Products function in an extremely competitive landscape vying for every impression it can get among the millions of potential customers available online. Getting your startup visible or discoverable is one thing, getting them to convert on your website and retain them is an even tougher task with the plethora of services and products that the consumer is forced upon. This is why it becomes so very important for products to understand each and every activity of the user right from the first time a potential customer/ user discovers their service or product on the web to the point they convert and start coming back to their website.

There are plenty of data that’s available to internet products these days and a vast variety of analytic tools to analyze them as well. A few years back, one would have managed analytics and data tracking using just a Visitor analytics tool like Google Analytics, but that is no more the case now. With growing competition, you have far less room to fail. Based on your website and your requirements you can choose from the various Analytic Tools that’s available to you. More often than not, you would need to have a combination of these tools below to better understand user behavior. The below chart gives you the various classes of Analytic tools and their strength in measuring various parameters:

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Source: www.moz.com

It is crucial for a marketer to appreciate the insights data can provide on user behavior and take necessary actions to correct and optimize wherever required. It is also crucial for a marketer to measure the right data and understand it’s essence for better improvement of the customer lifecycle on their website.

In my previous post, we had discussed the importance of measuring the right macro metrics. For understanding and validating Product/ Market fit, one needs to measure Activation and Retention. However to completely understand the lifecycle of the Customer one needs to also measure the other three elements: Acquisition, Revenue and Referral.

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Funnels are a great way to understand user behavior on your website. They are visual, simple and map well to most of the events related to measuring the macro metrics. But Funnels alone have their limitations as well. Imagine if you wanted to measure the impact of repeated product iterations you have pushed out to during a period on the revenue. It becomes extremely difficult to track the same using only funnel, one because the impact on revenue is a long term thing and also because you would need to segment users who signed up during the period when each iteration was rolled out to effectively understand the impact on revenue for the set of users who started off with a particular variation of the product. This is where cohorts play an important part. Think, I would cover cohorts in the next post and explain in detail the methodology to track metrics like retention, revenue, impact of feature iterations on both and more. In this post, we will focus on using Google Analytics in tracking the channels resulting in any of your user interacting with your brand, converting on your product/ service and also on coming back to your product/ service. The Digital Marketing Funnel as represented in the figure earlier can be broken down in to 3 components:

  • TOF – Top of Funnel
  • MOF – Middle of Funnel
  • BOF – Bottom of Funnel

Top of Funnel:

Top of the funnel represents the first interaction a user has with your brand/ product. There are plenty of channels on which the interaction would happen and one would need to optimize for each of the channels the interaction happens on. The best solution is to always focus on at max two of the channels where the interactions seem to be most effective. With the new Universal Google Analytics Tool, you can get the channel details at Acquisition » All Traffic.

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The above table gives you a good understanding of all the various channels that drive traffic on to your platform. You can export the data to an excel sheet and then use a pivot table to understand what medium acts as the best option to drive first time traffic so that you can focus and optimize for that channel/ medium.

You can drill down further to understand the best referral sources through Acquisition » All Referrals

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Determining which sites have referred the best traffic to your website is important as it enables you to focus on those channels. You can focus on important parameters like Bounce Rate and Time Spent on site to understand the engagement of the users coming from various channels. Not only that, you can also identify websites that are similar to the ones driving traffic on to your website by doing a search on Google [ Use the search query related:”site name”]or on Similar Web to try and leverage on to the similar audience on those sites to generate traffic. For eg: If weheartit.com is a major referrer to your site, then doing a search for related websites on google gives you these results:

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The above search result gives you a healthy number of similar sites with similar target audience who would be interested in your site. Refining and cross-posting your contents across these websites can also help you in getting additional traffic. You can even automate a few of these by using a service like IFTTT where you create recipes for simultaneously posting on a number of these platforms.

Remember, it’s always a good practice to tag the various URLs you use to drive traffic from various campaigns on referring sites. You can use the standard URL builder which google provides to generate tags.

By generating campaign URLs, you can identify the source of referrals to your website, whether visitors found the link from within a newsletter, social media post or other marketing campaigns. By naming the three main campaign tagging elements:  source, medium and campaign, Google Analytics will display information about where the referral originated. Simply complete the tool’s three-step form.

