy for relevancy and personalised experiences. Today, more and more people are using their real names in the web, especially in professional forums, because that is the identity they want to share about themselves online. Adoption rates for using credit card numbers in eCommerce transactions is another indicator this effect.

Facebook Connect is the first real workable alternative for SSO -single sign on - in the web. As it catches us, the web will be Facebooked all over. There will be a tipping point beyond which people will increasingly find it useful to connect their Facebook accounts because it is useful for them to do so, usefulness having derived from the increased relevancy owing to the presence their facebook network in those sites. A subtle network effect. By then, I expect people to increasingly give up their control on their data privacy, and this phenomenon will only get accelerated by institutional and technological measures erected to ensure that information is not misused.


Summary:


Using the Instant Personalization feature and Partnering with other online portals where the users hangout/transact/entertain themselves/consume information/ has a revenue generation potential for Facebook. Facebook could continuously organize your information in a way useful to the businesses and share it with them so that they can then make the web and life more relevant for you because you want it that way. And businesses could pay Facebook a contracted amount, or per server call (each time the site makes a call to Facebook servers to request information about the user). Privacy concerns will force Facebook to take a calibrated approach to the implementation of this strategy. However, I predict that users themselves will be increasingly less concerned about privacy over time. Its a near win-win solution. 

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Is search engine Blekko's current product design for crowdsourcing tags for websites, a viable solution?

Search engine Blekko has been getting a lot of PR from Techcrunch. In short, what Blekko does is to allow users to search the web using tags created by crowdsourcing - read fellow users searching in Blekko.  In my humble opinion, Blekko's crowndsourcing method of classifying (adding tags) to sites has limited scope of success. I say this because of two reasons:-

The like and spam buttons are in the SERP (search results page). Can you, as a user, come to a realistic conclusion about the page, as either one that belongs to a particular tag (here in this case - for search query python - the site could about the reptile python or programming language python) ? And is this snippet good enough to know whether the site is a spam? I guess, the answer to both question is a No.

1. The use case for adding tags/classifying a site as spam is unrealistic.

-User searches for a keyword

-Blekko displays the SERP.

Take a look at the anotated picture of the SERP.

Lets continue with the use case -

-User navigates to a site by clicking on a link in SERP.

-User consumes the site content.

-User now wishes to tag the site as "/programming language"; or mark the site as spam

Now what? The only realistic way I can think of is to hit the back button, and get back to blekko SERP, and do the tagging. If the user is already 5-6 pages deep in that site, this is not an option. I couldnt see a easy way to add tags in the current setting. Of course, there are other methods to create slashtags such as adding them through the profile page or using shortcut /add. However, those methods are very cumbersome even for a mild-geek like me.

One possible way out: - It would be nice to explore if having a browser plugin will make adding tags a easier process. For example, if blekko plugin can simply display a lightbox/dialogbox/popup(or, whatever), in each page, and the user simply add tags AFTER reading the site content? Can Blekko build a plugin for chrome browser?

Again, the problem is, this method will require explicit installation at client end, and that requirement will greatly reduce the install base. But the tags are more likely to be relevant than tags added by reading just a snippet in SERP.

The bottom line is, blekko must make adding tags an effortless, and a realistic process, especially for the 2 second attention span Gen Y and Z.

2. Is it realistic to tag the billions of websites by crowdsourcing alone? I think the machine learning approach will be more effective.

Many sites today use Google Analytics for web analytics. (i suspect especially many of these spam sites, and fly by wire content factory sites use GA). For a given search query, I would like to believe that Google might be able to factor in the bounce rates of these pages from the GA data, into their page rank algorithm. I think Google is in a better position to bring in more relevancy by factoring in data from Google Analytics. I am not sure whether Google does this kind of thing, and I think no can ever tell. (Alternative views are welcome.)

PS: Since tags are user generated, I suspect that many variations for the same tag may be found. For example, www.lonelyplanet.come can be tagged as travel, travl, tourism, etc. Blekko would need to have strong tag rewriting algorithms (similar to standard search query rewriting techniques in IR(information retrieval) ) to group similar tags in a topic/genre in intelligent way, and bring more relevancy and precision in search results.

