Just fantasizing about technology a bit today… Consider the following trends:

1.) The internet is coming to our TV’s.

2.) TV’s are getting 3-dimensional displays.

3.) Gesture control technology is becoming a useful interface.

Put those three together and what becomes possible? Well, lots of things, but one of them would be an entirely new e-commerce experience.

Picture mom shopping for shoes online.  She is sitting on the couch in front of your 65″ television looking at the latest shoe styles.  Except, the shoes are not just flat images.  They are visually popping out of the screen thanks to 3D imaging.  Ands mom doesn’t need a mouse or a remote or a keyboard.  With gesture controls, she is rotating the shoes so that she can see them from different angles and really get a feel for them, or waving past them to get to the next product, or adding them to her shopping cart for purchase…

Wild.

It’s probably a bit early to start building this sort of thing now, but…

In one example:

“Members-only site Beyond the Rack offered a pair of suede Adalene pumps from the two-year-old designer label Pour La Victoire for $129, posting a “compare it” price of $275 for the shoes. Gap Inc.’s online retailer Piperlime simultaneously offered the same pumps for $149.99, but with a suggested retail price of $220.”

If you pay attention to what’s going on here you might get the feeling that for any mainstream fashion product: Today’s suggested retail prices are total bullshit. You begin to wonder if anybody is actually buying those shoes for $220 or $275.

When I see an offer like “40% off”, I like to think that through my own connections, or dumb luck of being in the right place at the right time, or willingness to buy last seasons merchandise, I am somehow capturing more value for my money.

I think this feeling comes from my past experiences.  You used to have to be something of an insider to find the “sample sales” that would pop up around Manhattan.  I remember (living in San Diego) you had to drive half-way to Palm Springs to get to the designer outlets.  If major discounting ever occurred in large city stores (or online) the inventory and size selection would be minimal.  In one way or another, getting a “deal” usually meant some extra inconvenience.

But with the recession and the online outlet stores, “deals” are becoming increasingly accessible.  Sample shopping sites such as Gilt, Haute Look, Groupon and Woot seem unstoppable.

As these deal sites scale, going from early adopters to mainstream markets, they must inevitably become less exclusive (right?).  Their objective must be to make their deals more accessible to more people – to remove the inconvenience factor.

Meanwhile the internet makes information move faster and consumers smarter.  Price checking is getting easier.

“Members only” loses meaning when everyone is a member.  “Today only” loses meaning when those days become every day.  At what point does a deal stop being a deal?

(Theoretically) when this is realized, the startup can quickly scale by “buying” more customers, making a profit on each one.

Proving that you’ve achieved this (or creating a compelling story that you will be able to achieve this) significantly increases your valuation, increases your revenues, and increases the number of  VC’s that want to take you out to lunch.

There are probably great books on this topic that I have not read, but from my own experience, this is how I see it.  (I appreciate comments to clarify/correct my approach.)  The simple way to calculate customer acquisition cost is:

C_acq = A/( T_total*R_conv)

C_acq = Customer Acquisition Cost. How much you spend to get a new customer.

A = Advertising budget.  How much you spend to drive traffic to your site to get new customers

R_conv = Conversion rate from traffic to customers. The percentage of your site’s visitors that you are able to monetize.

T_total = Total traffic to your site in some unit of time.  Let’s say, per month.

Good so far, but we should also consider that a site typically gets traffic from a variety of sources each having different costs and effects. For this post, I want to focus on how viral sharing affects customer acquisition cost, so I’ll introduce the following variables.

T_base= Traffic that comes to your site from organic search, press coverage, bloggers, gift guides, product directories or really any other links to your site that you don’t need to pay for.

T_paid= Traffic that comes to your site as a direct result of your advertising.

C_pc= The effective cost per click you spend by advertising.  Advertising may be purchased as CPM, but you can still calculate the cost per click by dividing the amount you spent by the number of clicks that resulted.

T_wom= Traffic to your site as a result of ordinary users sharing it with their friends (word of mouth).  They find it interesting and email a link to someone, post it on their Facebook or Twitter profiles or mention it to someone at a bar.

