Businesses across a range of industries choose to collect data on their customers as a way to provide them better and more useful services. Whether you’re a technology company, a medical company or even a government body, this personalized data can be incredibly useful for creating meaningful and targeted experiences for your users or customers.
Despite data protection laws, many businesses have used underhanded methods of siphoning off customer data to third parties for a quick buck—even with it being a contractual right that consumers agree to the end-user T&C's. When data misuse occurs, it has historically caused much backlash from consumers. As it turns out, people don’t like it much when companies betray their trust. One of the biggest data scandals in this regard occurred with Facebook back in 2018. You may know it as the Cambridge Analytica scandal. Although we will refrain from going into detail here, know that this breach in trust caused nationwide shifts in political attitudes towards data protection regulations, as discussed here in an article by Wharton University of Pennsylvania.
Keep reading for ways in which you can responsibly use your customer datasets to maximize its value for your business—without ending up in the headlines like Facebook or Cambridge Analytica.
For the data you collect to be useful, you need to ensure it is accurate. For instance, you are highly likely to encounter contradictory information when gathering data from multiple sources.
A good example of this comes from the mixing of internal and external datasets. External end-users pay much less attention to the quality of the data they input into forms; whereas, internal employees are more likely to correctly format and organize the data they collect.
Due to this, it is a good idea to segregate these datasets so you can more easily compare information before using it in official company reports. Through cross-referencing, it is also possible to uncover hidden correlations that you would otherwise miss.
Trianz can analyze your data for various attributes. Some of the most valuable attributes include how difficult the collection of said data was, along with how unique it is when compared to other datasets. With proper analysis, you can know the value of your data, before you consider monetizing it.
One of the best ways to maintain high-quality datasets is to have a dedicated data maintenance team. This team will be focused on updating databases and cross-checking information to ensure data integrity. All authorized departments in your business should also be exposed to this data, so you can consider a wide breadth of potential data use-cases.
At Trianz, we can help you to strategically assess changes in your market, and properly implement data maintenance protocols to maximize the value of data you collect and store. Businesses tend to have multiple segregated systems, including CRM, Social Media, Marketing and Finance systems; of which the data can be collated in a centralized manner. With proper planning, you can retain a market focus rather than a product focus to maintain agility in the ever-changing data industry.
With the introduction of laws such as the GDPR, CCPA, and others, it can be difficult for businesses to lawfully maximize the value within collated datasets. A proper understanding of the role and value of data to your business is incredibly important. Without knowing where your data is stored, its relevance to your corporate strategy and its overall value to driving corporate growth, it is certain you will run into problems.
Firstly, it is important to store data about data, what we refer to as metadata. Proper metadata allows you to keep track of where information is stored, and what it means from a business standpoint. This also allows you to determine whether the data is needed or relevant and whether you have consent to store it from whomever the data relates to.
For global enterprises with EU customers, conformity with GDPR regulation is necessary. Customers have the right to access all data you store on them, as well as revoking your right to store their data on your systems. Improper data management can, therefore, wreak legal havoc on businesses that lack proper policies.
As an example, on January 21, 2019, the French National Data Protection Commission (CNIL) issued a €50m fine against US-based tech giant Google. Google’s advertising network was found to be the culprit, with consumers not being informed of data collection that occurred during their browsing sessions.
As you can see, data protection is now at the forefront of worldwide political discussion. Entering a new decade, businesses will have to adhere to strict data regulations in order to comply with new laws like GDPR and CCPA or face hefty fines and consumer backlash.
If you are unsure of how to adapt your business practices, to adhere to these new regulations, get in contact with Trianz at [email protected]. We can help you implement a successful Data Monetization program that fully complies with these new laws.
Contact Us Today
Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
The Cloud is the Key to Transformation Success… Transitioning your applications to the cloud is undeniably a critical factor to a successful digital transformation endeavor. It’s more than just a lift-and-shift, however. Let’s explore several things that you need to consider before migrating your applications to the cloud, including: Readiness of your application portfolio Where to begin – the right business case and migration strategy Technology requirements and considerationsExplore
Application Modernization at Speed and Scale Enterprises are pursuing greater application scalability, cost efficiency, and standardization with containerization and virtualization platforms. So, what’s the difference? Containers are a type of virtualization technology that allows users to run multiple operating systems inside a single instance of an OS. They are lightweight and portable, making them ideal for running applications across different platforms.Explore