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Facebook "Push" marketing vs Adwords "pull" marketing : Impact on ad bid prices

The differences between a Facebook marketing campaign, and SEM (Search Engine Marketing aka Google Adwords marketing) have discussed adequately in several places in the web. I want to bring out an insight on the impact of a key difference (the facebook ad push vs google ad pull) on your ad cpc/cpm pricing. I assume that the reader has basic knowledge about how Google Adwords and Facebook Advertising works.

The search engine "pull" use case (for Google Adwords) is simple - the user searches for a query, and google matches the ads where search query == bid phrase. The position of your ad is determined by your max-bids.In Google, the competing bids for your keywords are from businesses similar to yours; you bid for keywords and the cost of the keywords naturally depends upon other bidders, who happen to be related to your own business. For example, if you bid for the keyword -" modular homes California - your price depends on other bidders who bid for similar keywords; now, who will bid for such keywords? Naturally, your direct competitors, and other players who manufacture peripheral products, accessories, or who offer repairs and services for modular homes, and the like. So, the spectrum of bidders will comprise of bidders who have business related to modular/manufactured homes that are likely to be energy efficient, and easy to transport etc.


In Facebook advertising, however, we have the "push" use case - you target your ads to a particular demographic, who are also most likely the target of several other products/services/business that all have different margins, and marketing budgets. For example, you can choose the target demographics - users who are between 30 & 50 years old, living in California, who have "liked" anything related to homes. ( we could keep adding more likes such as "liked" sustainable living products etc) Now, this target demographic is same for tens of other businesses, for example, insurance companies selling home insurance. And, naturally, the margins, and marketing budgets for each of these businesses will be different, and may be far higher than your products. They will bid more for the target demographic.So if your value per click(or per thousand views) is $10, you could be out bidded by another business who is bidding for the same demographic, and whose value per click(or per thousand views) is say $50. So the Avg CPC or CPM could be much higher in Facebook.


In a situation where ad inventory == supply of pageviews, you are fine. Facebook will achieve its target displays for all ads in the inventory. This is more likely when your parameters for target demographic is broad based, and facebook can display your ads to anyone. your ROI in this case may be less than ideal. The more targeted you want your ad demograhic, the lesser is the audience, and more is the competition, and you may be competing with deep pocket business, whereas in google, you were competing with similar businesses. This one aspect may push up the max bid value. Also, consider that FB can show only 5 ads per page, whereas in Google there are about 10 spots. This intensifies the competition in FB, and pushes up the bid prices. In one of the ad campaigns I ran (in both Google Adwords and Facebook Advertising) for a home manufacturing company, Facebook consistently suggested a higher bid price of $2+ for our ads but our Google Adwords campaign managed an avg cpc of $1.31(it is another matter that we bid over $3 but google wouldnt push up the ad to 1st spot due to low quality score. I dont think Facebook has such an algorithm). 


But that said, Facebook leads are not likely to convert in first visit, and a direct ROI comparison with Google cannot be normally done. Generally, the Facebook campaigns are primarily for generating brand/product awareness. A more thorough ROI analysis can be done if only we can track the first source of leadgen for conversions in your site. If you use google analytics, you can set the parameter "utm_nooverride=1" in your landing page url. This will attribute the conversion to very first source of lead, and thus you can track a conversion that first came to your site using Facebook, (brand awareness), and say later converted in the 3rd or 4th visit. But a more accurate ROI will be after analyzing the conversions over a period of 3-4 months(depending upon the purchase cycle of your products), as FB leads will likely convert in later visits.