Here are just a few examples of valuable KPI data points you might consider tracking as part of acquisition:

  • Organic Search (SEO)
  • Paid Search Marketing (SEM)
  • Social Campaigns
  • Banner Campaigns
  • Links from External Sites
  • Links from Online Videos
  • Email Recipients
  • RSS Subscribers

Another important parameter which you would want to track is the landing page and how you can optimize them for better conversions. Google analytics helps you identify the most important landing pages on your site and the user flow thereafter. This would give you a better understanding on which pages are performing badly and helps you understand what you can do to further improve user interaction on those pages. [Behavior » Site Content » Landing Pages or Content Drill Down ]

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On Improving weak landing pages:

  • Optimize the content to make it relevant if it’s outdated.
  • If it’s your main landing page, change the message or positioning if required. Use the heatmap tool to better understand the user interaction on the pages and optimize your page accordingly.
  • Make the content more comprehensive so that more people will find it interesting and informative.
  • Build more relevant internal links to the weaker pages to give them more link juice.
  • You can prompt the user to sign-up for email newsletters or at least try and convert them on any of your micro-conversions before the user leaves.

Middle of Funnel:

Middle of Funnel in the Digital Marketing Funnel is the point where in the user is moving from an initial product or brand interaction to a first sale/ to any major interaction on the platform. You might not be able to get a user to convert during this stage but it’s crucially important for companies to target micro-conversions during this stage.

It’s important to track the sources or channels through which the users come back to your site during this stage and it’s also important to measure the paths taken by the users in completing the micro-conversions or goals set on your page. For understanding user paths, GA has an option called Visitor Flow under Audience that visually represents the user path on the website and the drop-offs at each stage. The Visit Flow Report is a nice and a better representation of the traditional click path report. One can view the visitors moving between nodes. One also has the option to view particular segments of users based on region, campaign, traffic source, country etc and their flow/ browsing pattern on the website.

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You can also create your own funnel for any of the goals you have set using GA to better understand where the users are dropping off. For setting up goals or micro-conversions in your site, you would need to clearly define the business objectives for creating goals (micro-conversions). Few examples of good engagement goals to track:

  • Account signup
  • Email signup
  • RSS subscription
  • Watching video
  • Content interactions (e.g. photo zoom, faceted search attributes, etc.)
  • Product Purchase

The goals would vary based on the type of website you are measuring for. To set up these goals, you can login in to the admin panel of your Google Analytics dashboard and then click on the Goal tab.

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You have different goal types to chose from: Destination, Duration, Pages/ Screens per visit or Event. In case of an E-commerece website for eg, if the marketer needs to track how many users complete the check-out process, then he/ she would have to chose the type of the goal as “Destination” in the first step. In the second step he/ she would have to define the destination page which would complete the goal (Conversions).

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For creating the funnel, you would need to specify each step (page) the user traverses before completing the final goal. The funnel visually represents each stage in the micro-conversion process also specifying the drop-offs at each stage. You can create, based on your requirements, multiple mini-conversions and funnels to better understand user flow during this middle stage of user lifecycle.

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[Fig: A funnel representation of a goal set to White paper Downloads from the start page clearly indicating the conversions and drop-offs at each stage.]

In the middle of the funnel (MOF) for the Digital Marketing Funnel, it’s also important to analyze the most effective and popular channels that bring the user back. For this, GA provides Multi-Channel attribution tools under the “Conversions” section. There are various attribution models one could use. For a full guide refer this. The Linear Attribution Mode, which gives equal weightage to any channel in the funnel irrespective of where it appears,  gives us great insight in to which channel accounts for the most revenue overall. You can use the Model Comparison Tool in GA to find this out:

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For figuring out the most popular channels in the MOF, we would have to do some manipulation using excel to weed out the first and the last interaction channels.

Bottom of the Funnel:

The bottom of the funnel is the last touch before someone buys. These channels are very important as it let’s you identify which channels to focus on to complete conversions. You can find this data in Conversion > Attribution > Model Comparison Tool and select your model as the Last interaction.

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You can use these data on the best channels for driving traffic on to your website to further improve and optimize.