Based on these new variables, define the following:

T_paid = A/C_pc

T_total = T_base+T_paid+T_wom

Furthermore, seeking a better understanding of of T_wom, we would see that it is probably a function of how many visitors our site has and some viral coefficient “V”

V = Viral coefficient.  Practically speaking this is the average number of additional visitors that each visitor recruits.

T_wom= (T_base+T_paid)*V

Solving for Total Traffic, we get:

T_total = (T_base+T_paid)(1+ V)

Thus, solving for Customer Acquisition Cost, we could say:

C_acq= A/(R_conv* (T_base+T_paid)(1+ V))

Identically:

C_acq= (A/(R_conv* (T_base+T_paid)))*(1/(1+ V))

Now – that was a lot of math – but if you think about this equation a little bit, you can see the huge value that customers word of mouth brings to the table.

Suppose you have a viral coefficient of 1, meaning each site visitor recruits just one additional visitor. The result is that you cut your customer acquisition cost in half.

IN HALF!

(*Note1: This is even before we take into account the second order effects of referred people referring even more people.  A viral coefficient greater than 1 would theoretically result in a naturally exponential growth – so called “viral growth”.  Depending on the time delay between referrals, and your target growth rate, this could potentially drive your customer acquisition cost to zero. )

(*Note2: You might point out that this equation calculates “average” customer acquisition cost, rather than your marginal customer acquisition cost.  This is correct, as you scale up advertising, T_base+T_paid will approach T_paid, so you could calculate marginal costs this way to be more precise.)

(*Note3: Please excuse the implication that R_conv is a constant.  I realize that it tends to vary widely depending on the nature of the traffic and corresponding intent.  However, for this exercise let’s assume a general, mass-market conversion rate.)

It can come down to pennies per customer, but for many startups this can be the difference between having an exciting, scalable startup and a failure.

Just 5 years ago (ok maybe 10), Word of Mouth for most people meant sending an email or actually mentioning something face to face.  A good analytical marketing person might have even ignored the T_wom component because it was so small – better to just consider it a nice little bonus.

However, things are changing.  With the growing influence of social networks, this viral coefficient is becoming increasingly significant.  It’s increasingly convenient to post things on Facebook and the average person’s number of friends and followers is also growing.  We may be more choosy with what we share to our friends, but with more followers, an AVERAGE person’s post on Facebook or Twitter can now generate your site hundreds of additional visitors.

Two recent startups that have shown explosive growth: Groupon and Zynga are great examples.  While their ability to monetize customers is itself very awesome, without a doubt they are relying on fairly large viral coefficients to keep their average customer acquisition costs low.  If you’ve played with their products, you’ll see that they aggressively push you to refer additional people to their services.

Of course, we cannot forget about SEO, press, usability design, conversion funnels and optimizing ad campaigns, but I predict that increasingly this viral coefficient will be the metric that startups rely on to justify the economics of their businesses.

I generally agree with the direction that Chris Anderson sees things going.  The marginal cost of a web service is getting smaller.  The freemium business model makes sense and there are several successful examples of this.  And yes, without a doubt, consumers have become accustomed to not paying for web services.

But there’s something missing to this story that I just have to highlight (or someone please correct me):

Most of today’s free web services are subsidized -not by a few paying customers, but- by optimistic (delusional?) venture capital and corporate investors.  

It seems that in just the last few years, there has been hundreds of millions (billions?) of dollars invested in web services that either have no business model or planned to rely on advertising alone.

With millions of dollars, startups like Twitter, Pandora, Digg and Facebook have created some really compelling products that have attracted millions of users.  These are the darlings of the internet that experts point to as examples of success.

But, NONE of them are profitable today.  Fueled by the optimism of their investors and the bubble network of bloggers/users/experts, these companies are able to continue raising money to support their free services.  As subsidized startup competes against subsidized startup, prices continue to fall, advertising inventory continues to increase, millions of dollars of investment are lost and consumer expectations for “free” increase.