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Groupon Stores: Implications for Groupon

In my last post I discussed the weak Network Effects of Groupon Business Model. Groupon clearly understands this problem of weak (or, lack of) network effects; Group CEO Andrew Mason said Groupon is the  "N Sync of Websites", and acknowledged that Group Buying is not a winner takes all market. Groupon also has a long line merchants waiting to run their deals in the Groupon site. One way to increase the network effect is to become a deal marketplace for local businesses. Groupon will drive traffic, and merchants run deal on a pay for performance model. Not surprisingly, Groupon recently announced the launch of ‘Groupon Stores’; according to Groupon’s blog, “With Groupon Stores, businesses can now create and launch their own deals whenever they want. Think of it as the online equivalent of a merchant’s physical storefront.”. The blog also says “Today things are different – our biggest problem is that demand is so high, merchants often wait months to be featured. And while we once only had a few thousand customers per city, now we have hundreds of thousands (Chicago just added its millionth subscriber!) – making it increasingly difficult to find one deal that satisfies everyone”

Some of the implications of Groupon Stores for Groupon that come to my mind are:-

Strengthen Network Effects. Surely, introduction of Groupon Stores will significantly help several hundreds of merchants to run their own deals in Groupon. This is likely to attract even more users, and contribute to the existing weak network effects.

Scaling business without costs. Because merchants would be signing up individually, there will be limited requirement of sales force, and since merchants will run their own deals, there will be no added requirement for copywriters. Essentially, the cost of adding a new merchant under Groupon Store is not significant.

 “Freemium” Customer Acquisition model. Groupon Stores allows merchants to try the effectiveness of Groupon, at a low cost, before they sign up for the Home Page Deal with Groupon.  For Groupon, this is also an easier way to acquire new customers.

Deal discoverability and Conflict of Interest:  Users primary discover deals through the daily emails that Groupon pushes to its users. In Groupon Stores, there will be some algorithm that Groupon will run to select and feed the best deals to its users. I see a conflict of interest here: Because Groupon takes 10% of the deal value, all other things being equal, it is incentivized to push the deals that has more revenue potential.  For Groupon, merchant A offering a 50% discount off massage deal worth $250 is more likely to be worth less than merchant B offering a similar service for $100, or worth less than merchant C offering boating trip worth $300. I want to see how Groupon is going to balance the different sets of incentives, and feeds the deals.

Need for good Search and Recommendation Engines. I suspect that it might be possible for users to directly visit Groupon’s site and browse for deals.  I hope Groupon builds a powerful recommendation engine to help the user discover the products/services (s)he  may like.  Also, Groupon must have a powerful search engine to help users search for deals.

Need to Manage Merchant Entropy.  In an open for all model, Groupon is also likely to attract merchants who are less than ideal to do business with. There might be an increased requirement for customer support, and fraud prevention. What if the merchant doesn’t honor the deal? Groupon will refund the money to the user, but what systems are going to be available for the users to give ratings to merchants? Can other users base their purchases of deals, on the ratings of the merchants?  As the number of merchants grows, how can Groupon keep the climate of trust intact?

If not executed well, Groupon is likely to enter the murky waters that eBay is struggling to get out. That said, I am excited to see how the Groupon Stores changes the game for local businesses. 

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Network Effects in Groupon Business Model

With 40 million subscribers from over 300 markets from 35 countries, and with 20 million groupons already sold as of date, Groupon is a raging success.  Groupon provides a real “Pay for Performance” marketing model for local businesses, helping them get new customers using the power of viral web marketing.  Groupon also recently started providing Deal Statistics including aggregate buyer demographics such as gender, age and Zip code, share of purchases bought as gifts, distribution of sales by time etc, to merchants running the deals. Having such data will help the merchants to better understand their customers, and make product offerings and their marketing campaigns more focused to their customers.

But how defensible is Groupon’s market position? The barriers to entry in group buying business are so low, that as per Groupon CEO Andrew Mason, there are 500 Groupon clones in the market. Unlike a true marketplace such as eBay, there are limited network efforts in the Groupon’s business model.  The network effects of Groupon is induced by

•  40million subscribers, who attract more merchants to want run deals at Groupon, and hence more deals for the users, attracting even more users.
•  More merchants would mean deals available in different products and services, and Groupon can run more personalized deals to cater for subsets of users.
•  Because there are more users, the chances of any deal going through are much higher, resulting in more successful deals, which add value to both user and the merchant, attracting even more users and merchants.
• Also more users, and more deals will give more data to mine, and will significantly improve the personalization algorithms, resulting in better personalized deals, which adds value to users.