Segmenting:

In addition to standard segments that are available in GA to chose from ( You would have noticed this when we discussed the User Flow path), there are also a wide variety of custom user segmenting options that lets you better understand each set of users. You can create your own segments from the dashboard by clicking on the drop-down next to the All Visits tab that’s present as default. GA with the latest update now has the ability to segment visitors and not just visits, which is something GA lacked compared to tools like Kissmetrics and Mixpanel.

Now click on the Create Segments Icon to define your segments. There are a wide variety of parameters you can use to create segments or else you can use any of your own created events as well to define a segment.

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Refer this post for a great list of custom advanced segments which you can use.

Using segments, you can slice and dice your audience in ways never imagined before. You can create segments based on first purchase value, browser being used, platform being used, device on which the visitor opened the site, purchase value during a period etc. I can very well use this data to do a cohort analysis which is very important at an early stage especially if you are on a lean methodology and constantly iterating, measuring the behavior of the set of users who come in during each of these iterations. Even otherwise, there is tremendous amount of insights analyzing segments will give you.

One of the major challenges for a marketer or an entrepreneur is to get users and grow for an eternity. Paul Graham would tell you that you ain’t doing it right if you are not growing by a minimum of 5-7% Week-on-Week. And there are plenty of channels one could use to grow, be it the Press, Text Ads or Visual Ads, Partnerships. All of these techniques require money to be spent proportionally to the amount of visits/ click throughs or conversions you are going to get. Wouldn’t it be so much better if we could get hundreds of users for an eternity for virtually no marketing spend. This is where the inherent Virality of products help.

 What is Viral growth? Viral growth is nothing but an existing user bringing you new users either through a generic invite sent on any of the platforms the potential user is on or by directly using the product ( sharing a file link on dropbox) or by any means possible. Google with gmail was phenomenally successful in creating a viral growth. Google initially started with a base of 1000 people who were given a limited number of invitations to share with friends/ family. Gmail finally went public in the year 2007 but by April, 2006 Gmail had through viral referrals grown phenomenally to a base of 7.1 million users. Quite incredible. Products like Instagram, Dropbox, Youtube etc grew rapidly to a million users through virality.

As with any product the key to being successful in growing virally is to have a world-class product, a product people would love to use and would love to share with their friends. Word of Mouth is a great, free channel for products to grow. But that’s not the only way to build virality in to your products. Look at products that grew phenomenally and you would understand that they built in and utilized at least one or two incredibly viral features in their products. Let’s examine the various viral features a product could have:

1) Inherent Virality : It’s incredibly difficult to achieve this type of virality in all products. There are certain products and niches where the products are inherently viral like gmail or Whatsapp or facebook. These products thrive on users inviting others users because the user gets no value out of them without his families or friends or someone else. But do understand that the easier you make it for a user to invite his friends or family, the more invitations they send out whereby increasing your virality.

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2) Signature Virality : Remember the messages “sent from my Blackberry” or “Sent from my ipad”? This type of virality encourages people to include the messages as signature because they think it makes them cool. Again, you would need a world class product that people would aspire to use to truly achieve this. Could you imagine someone using the signature “sent from my Nokia?” Kidding. But yeah, the point is to spread the message like Hotmail did with a simple “ Get your free email at Hotmail” signature and grew rapidly from a nominal base to 1 million in 6 months and in the next 5 weeks to 2 million. Remember this was a time when there were only 70 million Internet users and in 18 months they had about 12 million users.

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Paypal with their autolinks on ebay is another great example. It automatically inserted Paypal logo to the bottom of each of the listings of the sellers who used Paypal. This was incredibly successful in making Paypal grow virally.

3) Incentivized Virality: Companies like Fab.com or Dropbox are great examples of this. They incentivized their users to send invitations to their network for either monetary benefits or extra storage space in the case of Dropbox. It worked and people brought in an incredible number of referral traffic. Think of Affiliates as well. They thrive on this. The company grows and sells products by incentivizing the affiliate marketer to sell more or bring him more buyers. Amazon has achieved an incredible amount of success through their affiliate networks.

My facebook feed is filled with shares from this new to be launched service :Trevolta

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Of course one is going to share this with their friends, there is no better thing in this world than travelling around the world on someone else’s money! 🙂

4) Embeddable Virality: The biggest example of this is Youtube. Youtube was not the only video sharing website available during its initial stages but what made Youtube a leader was when they made the videos embeddable. People started embedding Youtube videos on their website and with it Youtube amassed massive views and made itself visible to an incredible number of people. This shifted the balance in youtube’s favor and there was no looking back.

