Long Tail and e-Commerce

When I first saw the Long tail graph the first thought that came to my mind is this is 1st quadrant 1/x. and the unique property of 1/x is that it tends to 0 at infinity implies it always has a finite value for even the largest value of x. Now moving from graphical to the business implication:

Long tail property allows e-commerce business which have low inventory costs and offer low search costs to provide "unpopular" products. By just observing you can see that one can provide equal or more sales by offering low demand products than by selling the popular products.

E-commerce provider low search, storage costs which has resulted in exemption of Pareto's 80:20 rule- 80 % of your sales will come from 20% of your products. Now companies like Amazon and Netflix can house the products economically at a centralized warehouse and offer a wide range of products. This change has affected people's preferences as earlier they could not find the product of their choice which was outdated.

Final verdict: The more extensive the data warehouse will become the thicker the tail will be.

Networks and BI

Networks have become a very integral part of our lives. and technology is making full use of networks to make our lives easy. Facebook makes use of networks and lets you designate some friends as "Close friends", you are send special notifications when these friends update their status or post a new album.

LinkedIn and Twitter use networks to analyze your level of association with others and based on that you get recommendations to follow similar trends or add new friends.
But Amazon's use of networks combined with Business Intelligence is something that others have not being able to emulate.

The recommendation system system of Amazon suggests you new products based on someone else's shopping experience. and to everyone's surprise the recommendations are quite helpful.

As time progresses we will see closer association of network study and business intelligence.

Various similar terms

While browsing through the web for proper understanding of the semantics of various online marketing terms this is what I learnt:

Cost per milli=Cost per 1000= Cost per impression:
These three terms all mean the same. This model of online marketing generates revenue in the ways similar to the traditional marketing- amount of exposure. The firm is charged on the basis of number of people to whom the content was displayed. Mind it DISPLAYED.

Cost per click: Is the next step in online marketing evolution. Here the firm is charged either a fixed or a varying amount for every click on the ad being displayed. This is a better quantifying metric to estimate the success of ones marketing campaign as you can actually see how well you ad campaign is doing and accordingly change it.

Cost per action: This is the final step of evolution in the online marketing strategy. Here is the firm is charged on the basis of execution of a pre-defined action like purchase of a product, filling of a form etc. This ad campaign though best for the advertising firm is not the best from the website's point of view. because majority of the people still buy things offline (for reasons click here- http://www.theatlanticwire.com/technology/2011/12/we-still-shop-mall-bunch-reasons/45738/ ). People come online survey the product of their choice and still buy stuff from the store/mall.

Lastly we have another form of marketing campaign but this one is different in its essence. Pay per sale followed by Groupon and similar businesses needs equal dedicated efforts from both sides.

online v/s offline marketing

The times have changed. The proverb- First impression is the last impression, cannot be truer. The attention span of an average person is so small that as a product either you make it big or you find your place in the basement. In such volatile times marketing has reached a completely new dimension, with a plethora of options the marketing team had to find the right audience and target them in the only best way possible.

The technology is supporting these advancements. Benefits of online marketing
1. targeting the right person: based on the users shopping/ browsing history you can find the right person to market to rather than spend millions on trying to woo everyone.

2. dynamic: you can change/ tweak you marketing campaign very readily from the comfort of your home/ office rather than changing all the billboards all over the country or coming up with a new print/media ad, shooing for a commercial etc.

3. ubiquitous: with the huge number of mobile apps and internet devices all around us online marketing is able to penetrate every minute of our lives rather than just one glance from the morning newspaper.

Google has become the leader for these and many more reasons.

A/B testing

Testing for web analytics: testing entails one of the major costly operations for any organization. And when the issue is of website designing where user input and perspective is of paramount importance A/B testing is the best route out. A business can assess its competence at converting its visitors to customers by defining certain metrics or KPIs and then make "minor" changes to the website to see which option helps them achieve their KPI better.

The problematic issue with A/B testing is that the changes made to the website should not be drastic and frequent, and that KPIs should be well defined and quantifiable. Implementing A/B testing is easy but understanding what you want to achieve out of it and planning around it is mind-boggling.

In today's fast paced time the human mind is accustomed to living in their comfort zone, changing site drastically will offset this convenience and the A/B testing can result in a business loss.