A pictorial representation of network effects in Groupon Business model:-

Network Effects in Groupon Business Model

However, for users and merchants, there are no barriers to exit. What stops a user from signing up for a deal elsewhere? What stops a merchant from running the deal in another site offering similar access to users? I think the current business model of Groupon at best induces weak network effects, and is completely vulnerable to competitive forces. There is no stickyness in the system, and there are no switching costs for any of the stakeholders. Groupon can increase the stickyness by rapidly growing and having a large user base which will be attractive to the merchants, and vice versa. But  even a strong network effect is not a guarantee for success, and in fact network effects alone have never been enough to make users stick to a product/service for long.  The best example is Facebook, which dethroned MySpace with a better technology and product.  Users look for value, and merchants look for profits; In a free market, customers (users and merchants) will use that service that maximizes their utility. Groupon is no exception to this established principle in market economics.

Further, the network effect in Groupon business model, albeit weak, is induced by symbiotic growth of number of users and number of  merchants.While Groupon has no added cost in scaling up its user base, (in fact, it added 3million users in just one week), it is a different story when it comes to adding merchants, and running deals. Groupon has a significant number of sales persons who acquire merchants, and copywriters who write attractive ads for the deals, on behalf of the merchants. In order to scale up the number of merchants, Groupon must also increase its sales force, and copy writers; scaling comes at a cost, and it will likely reduce the slope o the hockey stick in the Groupon’s financial graphs.

It is not that Groupon is not aware of these vulnerabilities. In fact Groupon appears to be taking significant steps to defend the fertile group buying market they created from scratch. Recently, Groupon has announced their plan for introducing "Groupon Stores", which will enable any merchant to run their own deals in Groupon. I have discussed about the possible implications of Groupon Stores, for Groupon, in my next post.

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Kindle for Facebook - An analysis of a new product idea

Recently Amazon unveiled its Kindle for the web application that would allow anyone to read a kindle book in a web browser. I thought it would be nice to extend this idea to a new product called the “Kindle for Facebook” app, which will allow a Facebook user to preview a Kindle version of the books listed in the books section of his/her friend’s Facebook profile information page, and should the user like the book, then purchase the book seamlessly right from the app. Amazon is already pushing for greater technological integration with Facebook to improve recommendations, and take a leap towards social shopping. “Facebook for Kindle” app could be another solid step, providing utility to all the stakeholders – users, Facebook, and Amazon.


Currently, when a Facebook user hovers on any thumbnail/link in the Books section of any Facebook profile information page, Facebook presents a layer like this





If you are Facebook user, ask yourself how many times you have updated your books section? I had not updated in over 3 years. A few months ago, Facebook started recommending books pages to me, and when I ‘liked’ them, Facebook automatically updated my Books section information page. Sweet.So, what is next?


Here is my idea for “Kindle for Facebook”; before we dive into the opportunities and challenges, let’s look at the use case first.


Pre Conditions :

• User has his/her Facebook Account linked with Amazon.
• User has set the required settings and has activated 1-Click buy option, in Amazon.
• User has given the necessary permissions to the “Kindle for Facebook” app in Facebook.

Use Case:

• User navigates to any Facebook profile, and browses a profile information page
• User hovers the mouse over the books link/thumbnail.
• If a Kindle version of the book is available, Facebook displays the layer like this

• User reads the chapter in the Kindle for Facebook app that has been seamlessly integrated into the presentation layer.
• User wishes to purchase the kindle book, and clicks the “Buy now with 1-Click” button.
• Kindle for Facebook app completes the necessary transaction in Amazon back end, and delivers the Kindle to user (as per his/her existing Kindle settings)

What problem does this app potentially solve?


Users: Users read about their friends interests in books but they actually never get an immediate opportunity to check out what those books are all about. This app will provide a tool for users to immediately check out what their friends read and recommended, and if that book is compelling, then have an option to immediately buy a kindle version.
Amazon: One of Amazon’s goals for Kindle for the web app is to allow any user to embed a link for Kindle book and become an affiliate. This app will virtually create an army of Amazon affiliates, and has the potential to generate a lot of traffic. Also, currently, an Amazon user has to follow a long winding navigational path inside Amazon your account page, to do anything related with shopping using recommendations using Amazon and Facebook integration. This app can serve as a turning point for greater integration of Facebook and Amazon, at the doorstep of the user. Virtually, any Facebook user can become a Kindle affiliate.
Facebook: Facebook can get revenues out of this lead generation business; Amazon and Facebook could come to some revenue sharing agreement. For Amazon, the risk free revenue share is a simple CPA model in which Facebook will get a revenue share for every successful purchase by a user. For Facebook, the risk free revenue is a CPM model in which Amazon pays for impressions(views of the Kindle book) by users. And then, there are several solutions in between this wide spectrum. But whatever the revenue share might look like, I feel that having a Kindle for Facebook could be a win-win model.