5) Social Virality: In this case, Products depend on Social Network like facebook, twitter, pinterest etc to rapidly spread their base. There is a psychology behind Social virality. The key here is always to give people a set of tools to create something awesome which they would want to flaunt with their social graph. Instagram exploded because they could make photos beautiful and people loved flaunting their good looking self to the world. Services like twitter or Scoop.it grew virally because they allowed people to project a certain persona. Even the content shares that are done on any of these networks is in effect a way for a user to project a certain type of persona. If one could get this aspect right, then the product is a sure shot bet to grow virally. What I like about Twitter or Tumblr is the re-tweet or re-blog option which enables a user to create content effortlessly while actually he or she is curating content. It increases engagement on the platform and also gives a sense of satisfaction to the user that he or she is actually creating content.

I guess it’s easy to understand virality but its difficult building virality in to a product and even more difficult trying to measure it accurately.

For measuring Virality, one needs to understand two components:

  • Viral Coefficient
  • Viral Loop time

Let’s assume the scenario where:

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This implies that each user brings you an additional user within a time frame of 10 days ( the Viral Loop time), which is absolutely incredible if you are able to achieve it! J As we had discussed earlier there are different types of virality and in this case we are assuming a simple scenario where each user is sending out invitations to get their friends in (it could be incentivized or simply because your user loves your product)

Now if we were to look at the growth the product would have by the 20th day:

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Understanding Viral Loop time is important because Virality is inversely related to it. The shorter the Viral loop time, the better virality one would be able to achieve. Imagine if the Viral loop time in the earlier case was 1 day, ie, each user invites a set of users and the new user signs up all in a day’s time. That would make the user acquisition 5 times faster than the earlier scenario and your table would look like this:

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Let us plot a graph to understand our growth curve in the first scenario:

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Assuming a product has a viral coefficient that is equal to or greater than 1, it results in a steep upward growth curve. In reality a product having 1 or a number greater than 1 as its viral coefficient throughout its lifetime is impossible although there might be intervals during which the product shows such a viral coefficient. In reality a viral coefficient of 0.4-0.6 for a product is extremely good. Now let us consider such a scenario where the Viral coefficient is 0.5 assuming the rest of the numbers remain the same from our earlier example.

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And if we were to plot this on a graph, the growth curve would look something like this:

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The growth curve flattens out after a particular interval. It’s important for growth hackers and marketers to understand that in reality for most of the viral product this is how the graph would look like if they only depend on user acquisition through virality. So it’s important to plan out the metrics in such a manner that you constantly boost up user acquisition from other channels as well to have a steep growth curve which a product requires to be successful.  Remember Paul Graham and his number for the ideal growth rate for a startup? Utilize not just the virality of the product but also other channels like Press, Market Places , Creation of Viral Content, Paid Advertising or anything that boosts traffic and discoverability of your product/ service which drives conversions in order to maintain an upward trending growth curve.

Now if I were to simply consider the scenario earlier described with users sending ‘n’ invites and x% converts from them giving us a Viral Coefficient of K=n*x%, then the User Base at any particular point of time would be (considering only viral growth):

User Base (t) = User Base(0) * (K ^ (t/vlt +1) – 1)  /  (K-1)

(where vlt is the Viral loop time)

[Reference: David Skok’s article]

The above is not a comprehensive model as there are various things we have left out which includes:

  • The sending invitations process is always staggered. We have just assumed it to happen in one go. If I were to give an example – Imagine dropbox, you will always end up inviting people in a staggered way as you interact with them and share docs with them. It does not happen in one go. And If I were a user of dropbox and If I were to stop using it all together one fine day, then dropbox loses out on any referral signups from me.
  • The churn your product will have as it affects the above mentioned parameter.
  • We have not considered virality across the many channels and the different forms of virality.
  • We have also not included the saturation of a particular channel. If I were using a platform which has a total base of 10Million as the target base for sending out invitations, once I cover the entire user base I can’t rely on the formula.

