Digital pirates are keeping up with the times! They use the same technology that OTT and streaming platforms use to distribute unlicensed content. They have built their own ecosystem with cutting-edge technology. Now, all that a pirate needs are a streaming box and a high-speed reliable internet connection.
The days of torrents, cumbersome search for content, painful downloads, and low-quality content have gone. The content is just out there easily accessible, and high quality too.
The only way content owners and anti piracy firms can fight this evolving form of digital piracy is by using computing and machine learning prowess. Effective anti piracy and content protection is near impossible with traditional anti piracy measures. This is where using machine learning to fight digital piracy becomes inevitable.
Fighting digital piracy is all about staying a step ahead of pirates. Using machine learning and data analytics in combination with natural language processing (NLP), keyword searches, etc., (to identify sites hosting pirated and unlicensed content) is a great way to fight digital piracy. Let us understand how!!
What is Machine Learning? How can it be used for fighting Digital Piracy?
Machine Learning is a subset of Artificial Intelligence. Machine learning is the ability of systems to automatically process big data and produce reliable and repeatable outcomes. It is based on the concept that machines can learn from data, identify patterns, and perform specific tasks with minimal human intervention. In this case, identifying URLs hosting pirated content. Machine learning can either be supervised or unsupervised.
With respect to fighting digital piracy, supervised machine learning is a better choice as it involves training the machine using data that categorizes URLs as legitimate or illegitimate. It can also be trained to identify piracy hotspots and hosting sites with the highest incidence of piracy and the most likelihood of hosting infringed content.
By crawling the web, the monitoring and detection team effectively compiles an exhaustive database of URLs. Applying various machine learning algorithms, customized to each content type, the URLs are categorized either as legitimate, or illegitimate URLs hosting pirated content. This process typically eliminates approximately 94% of the URLs, and it is usually the remaining 6% URLs that host pirated content.
Since this is a reiterative process, the system progressively becomes efficient and accurate with each reiteration. The anti piracy efforts get laser focussed on eliminating this narrow subset (6% URLs that host pirated content) thus greatly enhancing the effectiveness of anti piracy efforts in terms of speed, time, and eradication rate.
Checks and Balances & How it Improves Machine Learning Efficiency
Even as the machine learning tool identifies an URL as an illegitimate URL hosting infringed content, anti-piracy analysts manually cross-check the identified websites before authenticating whether the URL has been correctly identified.
This process, in turn, helps further finetune the machine learning systems. These human decisions are used to train the system/machine, which when confronted with similar situations in the future will be better able to deal with the query. A machine learning technique called reinforcement learning in which the machine learns from continuous and relentless trial-and-error is used.
Machine Learning Could Deliver a Decisive Blow on Digital Piracy
Machine-learning technologies that are applied to investigate high-value and high-profile cyber attacks can be used to detect pirate websites, find their owners, and remove illegal content.
Classifying traffic by using IP flow data from an IPFIX/NetFlow feed is an option that seems to have a lot of promise.
Machine learning can exploit weaknesses in the piracy ecosystem where most providers are using a client/server software pair from specific providers, and these can be targeted.
Use IP flow data to detect pirated linear streaming traffic on broadband networks.
Do you think that Machine-Learning Based Piracy Detection system could give digital piracy a final decisive blow, or do you believe that the pirates have a lot more “up their sleeve”?
The internet space via search engines, websites, e-commerce platforms, mobile apps, social media, smartphones, etc., have drastically changed how businesses are conducted and brands perceived. Most purchase decisions and purchases are made after searching & researching the brands, products, and services online.
E‑commerce or market places accounts for over 22% of global retail sales. Most customers come to your website through search engines, email, social media, mobile or online ads, rarely do they come by typing your URL directly into browser address bars.
Since online is where the customers are, the fraudsters with their fake products and services throng to the online space to sell their wares. Brand misuse is done with fully functional fake websites, emails, logos, product descriptions, etc. Everything from music, movies, holiday packages, life-saving drugs, automotive parts are fraudulently sold. Your content and imagery are used to create URLs that appear authentic to hijack your brand, wean your customers, and steal your profits.
As a consequence, brands not only lose their credibility and reputation that they have meticulously built but also lose billions of dollars due to counterfeits and brand abuse. Since many brands are still to grasp the enormity of online frauds, they do not have a comprehensive brand protection strategy for digital channels.
A recent report by the Organisation for Economic Co-operation and Development (OECD) mentions that fake goods result in over $500 billion in losses annually to legit businesses. The biggest consequence of not protecting the brand online is the loss of trust in the brand. More than 52% of customers have lost trust in a brand after being deceived by counterfeit products.
As search engines are at the epicenter of a buyer’s journey across mobile, web, and social media, it is extremely important that your brand is digitally protected and this is the most important element in your digital marketing strategy.
Needless to say, you should have a comprehensive online brand protection strategy with effective enforcement.
An effective online brand protection strategy should essentially monitor online channels; search engines, social media, marketplaces, e-commerce, and auction sites, paid search, email, etc.