Opportunities for the Kindle for Facebook app.

• This app could be the Trojan horse for getting more users to connect their Facebook account to Amazon.
• Amazon physically sells goods only in 6 countries, but Kindle books can be purchased by any one virtually from anywhere in the world. So connecting Facebook will help Amazon gain customers instantly from new countries where they don’t have any physical presence.
• Facebook, with all their social graph and Facebook connect, is still looking for ways to expand revenues streams. “Kindle for Facebook” app will generate revenues. Also, if this model works, then Facebook can streamline the processes for new products such as “Amazon for Facebook” App, using which any user can buy any of product their friends like using this app, right from inside Facebook.
• If explicit user permissions are needed for sharing information between Amazon and Facebook, users can be incentivized to provide them, and one of the incentives could be a revenue share of a small percentage, and can be given with Amazon credits or Facebook credits that they can use it to purchase other goods in Amazon or Facebook or sites that accept Facebook credits such as gaming sites. Such a revenue share with users will also incentivize users to constantly keep their profile updated, and like/recommend the products they like.

Challenges

• I am sure there will be a number of technical challenges, which is out of scope of this article; but I am very confident that these will be the easiest ones to solve.
• Working out a revenue share business model will be a challenge. Can Amazon short Facebook by developing the app that can be installed by users themselves, an app that has no technical integration with Facebook beyond what the current Facebook APIs provide? These options need to be explored, but I guess, Facebook is unlikely to allow an app that gives Amazon a free lunch.
• Understanding the impact of such a user generated ecommerce in Facebook profiles, on the overall User Experience would be important. What will be the impact on Facebook user experience, if eventually, when a user visits any Facebook profile, he/she encounters several links to third party ecommerce sites such as Amazon. Will Facebook users like it? Will they visit their friends profile who keep posting such links, especially if they know that their friends are likely to earn some cash if they purchase the kindle book? So the challenge is not only to keep these ecommerce apps seamlessly integrated into user experience, but also understand the impact on the social capital of users who turn into Kindle affiliates in Facebook. Extensive A/B testing must be done to understand these implications. At the end of the day, Facebook must not lose its USP as a “cool place to hang out with their friends online”.
• For Amazon, the challenge will be providing a seamless purchase experience and account integration for existing customers, and an easy path for new customers to register as Amazon customers and buy the kindle book with minimal disruption to their Facebook experience.

Final word: The product manager in me many a times wakes up with new ideas, and this is one such idea that I got while reading about “Kindle for the web”. Kindle for Facebook app is neither real nor anywhere close to reality. I have only let my imagination run wildly. The mockups have been created using images from facebook.com and amazon.com. That said, I think this idea has some great potential, so much so that I actually spent some time blogging about this.

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An article from Tech Crunch: Who Is Best Positioned To Win The $20 Billion Brand Advertising Prize?

I read an interesting article in Tech Crunch : Who Is Best Positioned To Win The $20 Billion Brand Advertising Prize? 


The author analyzes how Facebook, Twitter, Groupon, and Foursquare are positioned to capture this huge brand advertisement market, and after an interesting analysis, concludes that "Based on my research, while Facebook, Twitter, Foursquare, and Groupon are the best positioned to capture the estimated $20 billion in pent-up consumer marketing dollars, none of the four are currently optimized to execute along all of the necessary dimensions. There are considerable opportunities for startups to innovate and capture share. I look for this to be one of the most attractive areas for entrepreneurs in the consumer internet for years to come."


The article is insightful and worth a read!

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Platform Strategy : In-Product App Store for Enterprise and Consumer Software – Opportunities and Challenges.

