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Article originally posted on Data Science Central. Visit Data Science Central
General Data Protection Regulation (GDPR) came into force in European Union (EU) member states from 25th May 2018. It has far reaching ramifications for businesses and organizations given that data is ubiquitous and all businesses today rely on customer data to remain competitive in their industry and relevant to their customers.
In this blog we will examine some of the challenges that businesses in certain industries can face and what businesses can do about it. GDPR restricts itself to personal data thereby limiting its regulatory reach to all such companies and organizations that are serving direct consumers of their services.
In this era where advertisements on social media, advertisements on web pages, advertisements on mobile applications are personalized by gathering and processing information about the specific user how can companies that use these media of connecting with their customers continue to send pertinent communication/messages to their customers.
In retail ecommerce customers are shown recommended products using association rules and recommender systems. This is possible because the company keeps track of customers past purchases (past buying behaviour) so as to recommend new products to the buyer.
After implementation of GDPR the following can happen
- The buyer can refuse the ecommerce company to control and process his/her data. This at once nullifies all the investment it has made in processing this buyer’s data as it is brick-walled from its customer.
- On the flip side it gives a level playing field to other ecommerce companies as every buyer out in the market is anybody’s customer. In short, customer loyalty will be short lived.
So how can organizations and companies insulate themselves from losing out their customers? The answer is simple and has stood the test of time – roll out the best service to each customer whether the customer is buying from them for the first time or the hundredth time. Companies will have to relentlessly satisfy customers in every transaction so that customers willingly share their data. Period.
According to Epsilon research, 80% of customers are more likely to do business with a company if the company provides personalized service. With a possible destruction of customer data after completion of transaction as stipulated in GDPR
- It is difficult for companies to personalize their offerings to “customers”.
- Customer profitability KPIs like Life time Value(LTV) may not be meaningful anymore as the same buyer is a new customer each time if the buyer chooses to annul his/her personal data after completion of every transaction.
- Newer catch-phrases like Customer Journey Mapping fall off the grid as the “traveler” in the “journey” is temporary and companies may not even know the “traveler” i.e. the customer.
So how can companies personalize their services to customers? Prudent companies can anonymize customer data by encrypting it immediately after sourcing it. Though this will not help them decrypt to find the specific customer the still company has some sort of a handle on its customer.
Companies in the financial services rely on accurate, updated and complete customer data to discern genuine customers from fraudulent ones. To keep good customers separate from bad ones companies will have to be innovative to “pseudonymize” customer data.
So how does this work?
GDPR only regulates personal data and not transactional data. So financial service organizations will have to “pseudonymize” customer data using new technology mechanisms (which may or may not exist today) so that customer data is also treated as transactional data. Such transactional data can then be trained using Machine learning/Deep learning algorithms to spot fraudulent customers from reentering the financial services market.
All data is stored in servers and server farms on the cloud or in in-house data centres. As the financial cost of misdemeanor in following the GDPR is very high (ban on customer data processing and a fine of up to higher of €20 million or 4% of the business’s total annual worldwide turnover) the IT and ITES industry may also not be immune to impacts. The following impacts may be notices
- There may be instances where the processor of the data (the organization that defines the how and why of customer data) may move the data on-premise thereby playing the role of controller of data as well. The controller is the one holding the data like AWS.
- Small businesses may be tempted to move from cloud to on-premise to reduce chances of data theft or rework their contracts with data controllers to insure themselves.
With the widespread use of data science and machine learning in business, companies would have to be very diligent in deleting customer data from training data that is used to build supervised algorithms if a customer asks for deleting his/her personal data that is part of training data. If many customers follow suit then the model so built is itself now rendered inefficient as the training data has changed and patterns have to be learnt again. Companies will have to keep their learning algorithms and models updated regularly so that their outputs are pertinent.
GDPR puts the onus of processing data on companies and organizations and awards private individuals complete rights over the way their data can be stored and processed. As individuals become custodians of their data they may choose with whom and for how long they may share their data. Is it possible in the future that large groups of users form cartels and charge businesses for using their data?