At some point, internet startups are going to be forced to stand on their own feet.  When that time comes they will have to scale down their teams and optimize their pricing.  I wonder how many are going to realize that they’ve spent $50M building a company that can’t generate more than $1M/year in profit, or $5M building a company that can barely support a single founder?

Free is just NOT a sustainable business model.

The Paradox of Choice by Barry Schwartz

is a worthwhile, albeit slightly depressing book.  Schwartz does an excellent job of demonstrating that today we (especially Americans) have infinite choices before us.  We can choose from a variety of career paths, we can live in different cities, we can eat various foods, we can buy different products, we can date different people… on and on, you get the idea.  Schwartz also presents various statistics (suicide rates, diagnosed depressions, medications) suggesting that, we are (in general) less happy.  He suggests causation with the following rationale:

1. Making good choices is just plain hard (imperfect, constantly changing information).
2. We spend so much time researching choices that we’re too busy for our families and things that matter.
3. We are constantly stressed out about choices because we don’t want to miss opportunities (we want them all).
4. After making a choice we fantasize about how much better life would have been if we had chosen the alternative (regret).
5. After doing all the research to select the best option our expectations of the result become so high that reality can not deliver (disappointment).
6. Once we’ve made our choice, we constantly compare our choices to others and try to analyze who made a better choice.

Throughout the book is the theme that there are two types of people: maximizers and satisfiers.

Maximizers always try to make the “best” decisions and satisficers try to make decisions that are “good enough”. The ironic result is that maximizers tend to be more successful and satisficers tend to be more happy.

Most of us are somewhere in the middle, or behave as one or the other depending on the choice being considered.  I think the book is a worthwhile read for this point.  You might find some personal insight into your own quality of life!

If more choice = less happiness and mass-customization = lots more choice, it follows logically that mass-customization = lots less happiness.

And there are plenty of failed mass-customization efforts to cite.  Just see Proctor and Gamble’s “Reflect”, Cannondale, or Levi’s Personal Pair.  However, a little research will show is that many of these “failures” or “discontinuations” weren’t because consumers didn’t like the choice.  For example, Levi’s ended the Personal Pair effort because it caused sales channel conflicts – other efforts had trouble manufacturing custom products and staying competitive.

Points from PoC that support the case for mass-customization

We are naturally drawn to choice

The fact is, most of us want more choices – even if they make us less happy.  As Schwartz says, “65% of people not diagnosed with cancer say they would want to choose the treatment if they were diagnosed”.  We crave freedom and individuality whether it is good for us or not.  Mass-customization offerings are thus a natural draw to potential customers and should be able to easily get customer attention.

Whether we like it or not, we are already faced with infinite choices

Suppose you are an ecommerce company selling coffee makers.  According to Schwartz’s advice, offering fewer coffee makers on your website would increase your sales.  This might have worked 10 years ago in department stores, but today, when customers are looking at your coffee maker website, you can bet they have multiple browser tabs open to your competitors websites as well.  Putting less products on your digital store shelves only decreases the likelihood you will be offering what the customer is looking for (for more analysis on this point refer to Chris Anderson’s “Long Tail” discussion of Amazon.com).

PoC ideas to improve a mass-customization strategy

Provide salient information that help users make the right choices

The flip side of the above cancer treatment statistic is that “88% of people actually diagnosed with cancer did not want to choose their treatment”.  The unhappiness of choice comes when the stakes are high and the correct choice isn’t clear.  To help mitigate this, provide either a live person or a digital wizard to (1) provide an “experts” recommendation for the customers needs and (2) ease the customer’s mind that the stakes are not as high as they think (which is true for most buying choices).  When personal attention is not feasible (most ecommerce), it is critical to integrate easy to navigate and relevant information.   User interface designs such as Zafu that make recommendations after a customer answers several intuitive questions seem to work especially well.  MyShape, HisCatalog and Yelp also offer user interfaces that work well for helping customers make buying decisions. These strategies should be applied to mass-customization offerings as well.