A few years ago, most enterprise software companies worked on creating superior and more powerful software products, but today enterprise software companies increasingly look towards platform architecture and platform solutions to gain competitive advantage over their competitors. Creating an App store to sell third party applications that would run on top of their software is one of the major platform solution strategies. The success of apps business for iPhone has reinforced the notion that a robust product ecosystem is not only a viable competitive advantage but also a huge barrier to entry for competitors.

Opportunities

Product ecosystem as a competitive advantage. A software product can be replicated. But platform solutions that create a robust product ecosystem of users, developers, apps, and a network that cannot be easily replicated. Customers will buy the software, not only because of the superiority of the software itself, but also because of the ability to install apps, plugins, and add-ons that suits their specific needs. The app store may not generate any significant incremental revenue by itself, but the apps marketplace will create a product ecosystem that will be a viable barrier to entry for new players trying to enter the competitive space.

Aggregated Market Place for Developers. For the developers, an app store is a one stop place to reach their target customers. In fact, all the developer needs to do is to develop and deploy apps in the app store. The app store itself has great potential to create a network effect by completing the virtuous feedback loop.

Why In-Product App Store? If the app store is available inside the desktop interface of the software, it will remove the barrier to actually go an online store elsewhere in the internet. Users can access the app store in one click. The app store is located right at the backyard of the customer, and as long as the customer is online, all apps, products and downloads related to the software can be made available right at the backyard of the user. However, an in-product feature can be only for the new releases of software. For the users for older versions of the software, the app store must be made available through an url accessible through the internet.

Outsourcing lower level R&D. Oftentimes, the company making the enterprise software is not structured to cater for the needs of every small segment of its customer base. For the company, the resources required to develop an app or a plugin to cater for a small segment may not be worth the effort, and at times, it could be highly risky to commit resources on a small piece of work. But for small 3^rd party software/app developers, this small segment could be an attractive market, and they would be willing to take the risk. Allowing 3^rd party developers to develop apps is akin to outsourcing lower level R&D, and the enterprise software company can use now their precious resources on improving the core product functionalities rather than on the peripheral improvements.

Sustained Release model. Normally, the product update cycle for enterprise software is 12-18 months, and the company sees each new version of the software as a source of incremental revenue. So the company will always group the new functionalities it has developed and market into a new version in regular yearly intervals. However, in an app store model, the 3^rd party developers can rapidly build and deploy new apps/plugins that will give the users the desired functionality without having to wait for the update, thus allowing the users to enjoy a sustained update release, albeit only if they install the apps.

Challenges

Even though there are attractive opportunities, there are a number of challenges that can delay the successful execution of the platform solutions strategy. 

App Store Product Development Cycle. The first and foremost challenge arises from the inertia and alien product development culture. An software product development cycle is about 10-12 months, where in the new release of the software is a “finished product” complete in most respects. The user, once he downloads the software to his desktop, will have to live with it until he upgrades to a new version. Compared to that, an app store is a web site, and the development time for the beta version is about 6 weeks. The web development model follows the iterative design cycle, in which each version is designed, developed, tested, refined, and redeployed, in rapid cycles. The changes can be done at the server end, and the user is able to use the improved version instantly. This rapid iteration cycle culture is very alien to most software companies. The software product development team could be wasting a lot of time developing the “perfect” initial app store without realizing the iterative design cycle, because they are hard wired to develop the app store the "software way", and/or senior management wants it that way.

Critical Mass of Apps. Creating a critical mass of the apps is very crucial to ensure that the app store goes live and kicking. Initially, the company itself may have to develop a certain number of apps, and deploy them on the app store. In order to drive traffic to the app store, other learning materials, blogs, and online help could be combined along with the app store portal. Once the traffic is ramped up to be attractive enough for 3^rd party developers to develop and deploy apps, then slowly the company can disengage from actively producing apps. The challenges of targeting the right app developers, and active marketing to app developers is a topic in itself that is beyond the scope of this article.