The Viral Loop

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The viral loop highlighted in the diagram is what can be called as the single viral loop. It’s important where it’s possible to have a double viral loop to fasten your user acquisition. This is possible especially in case of Social networks. Like we discussed earlier, retention is a key component that defines the Viral Coefficient. An increased retention will result in increased Viral Coefficient and hence a faster user growth. There are simple techniques one could do to improve retention and engagement on the platform. This forms part of the double viral loop. Re-connection always increases engagement and retention and hence it’s important to re-connect people by prompting them as well as by making it easy for them.

For ex on LinkedIn, after we sign up, it prompts us to export contacts from our address books and re-connects us. This removes the friction normally people will have in searching for people and then connecting with them. Also, it helps in retaining dormant users. This is a technique employed by many of the Social networks to bring back dormant users on to the platform. Notifications on follow improves your chances of brining back dormant users.

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This simple step resulted in an increase of 16% in the number of invitations sent. Check the stats below:

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Source: http://www.slideshare.net/joshelman/josh-elman-threegrowthhacksgrowconf81413

Or in case of twitter they take you step by step through the various things one can do on twitter and by it helps you in getting content on your feed and making you follow a few popular people on login itself. It alleviates any friction the user will have initially to engage on the platform and also interacting with the popular users sets the context for them to get active. In doing so Twitter achieves more invitations and requests sent to users and prospective users and also re-connections and engagement between existing users. That’s a double viral loop.

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Similarly, it’s important for any marketer to understand the viral loop of their product, one would have to iterate and measure to understand in detail the parameters and the best possible viral loops.

At Zoomdeck, we are creating a platform for making photos interactive. A User can spot anything interesting inside photos to ask a question or add notes or add spots to highlight an interesting story or experience about an element inside photos, then make it much more engaging by linking the spots to audio, video, products, people, places or any link relevant. Users would be able to discover and share the stories and elements in photos using interactive spots and have contextual conversations around each spot. We have a web version, an iOS app and an embedding option which along with viral content shared across various Social Media sites would be a key driver of traffic and user acquisition for us. When I look at the various channels of virality for Zoomdeck, I have:

  1. Embedding: Bloggers and Publishers embedding Interactive Photos on their website. Similar to how Youtube utilized embedding as an important element of their Viral growth.
  2. User joins Zoomdeck, takes photos and makes them interactive by adding spots. Shares it with their friends and family (Invite). ( This will have a longer Viral Loop time) Similar to how Instagram or Pinterest built their viral loop.
  3. Directly recommends the product to their contacts through the invite option in the app or in person.
  4. Sharing of Interactive Photos they find interesting on Zoomdeck( Content) on Social platforms ( Facebook, twitter or Pinterest). Their network discovers, finds it interesting and shares with their friends. ( This will have a much shorter Viral Loop time) The advantage of having content that is viral in nature is the Viral Loop time significantly reduces as you are providing ready made things for people to share and not asking them to create which is always time consuming and requires an effort and hence would always have friction. A Youtube or Twitter is a great example of this.

The four basic viral loops in the case of Zoomdeck as mentioned above would each have different conversion ratios. While the first option and the fourth option would enable Zoomdeck to reach a much larger base of audience and that too multiple number of times, the conversion percentage is going to be a lot lesser than the second and third option where in our chances of conversions are much higher. Similarly, the Viral loop time for the first and fourth option would be much lesser than the VLT number for the other two. So measure the various parameters continuously and optimize for the ones that give best results.

Importance of Seeding :

Imagine for calculation purpose the current user base of a product as 5000 and consider only the 2nd and the 3rd channels of virality listed above as the growth channels for easiness in quantifying. (Assume a Viral Coefficient of 0.6 and a Vlt of 10 days) We would have a table that looks like this

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And our user graph would look like this:

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Now, assume acquisition of a constant number of users from other channels, we have (all values are hypothetical):

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Seeding initially is critical as that’s what enables the viral growth to kick in. In the first example we flatten out our user base after 2 months. This is why seeding should always be an ongoing process to leverage maximum value from virality or else we should have a viral coefficient greater than 1 to have an eternal upward curve for our user graph which is very difficult to achieve throughout the lifetime of the product. There would be short bursts when the viral coefficient is greater than 1 and would result in phenomenal growth especially if you are on a larger base as well but not through the lifetime of a product.