Focus on offerings that provide real utility – not just aesthetics

Frank Piller once mentioned that this is the key success driver in mass-customization companies.   The paradox of choice psychology provides a good explanation why.  If your mass customization provides a product with a superior fit (such as custom orthopedic shoes), the choice becomes easier to make because you just choose “perfect fit”.  Real utility implies that there is a correct answer, not a subjective opinion.  It might be complicated and it might require domain expertise or a better understanding of your personal situation, but with the right information it will be an easy choice.  Conversely, aesthetic choices can be unclear.  For example, choosing between 100 shades of pink could be a subjective choice – thus a very hard decision to make.

If you find the topic interesting (and don’t mind a $2000 conference price tag) come to the First Annual MIT Smart Customization Seminar November 10th and 11th, where I will be discussing my mass-customization start up Proper Cloth.

What they fail to think through is  the cost of getting those potential customers to their website.  (To give credit, I was first introduced to this way of thinking about internet businesses by Nick Beim while I was studying at MIT)   Customers don’t just show up by themselves, and even if you’re really popular, telling your friends won’t bring you the thousands of customers you probably need.

Customer Acquisition Cost is the amount of money you have to spend to get someone to take the action on your website that gets you paid.   You can acquire customers through many different marketing strategies, some may be better suited to your particular niche.  Some people will pass out flyers around their school, or send emails to their colleagues.  Others may try to engineer their website to be “viral“, or to stimulate “word of mouth marketing“.

I like all these strategies, but I would hesitate to base a complete business plan on any of them.  They are not always predictable, nor are they necessarily scalable to a large audience.  Don’t ignore them, but consider them as a bonus: if you get them right they will only add to your success.

Perhaps unsurprisingly, I think pay-per-click advertising is where the most analysis should be placed. Pay-per-click advertising is both predictable (you can calculate how much it will cost to get a potential customer to your site), and it is scalable (you can choose to bring 10, 100, or even 1000 potential customers to your site per day).  Great places to setup ppc advertising are Google Adwords and Yahoo Search Marketing.

Knowing how much it costs to get a potential customer to your website is the first step.  The next step is to estimate what percentage of those potential customers you can turn into actual customers – also known as the conversion rate.  This number is hard to predict, but here are some things to think about:

1. How many competitors do you have?  – If you are the only one offering your product, you could expect a higher conversion rate (this never happens though).
2. How much better is your offering versus your competitors?  – It’s likely that the potential customer will browse through your site as well as a few of your competitor’s sites.  If your product is cheaper or more featured this could boost your conversion rate.
3. How easy is it for someone to understand your website quickly? -Your potential customers generally have short attention spans.  If you have a great offering but the site is confusing, your potential customers may never appreciate what you have to offer.
4. How closely aligned is your product with what the customer was searching for?  If you are building a social network for plumbers, and you buy the keyword “social network”, it’s likely that a lot of the people that come to your site are looking for something else, thus your conversion rate could be very low.
5. Analysis on your competitors is also a good idea.
6. Try to run some low cost experiments to test your theory.

Once you’ve convinced yourself that you have a good idea what your conversion rate will be, the rest is easy: Simply divide your cost of getting a potential customer to your website by the conversion rate, and you have your estimated customer acquisition cost.

From here it is simple- if you make more money per customer than it costs to get that customer (and there are lots of potential customers) you are in business! Best of luck!

Cognitive styles can be measured across several different dimensions. Some examples include: impulsive (makes decisions quickly) vs. deliberative (explores options in depth before making a decision), visual (prefers images) vs. verbal (prefers text and numbers), or analytic (wants all details) vs. holistic (just the bottom line).

As we are better able to determine what sort of customer is viewing an advertisement, we will not only be able to show them an ad of something they may be interested in (geographic, demographic, contextual), but we can present the advertisement in a way they are most receptive to it.

For example, if it is determined that a customer has a verbal cognitive style, they will be more interested in an advertisement listing impressive specifications of a product than they would be to a picture of the product. This will ultimately lead to higher click through rates.

Additionally, we’ll see these ad’s take users to the advertisers website in more intelligent ways. For example, take an impulsive buyer to a purchase page, and a deliberate buyer to a product details page. This will ultimately lead to higher conversion rates.