Growing a Developer Network. Getting the developers interested in developing apps will be a major marketing effort. This is a chicken and egg problem. The company itself is orchestrating the app store strategy to grow the user base. But the user base is small to begin with, and it will unattractive for the developers to develop apps. Many of these developers are small companies/ startups, and they would be cautious to devote time and money if the rewards are not forthcoming. So the company must create confidence in the minds of the developers by aggressively marketing the apps store. The developers must be given tools to market their apps.  Also, the company must share the analytics data with the developers about the number of views, downloads, and app content usage statistics.  If there are revenue sharing agreements, then helping the developers grow their sales will also help grow own revenues. 

Backward compatibility. The business rules whether to allow backward compatibility would decide the number of potential customers. Say the product has a 10 million user base, but only 20% of them use the latest version of the software that has the platform architecture. Now the net available customer base for the developers is only 2million and not 10 million. The company would have consciously limited the platform architecture to the latest version in order to create strong incentives for the customers using older versions to upgrade to newer version. But this will be a serious disincentive for the developers, whose market has now been limited to only 20% of the customer base. 

Ecommerce Imperatives. The enterprise software companies most often sell through a reseller network, and through direct sales. The unit price of the software would be hundreds, or even thousands of dollars. The app store would be a completely new channel of payments system. The company might not have the processes for revenue sharing with small developers or collect micropayments; or perhaps the marketing department might not have expertise in dealing with a large number of small developers, most of whom would have one time relationship. It takes time and coordination work to set up these processes.

Integrating Legacy systems.  It is highly possible that the existing customers would have a subscription account for their software, and perhaps another account to interact in the user forums. An app store account will be a third account, and it will only confuse the customer even more. If nothing else, the app store account must be connected to the subscription account if there are business rules preventing customers with older versions of software from using the app store. Again, this single-sign-on integration could take a lot of time, which must be factored into the overall time plan.

Seamless Offline - Online experience. It would be necessary to design the app store to provide a seamless user experience for user who goes offline while online. The user may never be online while trying to access the app store while working on his software. Or, the user goes offline while browsing the app store. There are many use cases for this scenario. For the in-product app store, when the user is offline, the exception pages, and offline contents in local machine for the app-store must be designed to deliver the best user experience, similar to overall user experience theme for the desktop software.

That said, none of these challenges are beyond the capabilities of the company to solve. If only the product manager is aware of these challenges, he would be able to work his way through to get the app store for enterprise software deliver real value in the targeted time frame.

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Social Referral Traffic - What to measure? Whom to target? What are the qualitative aspects?

The pieces of big puzzle of profitability of any consumer internet company have always been

1. Traffic Generation
2. Conversion
3. Monetization. (in some cases, 2&3 are same)
4. Retention.

But with the advent of social media, social networks, and social sharing tools, a whole new piece of puzzle is emerging : 5. Social Referral.


I had earlier written a post about the benefits of social media optimization here. Your customers and visitors share information about your products and services using the social sharing tools in your website. The ever expanding social networks such as Facebook and Twitter are fundamentally changing the way people discover information. Except for a brief period of last about 30-40 years, people, for times immemorial, were discovering information through word of mouth, and through the trusted sources in their offline social networks. Today, social media sharing is enabling people to hear what their trusted sources from across the world say about the news, products, and services people care about, before making their decisions. Simply put, social networks are slowly restoring the primacy of information discovery through word of mouth (mouse).


A simple diagram below depicts the big picture of traffic generation, referral, retention, and monetization.

Social Referral Traffic.
When your visitor or customer shares information about your website, products or services to his social networks, and generates traffic through such referral links, the traffic is called social referral traffic.


What to measure?

1. How many times information from your site has been shared.
2. Who is sharing the information?
3. Who is generating new social referral traffic?
4. No. of new visitors referred per social sharing link.
5. No. of conversions per No. of new visitors referred through a social sharing link.
6. Retention rate per unit number of converted referral traffic customers per social sharing link.

(there are certainly more parameters to measure than these six)

Whom to target? 
From the above analysis, it would be possible to identify the group of users generating the most valuable social referral traffic to your website. It will be useful to understand what percentage of your visitors are generating what percentage of your referral traffic from their social networks. Often, less than 3% of your visitors/customers would generate more than 50% of your referral traffic, and even a less percentage would generate new customers.  Most likely, these 3% visitors/customers are social media influencers of some significance, among their networks. Simply put, their followers trust their referrals, and that is why their followers follow their referrals to your website.