When brand infringement is detected, they should be able to enforce brand rights within the framework of legal guidelines.
Specific enforcement measures might include but not limited to bringing down counterfeit and digital piracy sites, stopping the sale of unlicensed products by delisting counterfeit listings on e‑commerce marketplaces, delisting fraudulent paid search advertisements, eliminating your logo and trademark misuse or misrepresentation, identifying and terminating fake websites, fake social media accounts, taking down typo squatters, cyber squatters, and domain squatters, etc.
Building a competitive advantage with data-derived by brand protection and enforcement. You have to appreciate and understand that the fraudsters are good at identifying demand and supply gaps and capitalizing on that. They are also responsive and adaptive to market changes. By analyzing the data obtained in your fight against digital brand abuse, you can improve marketing, pricing, products, packaging, promotions, customer service, and distribution strategies of your business. They also help you identify price point gaps and opportunities in different market segments. Researching and identifying keywords that counterfeiters are using to wean away traffic from your brand is a great place to begin for your marketing team. They are a clear indication of which keywords are customers using to search for your product.
While customers use search engines for every stage of their buying journey right from the price comparison, feature comparison, product reviews to the actual purchase, brands must deliver credible & trustworthy brand experiences across digital channels.
An effective online brand protection solution helps you recapture revenue, convert potential customers to paying and loyal customers, preserve brand credibility and trust, and safeguard the long-term future of the business.
Selecting the right brand protection partner is the key. Selecting the right brand protection partner could help design an effective brand protection strategy and thus help all key stakeholders make informed decisions and produce measurable results and a compelling ROI.
Piracy-Derived Data can improve film distribution strategies
Digital piracy or online piracy is the biggest enemy of Content Owners, but could Piracy‑Derived Data & Business Intelligence be their greatest friend!!
Interesting insights could be obtained by Piracy-Derived Data.
“Data will talk only if you are willing to listen” and “Your data is only as good as your ability to process it” and “Data is just the beginning……” These 3 quotes more or less summarize what data is all about!!!
What is that we, as content owners, will have to listen to?
Which titles or movies are pirated the most? Which regions do they get most pirated in? When does maximum piracy occur; post-release, pre-release, post-nomination to awards, after being awarded?
What are the questions that we should seek answers to?
Are our current distribution platforms adequately catering to the demand?
Are the films released on time at these geographies or is there a delay?
Are we promoting our movies or content adequately in these regions?
Is our content reasonably priced to sell and is it easily accessible?
Are there any blind spots we have in terms of marketing and promotion of our content?
When it comes to our catalog content portfolios, which are the ones that are most pirated; where and why?
We did get the answers
Piracy was highest where the popular title/ movie release was delayed because of underestimating content demand in those geographies or various other reasons. No promotional activities were done to promote these movies in these specific geographies. The most critical factor was overpricing; the pricing was out-of-reach for a large number of potential customers.
Obviously, they resorted to watching pirate content, and pirates were more than happy to give them access to unlicensed content. Many assumptions with regards to popular catalog content were proven wrong based on piracy-derived data.
Piracy-Derived Data can Predict Blockbusters and Award-Winning Movies
What the Data Tells
Highly pirated movies are potential blockbusters.
Data on viewership/piracy of movies nominated for awards could predict which movies could eventually win the awards.
Data on movies that do extremely well when released on OTT platforms but had lackluster theatrical release points at inadequate marketing and distribution theatrically.
Data derived by keyword research on movie releases could give great insight into demand.
The films that are nominated for awards get highly pirated.
The film winning the awards remains in demand and has more shelf life.
Data also gave direct inputs as to where the demand for such content is highest.
How we Could use This Data
For projecting box-office collections.
Focussing our resources on marketing and promoting the movies that have the best shot at success both in the box office as well as the awards circuit.
Spotlight on key markets that were underserved and ignored.
Piracy-derived data could be used for making strategy with regards to offline and online merchandising of film-related memorabilia.
Entering hitherto unexplored new markets to improve business revenue and increase the fan base.
Paradigm Shift in Mindset-Converting Piracy to your Advantage
This approach to piracy and piracy-derived data is completely counterintuitive. As a result, pirates and piracy-derived data can be viewed as a feedback loop on how content owners could change distribution strategies. The mindset change is how can we use this data for converting potential customers to paying customers. Plugging marketing and promotional gaps in certain geographies and markets.
Reworking on pricing so that our content is accessible to the widest possible paying customers. Relooking our movie release date patterns across geographies where there is the demand for our content. Giving more attention to overlooked catalog properties based on data derived from piracy. Focussed marketing and distribution efforts towards such catalog properties. Laser-focusing our promotional, marketing, and lobbying efforts on movies that have the highest potential for success both in the box office and national and international awards.
Should we conclude by quoting Peter Drucker, “what gets measured, gets improved”. Use the insights from piracy data, i.e., illegal viewership/downloads, geographies, demand‑supply gap, etc. to see how you can improve business revenue.
