Data-driven marketing has been an effective marketing approach for several businesses. But, are there any negative implications of implementing data-driven marketing?
Several business leaders and experts have claimed that data is the new oil. Multiple organizations have realized the importance of gathering critical customer data to make the most out of their data-centric business models. In fact, data has become so essential for businesses that startups are generating synthetic data to eliminate the cold start problem. Hence, numerous organizations in every industry sector are adopting a data-driven marketing approach to offer better products and services and ensure customer satisfaction. Although there are numerous benefits of data-driven marketing, several experts have raised privacy and security concerns regarding aggressive data collection. The entire conflict may create a deadlock situation as consumers are paranoid about sharing their data, and businesses need to accumulate more data for business practices. But, during his congressional testimony, Mark Zuckerberg said that data isn’t everything. He added that data-centric customer targeting doesn’t always work in marketing. Hence, organizations need to address customer concerns by generating a trustworthy and transparent approach towards data collection.
Accumulating and optimizing customer data is a complicated procedure. Manually collecting and optimizing customer data is highly inefficient. Whereas a basic software-based approach is better, it’s still not up to the mark as the database needs to updated quite frequently. Marketing automation, with the help of AI and big data, will automate the entire process of data collection and optimization for data-driven marketing mechanisms. Also, customer data will be updated and optimized at specific time intervals without any human intervention. The updated data can help generate analytics to create customized marketing strategies that cater to different customer preferences.
Customers are always looking for products and services that would cater to their requirements. So, businesses are consistently trying to target a specific customer base to endorse their services. But, different customers that belong to various age groups, ethnicities, geographical locations, and financial status have a wide variety of requirements. Hence, segmenting customer data and developing strategies is a complicated task. Gathering critical customer data provides insights into every customer’s needs. By optimizing and analyzing the accumulated data, using big data analytics, marketers can understand every customer demographic precisely. With such profound analysis, marketers can create data-driven marketing campaigns that are personalized to target every specific demographic. A personalized marketing campaign will have a better success rate as it caters to customer’s preferences.
Industry trends are constantly changing. Businesses that stay ahead of changing industry trends have better chances of being successful. But, multiple businesses fail at predicting the upcoming trends only to find themselves unprepared later. Big data is the most feasible solution for keeping up with business trends. Big data analyzes the accumulated data to predict changes in the industry trends. Such analytics enables informed decision-making for future marketing strategies. With such an approach, organizations can preemptively create data-driven marketing strategies to adapt to the upcoming changes.
Several customers post reviews online, especially on e-commerce websites. But, manually going through every review and rating and identifying where a product or service is lacking, can be a tedious and slow process. The entire process can be automated to find the average ratings and the most frequent reviews of a product. Also, businesses can implement sentiment analysis on social networks such as Twitter and Facebook to gauge public opinion about a product or the brand as a whole. Collecting consumer feedback will help organizations understand what customers want. Using such feedback, organizations can improve their products and advertise for the improved products with the help of data-driven marketing. Due to such a customer-centric approach, consumers will feel that their voice is being heard and this would positively influence the customer engagement.
The ongoing debate about big data and privacy is raising concerns among several experts as well as consumers. Experts have also said that aggressive data collection may destroy the freedom of anonymity for everyone. Most businesses collect data for ethical practices such as data-driven marketing. But, the potential of using collected data with q malicious intent is always a possibility. The recent Facebook-Cambridge Analytica scandal has shed light upon how data can be used for malicious purposes. Allegedly, Facebook gave away crucial user data to a Russian election analytics firm called Cambridge Analytica. The data was used to manipulate the 2016 United States Presidential election. Due to such incidents, privacy experts and consumers are increasingly paranoid about data privacy and are inclined to distrust major corporate organizations. Lawmakers are trying to address privacy concerns by creating stringent regulations. But, lawmakers themselves are not updated with adequate knowledge about modern technologies and its effects. As evident as it is from Sundar Pichai’s testimony, lawmakers need to be educated about advanced technologies, such as AI and big data, to create effective laws and regulations.
After major data breaches or non-compliance of regulations, consumers find themselves in a tricky situation. They have numerous serious questions after their data is compromised, such as ‘What should I do next?’, ‘Who can be held responsible?’, and ‘How do I protect myself?’ Complex consumer queries need to be answered to maintain a sustainable relationship between customers and businesses. Customers have the right to know who has access to their data and the purpose behind acquiring customer data. In case of any illegal activity, consumers should know who could be held accountable and how they can implement damage control. Hence, organizations have to create a mechanism to ensure accountability across the board.
Another major issue with big data is the presence of data bias. The historical data used for training big data systems is human-generated data. If the data contains biased information, then the bias will also be introduced into the system. The data bias may be based on race, gender, ethnicity, or age. Hence, the output of such systems will be inaccurate. Furthermore, businesses sometimes tend to depend on technologies blindly. If biased data is used to generate data-driven marketing strategies, the result can be disastrous for an organization’s reputation. For example, let’s assume that an online fashion brand is pushing ads to Asian women about ethnic Asian clothing. Asian women may or may not prefer such clothes, but the ads on social media and mobile apps only display Asian attire. Such marketing campaigns may trigger some women and lead to outrage. In such a scenario, the data acquired by the organization’s system could have been biased and the organization was not deliberately pushing such ads. No matter what the cause, the reputation of that company will be adversely affected, regardless.
After looking at some of the biggest data breaches of 2018, anyone would agree that the current security protocols are not robust enough. Crucial data that contains sensitive personal information of millions of people is compromised in multiple major security breaches. Even industry giants that use state of the art security systems have been unable to protect themselves from cyber-attacks. Such high profile security breaches pose a significant threat to customer privacy and the reputation of a business.
When businesses expand by acquiring other organizations or partnering with different firms, they may share crucial data that contains customer information. Such data, when acquired by different organizations, may be used for purposes that are not disclosed to customers. In such scenarios, if the third-party organization gets exposed to a data breach or uses the data for malicious purposes, then customer data is prone to privacy and security risks. Organizations need to ensure that the uglier aspects of data-driven marketing do not outweigh the benefits. For this purpose, businesses can disclose all use cases of customer data clearly in terms and conditions or create a subscription program where consumers can delete their data by opting out. Alternatively, organizations can also implement transparent and decentralized data storage with blockchain for better security standards.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.