Outsourcing in Brick and Mortar Business

When a new product first becomes available its performance does not usually fulfill the needs of its customers.  For example, when the first personal computer became available, it was slow, lacked memory, and had a poor user interface.  In short, it was not good-enough for most users.  Any improvement in performance was highly valued.  When performance is so critical, Christensen demonstrates that proprietary, interdependent system architectures dominate.  However, as these proprietary systems move from being not-good-enough, to good-enough, to more-than-good-enough, advantages begin to shift to systems with modular, open architectures.

Personal computers in the 1980’s were produced by vertically integrated companies like IBM, Digital Equipment and Apple, but during the 1990’s, more modular architectures began to emerge.  This shift was accompanied by a shift in the industry from vertically integrated firms to horizontally integrated firms.  IBM, the original market leader in personal computers supported this shift as it outsourced component development to emerging companies.

Particularly when a company is managed to optimize short-term financial performance, outsourcing certain functions makes a lot of sense.  Outsourcing decreases the company’s asset base (improving ROA) and lets management focus on only the most profitable operations.  In the PC industry, operating systems were sourced from Microsoft, micro-processors from Intel and hard-discs from Seagate.  This shift to a modular architecture and horizontally alligned industry allowed narrow expertise to be developed for each component, and the overall performance of the PC to continue to improve, but it also caused market power to shift from the systems integrator to the component manufacturer.  As the performance of the individual components begins to define the performance of the overall product, the system integrator became commoditized by the component manufacturer.  IBM suddenly found itself competing with HP, Dell, and Compaq in the systems integrator role and unable to capture much value.

It’s not always clear, when something is outsourced, which side of the equation will end up becoming commoditized.  Often this is determined by the strength of the relationship between the systems integrator and the end customer.  When the relationship is strong and end customers have few alternatives, or high switching costs, the suppliers become commoditized.  However, if relationships between the systems integrator and customer are weak, it is likely that the systems integrator will either completely liquidate their company through outsourcing, or become a commodity service themselves.

Outsourcing in Consumer Internet Web Service

As consumer internet web services improve in performance, and become good-enough for their users, will a similar outsourcing phenomenon occur?  In many cases, it seems that the leading web services are wise to this game and will try to stay vertically integrated as long as possible.  However, some companies seem more open to outsourcing certain functions and may provide an opportunity for a new company to disrupt them.

Google

In the initial stock offering, Google boldly declared that it would do things differently and not make decisions for short term financial benefit.  Its founder’s unique, powerful stock privileges, and Google’s outstanding financial performance to date have given it the flexibility to focus on a long term strategy.  As a result, Google keeps almost all of its functions in house.  It’s interesting to consider that Google takes a very broad view in what it considers its “core-competency”.  Everything from mapping software to electronic mail to mobile applications to advertising networks, even huge server farm management are developed and managed in-house.

Yahoo

Yahoo, while similar to Google in its product offerings, does seems in jeopardy of outsourcing important functions.  With weak financial performance the last few years and recent pressure by Microsoft to justify its share price, Yahoo is feeling the pressure to outsource certain functions to boost profitability.  A recent Wall Street Journal article “slams Jerry Yang’s strategy to remake Yahoo into the front page of the Internet. The column calls for activist investors to shake up discredited management, outsource search, and spin off Asian investments in Alibaba and Yahoo Japan”.  Thus, it seems that short-term financial pressure could force Yahoo to outsource a critical part of its offering, beginning the outsourcing business liquidation evolution described by Christensen.

Facebook

Facebook showed huge confidence in its customer relationships when it announced the Facebook Platform.  By allowing third parties to develop and profit from applications, Facebook has essentially outsourced its application development and several successful companies specialized in producing Facebook applications have emerged including Slide, Rockyou, and Fotoflexer.  At the time of the announcement it seemed these companies would only be able to prosper with the consent of Facebook.  Facebook was the destination that consumers went to, and had tight control over the environment.  Thus, Facebook was in a safe position to capture most of the value created by third party applications.  Thousands of web developers began to compete to develop Facebook applications to try and profit from this new opportunity.  As a result, these applications themselves became commoditized, with several different applications having essentially the same function.