Key-points:

  • Virality is something that should be inherent in the product. It’s important to design and incorporate virality during product conceptualization itself.
  • Always measure and track various metrics to understand what works best and dig deep into those channels.
  • Iterate as fast as possible to understand the best viral channels. The longer the iteration cycle, the longer it will take for you to spot your best viral loop.
  • Reduce the number of steps required to do any action that results in virality. Make it as easy as possible for the users to send invitations. Understand that the easier you make, the better your metrics would look.
  • Two factors that influence Virality are: Viral Coefficient (K) and Viral Loop time (Vlt). Increase ‘K’ and decrease ‘Vlt’ for rapid growth.
  • Retention and re-connection are important factors that help in Viral growth.
  • Important to seed users initially.
  • Exponential growth from Virality kicks in after a threshold limit. Make use of various channels for seeding the initial audience.
  • It’s very difficult to achieve sustaining growth through virality where you require a viral coefficient greater than 1. Hence, compensate for this and balance it out by seeding users through other channels as well – if required paid channels also to maintain momentum.

References:

http://www.forentrepreneurs.com/lessons-learnt-viral-marketing/

http://www.linkedin.com/today/post/article/20130402154324-18876785-how-to-model-viral-growth-retention-virality-curves

http://andrewchen.co/2007/07/11/whats-your-viral-loop-understanding-the-engine-of-adoption/

If you are worried about user acquisition, growth rate, engagement, retention and more, here is something that will cheer you up! List of all the resources you can fall back upon to drive up your growth numbers.


Growth Hacking Tools List:



User Acquisition & Retention:



Blogs & Communities for Inspiration:


 (PS: Thank you autosend.io for the list)

Business success stories always inspire us. There are various types : the rags to riches story, the ones involving outsmarting and outmaneuvering competition, the exceptional in execution story, the stories involving how one went bust before springing back up – all of them are quite inspiring and at the same time fun to re-visit. The ones that tops the list for me are the ones who outmaneuvered and outsmarted the biggies in a head on competition. Compiling a list of few of the most amazing stories:

The Dow Story

Herbert Dow founded Dow Chemical in Midland, Michigan when he invented a way to produce bromine cheaply. He sold the chemical for industrial purposes all over the US for 36 cents per pound at the turn of the 20th century. He couldn’t go overseas, however, because the international market was controlled by a giant German chemical cartel that sold it at a fixed price of 49 cents per pound. It was understood that the Germans would stay out of the US market so long as Dow and the other American suppliers stayed within its borders.

Eventually Dow’s business was in trouble and he had to expand. He took his bromine to England and easily beat the cartel’s fixed price of 49 cents per pound. Things were okay for a while until a German visitor came to Michigan and threatened Dow that he had to cease and desist. Dow didn’t like being told what to do and told the cartel to get lost.

Shortly thereafter German bromine started appearing for sale in the US for 15 cents per pound, way below Dow’s price. The cartel flooded the US market, offering the chemical way below their own costs, intending to drive Dow out of business. But Dow outsmarted them. He stopped selling in the US market entirely and instead arranged for someone to secretly start buying up all the German bromine he could get his hands on. Dow repackaged it as his own product, shipped it to Europe, and made it widely available (even in Germany) at 27 cents per pound. The Germans were wondering 1) why wasn’t Dow out of business and 2) why was there suddenly such demand for bromine in the US??

The cartel lowered its price to 12 cents and then 10 cents. Dow just kept buying more and more, gaining huge market share in Europe. Finally the Germans caught on and had to lower their prices at home. Dow had broken the German chemical monopoly and expanded his business greatly. And customers got a wider range of places to buy bromine at lower prices.

Dow went on to do the same trick to the German dye and magnesium monopolies. This is now the textbook way to deal with predatory price cutting.

Source: Herbert Dow, the Monopoly Breaker

Rafael Tudela’s Business Empire:

Rafel Tudela is a Venezuelan oil and shipping businessman. He is the quintessential street-smart executive.

He has built a billion-dollar business from scratch in less than twenty years. He seldom deals in written contracts because his word is his bond. He has always made his own breaks. And his principal business, which is oil speculation, relies on his constant process of seeing opportunities where no one else does and taking advantage of them.

In other words, Rafael Tudela is a genius at taking the edge. One of the best illustrations of this –of how he has the facts, knows what people want, and figures out a way to give it to them- is the story of how he got in the oil business in the first place.

