Open Source Marketing to the Max - Maximizing Blue Ocean Long Tails and Bull's-eyes

Long Tail Segmentation

A complementary segmentation that is more demand driven and related to (BO 3) above is long tail segmentation which is extensively written about in "The Long Tail by Chris Anderson". The classic example used is for moving from selling  CD's on a shelf in a shop to "bits" online (in iTunes). Every inch on a shelf in a store costs a significant amount of money and has to sell a significant amount of CD's to make a profit. Hence only the top 1000 CD's are held in the store, for example.

The cost to sell 1000 and 1,000,000 albums online is almost the same. Also, the interesting long tail characteristic is that even though after the top 1000 the numbers sold goes down dramatically to maybe 1 every few months the volume sold from 1001 to 1,000,000 is larger then the top 1000. This creates a situation where the store struggles to compete on a level playing field with an online retailer, particularly when the online search experience improves on the physical one.

The same segmentation applies extremely well to enterprise software. Traditionally every enterprise software trial has required a salesman and sales engineer to drive it. This large cost caps the number of trials that can be done. To go to a new country is a very significant  expense requiring a new office staffed with demand generation, sales and technical expertise. This severely limits the geographies that are economically feasible to sell into. This is where (BO 3) comes into play - Those that have been rejected by the software vendor because the cost of sale is too high to make a profit on this segment. Blue Ocean 3 segments can occur by geography, region in a country, types of small departments in large companies, small companies - niche after niche.

Open source enterprise software lends itself to a long tail. It follows an online  discover, research, try, buy model. The cost for the customer to search for and try the product is free. The cost to the company for 1 prospect to try the product is similar to the cost for 1,000,000 prospects. The cost to the company for a prospect to try in one geography is similar to the cost to try in another geography. Local communities often create new language packs.

Documentum after 4 years was used in 3 countries (driven by pharmaceutical company locations). Alfresco a comparable open source company in the same time period has paying customers in 43 countries and is used in over 180 countries - Blue Oceans and Long Tails grow much more rapidly.

Not all Segments are Equal when it comes to Monetization

Having previously discussed "Blue Ocean Sandwich Ratios" and the attractiveness of markets, the other key analysis for potential segments is the:

Traditional Pay Ratio

Even in a great "Blue Ocean Sandwich" if the target customer traditionally does not pay, or does not feel the need to pay, the segment has little monetary potential. If the low-end is good enough and free, then there is little reason to pay - look at the success sof the Apache web server. If your product is a database that powers a website the customer cares about if the website is up or down and has a higher Traditional Pay Ratio. People traditionally pay for Office software but rarely use support. Therefore, if your business model is support, this segment has a low Traditional Pay Ratio (TPR) and is less attractive to monetize. TPR also varies by geography. You are less likely to monetize in China for example than the USA and mainland Europe.

When you find a good Blue Ocean and TPR traditionally served by enterprise software vendors a rule of thumb is to have a price that is a tenth that of the existing vendor to calculate the market potential.

New Open Source Segmentation Summary

If you can deliver an open source product that provides the functionality of a traditional commercial product, in a simple consumerable package at  a tenth of the cost a really hard question is who will buy it and a question we asked ourselves. Will it be Small Medium Businesses who could not afford traditional enterprise software, companies committed to an open source stack or companies that had already purchased one or more content management systems that wanted to expand from the 5% to 10% of users out to the company (on their existing architecture). What we found was the latter (Blue Oceans BO1 and BO2) have dominated and that these Blue Oceans have expanded rapidly geographically. What is important though is you position to Blue Ocean segments and follow demand, You specifically do not focus on traditional demand creation particularly geographically. It is very difficult to create Blue Ocean demand when it is not there. Using Google analytics to see demand is much more fruitful than trying to create it in a country where there  is not inbound demand.

So in summary:

• Position yourself for those that are already looking for an alternative
• Position yourself for those that that have either tried and rejected the software in question. It has either been too expensive or too complex to use or rollout (or both)
• Target to the segments with the largest "Blue Ocean Sandwich Ratio" in a horizontal way for the masses
• Target to those with the Highest "Traditional Pay Ratio"
• Make yourself the bull's-eye target for those that are looking for your solution and make your self easy to be found. Everywhere someone turns they hear about you.

Then

• Follow the long tail demand for those that have been rejected by the software vendor because the cost of sale is too high to make a profit on this segment

In a nutshell - Make Markets not War

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