In response to this announcement, Google organized the commitment of several other social networks, and created the Open Social Platform.  Open Social provides a standardized interface between social network and application.  With this new development, power has shifted from the social network to the application developers.  Application developers now only need to write their application once, and can offer it on several different social networks.  Whereas at first it seemed that there would be many applications competing for attention on one social network, it is now possible that many social networks will be competing to get the best applications on their platform.  If the outsourcing trend continues and a social networks performance becomes defined by the performance of its third party applications, value capture will begin to shift from the social networks (Facebook and MySpace) to social network application companies such as Slide and Rockyou.

Consider air travel.  Eight years ago, when I wanted to fly from San Diego to Boston, I was pretty internet savvy, and would go online to buy my ticket.  The online travel agencies (Orbitz, Travelocity, etc.) were an option, but they were not perfect for two reasons.  First of all, there was a lack of transparency in the pricing.  If you booked an American flight through Orbitz it could cost more than if you booked it through American Airlines website directly.  Second of all, there were a few airlines that were not included in the search -most notably Jet Blue, that had reasonable prices and (at the time) great service.

As a result, when I went shopping for a plane ticket, brand mattered a lot.  It was the brands that I could remember off the top of my head that I was drawn to first.

I’d check American Airlines website, check Jet Blue’s website, and then make a decision.

Enter Kayak.  Kayak was the first vertical search engine for flights that I became aware of.  It covered all the different carriers, and its pricing was transparent because you purchased your ticket from the airline directly.  My new process for buying a ticket is simple.  Go to Kayak, enter the desired dates of travel, and see what the options are.  Being price conscious, I often just go for the best deal.  If two flights are virtually the same in terms of travel time and cost brand might by the tie-breaker, but generally speaking I don’t consider brand as much.  Kayak organizes all the information in such a comparable way that i can pick the product best suited to my needs.

Fine.  What’s so interesting about this?  Analogous to Orbitz are sites like Zappos and Endless, and analogous to Kayak are sites like Shopping and Pricegrabber.  Shopping.com and Pricegrabber are true vertical product search engines that send a shopper to the suppliers website to make a purchase, providing pricing transparency, while Zappos and Endless sell you the product directly.

I predict that Product Search Engines will improve over the next few years.  They will cover a broader range of sources and they will present the specification of their products in improved ways such that it is easy to compare products and make the best purchase decision.

For example, in the future, if someone is searching for a leather bag, they will be able to go to a Product Search Engine focused on bags, and know with confidence that 99% of bags for sale on the internet are included in their search results.  Furthermore, an improved interface will allow a customer to filter based on the specification of bags.  If you only want black, you can filter out everything else.  If you want a briefcase style, you can look only at those as well.  Only gold plated zippers, no problem.  Vintage finish to the leather, done.  In the end, we will have narrowed our options to a few products that meet our exact criteria, and ultimately be able to make an informed buying decision.  As before, if you end up with two bags that are equal in every way, with the exception that one has a brand you like and the other does not, the brand may still win out.  The brand is ultimately less important though, because you were not looking at the product because of its brand, you were looking at it because it met your product criteria

This will be a major shift from how things are today.  If someone wants a product today, they go directly to the brick and mortar store of the brand they know for producing that product.  In the store, they are captive to see only products from that brand.  For the online shoppers, they do effectively the same thing, going directly to the websites of the brands they know.

Bottom line: I’m excited about this, because I think it will open the door for new product companies without a lot of brand cache to compete against the major brands simply by offering quality products that meet consumers expectations and needs for a reasonable price.

