Piracy is a universal problem for businesses. From bootlegged novels on the roadside to fake luxury goods to pirated versions of your favourite computer games, music, movies and office software, pirated goods present potential losses of billions of dollars for each of these industries.
Why, then, is it so easy to pirate software goods and get away with it? Are multibillion-dollar companies like Microsoft, Netflix and Universal Studios so helpless that they have given up on trying to secure their intellectual property? Also, shouldn’t such large-scale piracy deter further innovation?
To analyse the problem of piracy beyond a common-sense approach, we need to consider two factors: one, would the consumer of the pirated good have actually paid for the legitimate product anyway; and two, has the legitimate product benefited from the word-of-mouth publicity effected by the pirated product? Both these answers are fairly complicated, and have puzzled business academics for a while.
Companies may have control over their marketing actions, but consumer decisions are, to a large extent, influenced by word of mouth, which is beyond their control
Consider the following situation. Renowned method actor Aamir Khan has released his latest movie Dangal. You must decide whether you want to watch it. If you do, you could watch a poor quality, illegal print from the internet, or go to the nearby multiplex and pay Rs 350 per ticket. Your decisions are probably affected by the promos of the film that are bombarding you on mass media, as well as your discussions with friends, social media and critics.
Thus, Aamir and team may have control over their marketing actions, but your decisions are, to a large extent, influenced by word of mouth, which is beyond their control. Furthermore, the kind of stuff you tell your friends after the movie may affect their decisions to watch it. So, how can the differential effects of these two things be quantified?
The word-of-mouth effect
Inspired by epidemiological models of viral spread, Frank Bass proposed a differential equation for the rate of adoption of a new product, where he assumed that every new product has a fixed number of potential consumers, called market size, and each of these are affected partly by marketing, and partly by word of mouth.
So how does word of mouth work? If we have a total of ‘m’ people comprising a market, out of which ‘N’ have adopted the product at any given time, the Bass model assumes a word-of-mouth effect proportional to N(m–N). Conceptually, the adopters (N) have an effect on the remaining (m–N) people in the market. However, as N increases, (m–N) duly decreases. Thus the word-of-mouth effect is interestingly nonlinear in nature. In comparison, marketing efforts have an effect proportional to just the number of remaining non-adopters (m–N), thus becoming increasingly ineffective as more people adopt the new product.
Bass’s model was remarkably accurate in predicting the dynamics of sales of durables in post-war America, helping companies optimise their marketing budgets and activities, apart from planning their inventories. The Bass model is a landmark study in marketing, and has spawned hundreds of papers, like modelling how to space two generations of a new product, optimal pricing decisions, and even modern-day research on social networks.
Say your friend downloads a Torrent of Dangal, and then writes a glowing review of it on her Facebook wall. The word of mouth spread by her is indistinguishable from that spread by you, who has watched the movie legally
Moshe Givon, Vijay Mahajan and Eitan Muller modified the Bass model to include piracy. Their model assumed that while consumers of pirated goods do not directly contribute to the seller’s revenues, they do spread word of mouth to other potential consumers of both pirated and legitimate goods, and consumption by them is simultaneous to that of others who buy legitimately.
Think about your friend who downloads a Torrent of Dangal, but then writes a glowing review of it on her Facebook wall. The word of mouth spread by her is indistinguishable from that spread by you, who has watched the movie legally.
Studying sales data of an office software in the UK, they estimated that six out of every seven users were using pirated copies, but these pirated users helped generate about 80% of the legitimate sales of the same product. Thus, while pirates did represent an opportunity cost to the seller at face value, they may have actually helped sell the real thing by spreading awareness about it.
Lack of consumer awareness is a kiss of death for any new product, and companies can either raise awareness via promotions or hope for word of mouth or, ideally, both. If the software firm above had strictly clamped down on piracy, we don’t know how successful it may have been.
Studying sales data of an office software in the UK, researchers estimated that six out of every seven users were using pirated copies, but these pirated users helped generate about 80% of the legitimate sales of the same product
There are, of course, limitations on how much piracy may actually be beneficial, and the jury is still out on this matter, with several researchers continuing to work on this. Moreover, the model of Givon et al does not consider the possibility of a consumer upgrading from a pirated version to a legal version later on. The next time you see an engineering student use a pirated version of MATLAB software, remember that the effects of his/her actions are not as obvious as you may imagine.
This column is intended to showcase interesting academic research in marketing. The technically oriented reader is encouraged to read the original research articles cited in the column.
Lead visual: Nikhil Raj