In the mid 1960s, Tudela owned a glass manufacturing company in Caracas, but, a petroleum engineer by training, he longed to be in the oil business. When he learned from a business associate that Argentina was about to be in the market for a $20 million dollar supply of butane gas, he went there to see if he could secure the contract. “If I could get the contract,” he told me, “then I`d start to worry about where I`d get the butane.”

When he – a glass manufacturer operating alone with no previous connections or experience in the oil  business – got to Argentina, he discovered his competition was formidable: British Petroleum and Shell
Oil.

But feeling around a little bit he also discovered something else: Argentina had an oversupply of beef which they were desperately trying to sell. By knowing this one fact –his first “edge,” so to speak- he
became at least an equal to Shell and BP. “If you will buy $20 million of butane from me,” he told the Argentine government, “I will buy $20 million of beef from you.” Argentina gave him the contract contingent upon his buying the beef.

Tudela then flew to Spain, where a major shipyard was about to close down from lack of work. It was a political hot potato and an extremely sensitive issue for the Spanish government. “If you will buy $20 million of beef from me,” he told them, “I will build a $20 million supertanker in your shipyard.” The Spanish were ecstatic and delivered a message to Argentina through their ambassador there that Rafael Tudela`s $20 million of beef should be sent directly to Spain. Once again he had found the edge and taken it.

Tudela`s final stop was in Philadelphia at the Sun Oil Company. “If you will charter my $20 million supertanker, which is being built in Spain,” he told them, “I will buy $20 million of butane gas from you.”

Sun Oil agreed, and Rafael Tudela fulfilled his desire to get in the gas and oil business.

Excerpt from the book: “What they don’t teach you at Harvard Business School.”

ASUS’s Story:

Dell computer used to outsource the manufacturing of their motherboards to a Taiwanese company.

Then, one day that little company presented Dell with a new offer: they could start assembling whole computers for Dell. For Dell, this meant higher profitability: they’d have the same revenue, but with a lower cost base. For some reason the Taiwanese didn’t seem to care as much about profitability, only cash. But that’s probably because they’re still a bit backwards in Asia and don’t have any Harvard Business School-educated MBAs to teach them otherwise.

Anyway, that arrangement worked out well. One day the company came back to Dell with a new offer: they could take over Dell’s entire supply chain. For Dell, that meant even lower costs, and so even better profitability. After that arrangement was put into practice the company came back to Dell and offered to start designing computers for them. Brilliant! Dell could now focus on its core competency,branding, and let the Taiwanese do all the unglamorous work of actually building the damn things.

After that arrangement was put into practice the company took another trip to the US, but this time they didn’t visit Dell. They went to Best Buy, and offered them PCs that were as good as Dell’s but at a significant discount.

Softsoap and it’s acquisition by Colgate

“Back in the 1970s, liquid hand soap was sold by one guy: Robert Taylor, and his small company Minnetonka.  It was his invention, and he knew he was on to something big. Test  audiences loved the product and, despite barely having enough resources  to do so, Minnetonka decided to go all in and make a push to take the  product nationwide.

There was only one problem: Nothing he was selling could be patented.  The concept of liquid soap wasn’t new, and simple pumps had been around  since the dawn of civilization. As a result, Taylor knew several huge  soap manufacturers were ready to happily steal his idea the very moment  it looked like it could succeed on a large scale. Armed with superior  resources and the ability to quickly R&D an imitation product, the  industry giants were ready to crush tiny Minnetonka.

Taylor, however, was ready for this. Before any other company had the  chance, Taylor decided to go shopping one day and bought a few plastic  pumps. And by a few we mean FUCKING ALL OF THEM. There were only two  companies nationwide manufacturing those little pumps, and Taylor ponied  up $12 million — more than the total net worth of his company at the  time — and ordered 100 million of them,  effectively buying every single pump these two companies would be able  to manufacture for the next year or two.

Anyway, without the part required to dispense the soap, there was  nothing the major companies could do but sit and watch Taylor slowly own  the entire market. His product would become known as SoftSoap, Two years after his little stunt, Colgate-Palmolive  would be forced to just buy SoftSoap from Taylor for $61 million.”

Reference : http://en.wikipedia.org/wiki/Softsoap

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~Inspired by this thread on Quora

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