New market strategies for disruption are different than low-end disruptive strategies.  Instead of simply entering the market with a lower cost, lower performance product, new market strategies involve “coming off the backplane” into a new market.
An example of a new market disruptive innovation is Sony’s portable transistor radio.  When originally released, the transistor radios sound quality was completely inferior to that of existing radios on the market.  However, existing radios were so large they were often built into furniture and thus not remotely portable, and prohibitively expensive for most customers.  When Sony’s low cost portable music player came on the market, it was not really a direct competitor to the existing radio businesses.  If someone was in the market for a high end radio, they would balk at the poor sound quality of the transistor radio.  Likewise, most customers interested in the transistor radio could never have afforded an expensive home radio.  By positioning the product for a new market, Sony was (according to  Christensen) “competing against non-consumption”.  Customers were either going to get a Sony radio, or not get anything at all.

New Market Strategies to Disrupt a Web-Service

In most of the examples Christensen describes, new market disruptive strategies seem similar to low-end disruptive strategies because price is the factor that separates different markets.  In free consumer internet services, markets are not defined by pricing categories because the prices are already zero, a price that anyone can afford.  However, there are other factors that separate markets in consumer internet and thus still ways to position a service such that it “competes against non-consumption”.

Foreign Language Applications

One proven strategy is to offer a consumer internet service in a certain foreign language.  Many consumer internet sites target the US market and ignore the rest of the world.  If you don’t speak English, you can’t use these services.

Xiaonei Disrupting Facebook

An example of a company employing this strategy is Xiaonei, dubbed by many as the “Chinese Facebook Clone”.  In April 2008, Xiaonei reportedly raised $430 million in venture capital, and had built a community of over 8.8 million active users.  As in all disruptive innovations, it currently seems that the two social networks do not compete with each other.  As globalization continues it’s possible these companies will become direct competitors.  If Xiaonei is able to focus on the unique needs of their Chinese customer base and to develop real innovations in their own right rather than just mimicking what Facebook does, it may be able to build enough momentum to compete with and even disrupt Facebook in the English market.

Baidu Disrupting Google

Similarly, Baidu is a search engine that targets the Chinese market.  The interface, while resembling Google’s search page, is in Chinese, but the differences go much deeper.  For a search engine to adequately address the Chinese market, it needs to be able to index and search through pages that use Chinese characters.  This provides unique challenges that companies focused on the US market are not well positioned to address.  In 2006, Baidu was “the first choice of 62 percent of Chinese users, up 15 points over 2005”, according to a study released in September by the China Internet Network Information Center.  As globalization continues, Baidu may one day expand into offering a US search engine that can disrupt Google at home in the US.

Provide Mobile Access

Another new-market disruptive strategy is to initially focus on mobile.  Around the world, many people have access to a mobile phone, but no access to a computer.  Mobile services are generally lower performing products than their personal computer browser counterparts limited by the smaller screen, user interface and slower data rates.  Some mobile services work by simply sending text messages to the service, which responds with a text message, others work in the mobile phones browser, and others work as a Java application installed on the phone.  Mobile services with value propositions similar to desktop browser internet applications could provide a foothold to disrupt the leading internet application.  Some companies that seem to be employing this strategy include 4Info and Babajob.

4Info Disrupting Google

4Info was one of the early local/mobile search companies that functioned via text messages.  In order to submit a search a user only has to send a text message to short code 44636 (4info), of what they want to search.  Sending the message “Starbucks Boston” will return the address and phone numbers of Starbucks locations in Boston.  Sending “SWA 436” will return the details of Southwest Airlines flight 436.  By using text messages as the interface to the service, 4info is available to anyone with a text message capable mobile phone.  People without a broadband internet connection on their PC are able to use the service.  Unfortunately for 4Info the leading search engines have recognized this service as a potential disruption, and launched similar services, making it seem unlikely that 4Info will be able to disrupt Google or Yahoo.

Babajob Disrupting Monster

Another startup that is using mobile access as a new-market disruptive strategy is the India based startup Babajob.com.  Babajob is a service to connect employees with employers.  The business takes advantage of the fact that although most workers in India do not have personal computers with internet access, they have text message capable mobile phones.  Once signed up, job seekers get text message notifications of job opportunities they might be interested in, and can respond with their availability.  As the Indian job market grows and more Indians begin to use personal computers with internet connections, Babajob may be able to move up market and find itself in a position as the Monster.com of India, and a disruptor of the US market leader.