Redefine your Net Life Time Value parameters. It is very important to  identify who these top 3% customers are, and how valuable is their referral traffic. Assuming that all your current customers have same/similar Average Revenue per User (ARPU), these top 3% customers unquestionably have a higher net life time value than other 97% percent of your customers because they generate referral traffic, who then generate further profit. Therefore, it is important to identify this top 3%, proactively woo them with offers, and promotions to retain them, and give them incentives to share information more often to their social networks.

Qualitative Aspects of Social Referrals.
Web analytics is quantitative and often does not identify the qualitative aspects completely. For example, let us assume that two of your referring customers A and B, generate same amount of referral traffic AX and BY, and both AX and BY same amount of revenues and net profits. Your web analytics results would treat A and B as equally valuable referring customers, and your marketing department might approach both A and B with equal promotion offers. However, AX, the referral customers generated by A, is qualitatively poor: AX consume your customer care services much more than BY, the referral  customers generated by B, or may be, AX has  signification number of returns and repurchases than BY. In that case, you might want to think about which referring customer to keep, and which one to stop targeting. In the long run, quality of customers referred matter beyond profit numbers.

Today, as social networks expand exponentially, and as we rapidly perfect the social media monitoring tools, measuring, and understanding social referral traffic, and targeting social media influencers will be key to running a successful consumer internet business. 

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Opportunity Assessment for New Product Development

Opportunity assessment is one of the primary steps for New Product Development. A  suggested set of basic questions that a product manager must find answer to, in order to accurately assess the opportunity for a product is as under:-

1. What’s the value proposition of your product? What problem is your product solving? Or, Will your product create new market?
2. What is the Market size? In terms of volume, revenue, and share? Is the intended product valuable to your business?
3. Who are your competitors? What are their product offerings?
4. What is the pain point that customers have in the current product offerings available to them in the market?
5. In what ways your product will be differentiated? Will the customers find utility for your product? Will our customers find your product usable? Most importantly, will the customers actually buy your product? In other words, is their problem grave enough that they are willing to pay you to solve the problem through your product offering?
6. Why us? Do you have the technical expertise to build the product? If not, is it feasible to acquire the capability and technical expertise to build the product in the given time frame?
7. Why not your competitors? If they have not done it, then are your competitors simply too dumb, or is there a strong reason for them not having explored or for having failed in their endeavors to build one?
8. Why now?
9. What is the NPV/ROI metrics? What is the ROI for your customer?
10. What is the go-to-market strategy?
11. What are the critical factors for success? What are the risks involved?

Enterprise software products: What is the ROI for your customers? Does your product help your customers improve their competitive advantage over their customers?

Good product managers will know that customers buy a product to satisfy a particular need, and that customers are more interested in the solutions products bring, rather than the product itself. Enterprise customers often buy enterprise software or cloud solutions to improve in at least one of the three areas – product differentiation, operational efficiency, or customer intimacy – of their business operations. As they do for any investment, enterprise customers calculate their ROI for the investment they make in your products to the best extent possible. So a product manager of enterprise software or solutions product must place the customer at the core of any opportunity assessment study, or product design process. Wherever possible, a product manager in coordination with the product marketing team must closely understand his customer’s real need and design a product that will give a competitive advantage for his customers over their competitors. If the product offering is for a broad based set of customers, then the product manager must research to understand individual market segments, and how the product will actually give value for money to your customers, and help sharpen their competitive advantage to your customers over their competitors.

Adopting a customer and market driven approach to develop a new product is more likely to succeed than trying force a new product you have built using your great new technology, to a customer that has no utility or use for that product. That said, It would also serve well to be cautious of the Like-But-Wont-Buy trap that Gopal Shenoy brings out here in his “Like/Buy” matrix.

In almost all cases, the success of a product is determined by how well the product satisfies the customer and the market needs. And understanding the customer, and designing the right product by placing the customer at the core of the opportunity assessment study and product design process, is key for the success of the product, the business unit, and the company.

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