How your company can leverage datafication for growth

Have you ever wondered how Netflix, Hulu, HBO, or other platforms know what you would like to watch? Or how does your favorite supermarket always send you deals on products you love? It is because of datafication.

Every mouse click, keyboard stroke, like, comment, card transaction, or sent email is collected and analyzed. Every daily interaction can be interpreted into data and put to use.

And it is not as scary as it sounds.

Because of datafication, streaming platforms can personalize movies and show recommendations. Farmers can monitor soil conditions and weather patterns; real estate professionals can predict market trends. Athletes can use it for movement patterns and performance metrics for optimizing training and tactics.

In the corporate world, datafication helps businesses make more informed decisions, improve CX, optimize supply chains, and develop products and services.

While this does sound like an intrusion of privacy, datafication can still be effective within the data protection and privacy framework. Responsible and ethical data practices ensure that businesses can gain valuable insights while, at the same time, protecting individuals’ personal information.

In this blog, we will explore examples of datafication across industries. With these examples, we will show how using data can benefit your business. And explain what challenges you may encounter and how to navigate through them.

Firstly, let’s take a step back and define the term datafication.

And no, datafication is not the same as digitalization.

Digitalization is the process of converting analog information into a digital format, for example, making a digital copy of a physical book. Digitalization is how you can get a copy of Pride and Prejudice on your Kindle.

On the other hand, datafication focuses on converting information about our behavior and identity to data for analysis and decision-making.  So, if you’ve previously downloaded Jane Austen books, datafication is how you’ll get Sense and Sensibility recommended.

And as the number of data records grows, businesses are looking for ways to translate those behaviors into practical knowledge.

Making sense of that data and developing, testing, and deploying algorithms can take time. These clusters of information are massive and growing in real-time.

Let me paint you a picture.

In October 2006, Netflix launched a competition, The Netflix Prize, for the best algorithm that can predict user ratings for films. They provided data from approximately 100 million individual movie ratings of 17 thousand movies from roughly 500,000 users. They offered a one-million-dollar prize to the team that can make the company’s recommendation engine 10% more accurate.  

It took winners three years to develop the code.

As said, implementing datafication can be a challenge for all organizations. However, these examples in various sectors demonstrate its potential for business growth:

Until recently, people’s health data was only recorded in medical settings. Now, wearable devices such as smartwatches collect data on physical activity, sleep, heart rate, and more. It helps individuals monitor their health and control their overall well-being.

Probably the most well-known use of datafication is in social media. Social media platforms collect data on user demographics, interests, behaviors, and connections.

This data makes it easier to identify trends and set up advertising campaigns. Knowledge of individual preferences helps deliver personalized content and improves the overall experience.

Datafication has transformed how businesses operate and interact with customers.

Retailers collect extensive customer data like browsing history, purchase patterns, preferences, demographics, and payment information.

With said data, they can deliver personalized recommendations, detect fraudulent transactions, reduce cart abandonment rates, and optimize their marketing strategies.

Predictive analysis helps them forecast demand, allowing them to efficiently plan their supply chain operations and stock products.

Real-time data on traffic, weather, and other factors significantly affect travel and transportation industries.

Examples are numerous.

AI-powered traffic management systems can analyze data from cameras, sensors, and GPS devices to adjust traffic signals, optimize traffic flow, and reduce congestion.

On top of that, drivers can use Google Maps to avoid congested areas and get to their destinations faster. Google uses live data from mobile devices to detect traffic jams, and update suggested routes in real-time.

On the other hand, driverless cars can follow each other at shorter distances with more control, which can reduce traffic congestion. They also share data with traffic management systems for more effective route planning.

Also, ride-sharing companies like Uber analyze and monitor data on trip durations, traffic conditions, and driver availability. That is why they have implemented dynamic pricing models. With higher demand and limited driver availability, prices increase to motivate more drivers to participate. In the same way, during off-peak hours, costs decrease to attract passengers.

Financial institutions can leverage datafication to analyze customer transactions, spending habits, income, and credit history and create risk profiles. These help them manage credit risk and decide customers’ adequacy for loans, insurance, and credit cards.

It can also help banks prevent fraudulent activities and detect and prevent cybersecurity threats, including phishing attacks and malware.

Online education and tools have advanced the use of data in education.  

Each student can have content, pace, and difficulty levels personalized to their needs. And it is easier to identify areas for improvement.

Teachers can use data for curriculum development or streamlining admissions and enrollment processes. It can also analyze teacher effectiveness based on student performance.

HR departments can use data analysis to identify the most effective ways to find and recruit talent.

After finding the talent, next in the process is evaluating candidates. With data-driven analysis, HR professionals can quickly assess candidates’ fit for specific roles and even replace personality tests.

When they hire chosen candidates, it can help them with onboarding, ensuring that they receive the necessary training, resources, and support.

HR departments can use data to set performance metrics (KPIs) and goals for each employee.

As Peter Sondergaard, the founder and executive advisor of The Sondergaard Group, simply put it: “Information is the oil of the 21st century, and analytics is the combustion engine.”

By leveraging big data and data analysis effectively, your organization can:

With data-driven strategies, your business can base its tactics on evidence rather than intuition and guesswork. This leads to more informed and effective choices.

In a situation where you want to launch a new product, datafication can help you in market research and competitor analysis. As you gain new knowledge, you can decide on what strategies to implement during this process.

By analyzing your customer’s behavior, preferences, and needs, your business can help you create personalized and tailored experiences for each customer. In the long run, this can foster stronger connections and increase customer satisfaction and engagement.

You can segment your customers and send them email marketing campaigns relevant to them based on their past behavior and preferences.

Datafication can help your business identify bottlenecks and areas for improvement. That can include anything from process automation, exclusion of unnecessary steps, allocation of resources, or process optimization.

For example, airline companies can use sensors and maintenance records data to predict when equipment needs servicing.

In this ever-changing world, staying up to date with the newest trends can be challenging.

Suppose you predicted that the next big topic in the market is AI. With that information, you can take several strategic actions to respond to those market changes.

First, you would assess the risks associated with AI adaptation, such as security, and implement risk management strategies. Then, you would consider how to integrate AI technology into your products and services. And also adjust your marketing strategies to highlight your expertise.

Leveraging datafication can give your business a competitive advantage when responding to market changes and evolving customer preferences. It can lead to the developing of new products, services, or business models. This data may encourage you to try something new and take your business to another level.

On the other hand, knowing the challenges of datafication is essential so your businesses can maximize benefits while mitigating potential risks.

Here are a few challenges and ways to tackle them:

There are two concepts to explore here.

First are hard rules that apply to all.

As datafication includes collecting various data, this data can consist of personal information such as names, email addresses, locations, and browsing history.

Under privacy legislations, such as GDPR, all organizations must implement transparent opt-in processes that inform individuals about data collection, its purpose, and consent withdrawal. Each country has its own data protection and privacy laws so it’s imperative for businesses, their suppliers, and communication providers to adhere to them.

You must provide clear and transparent privacy policies, adhere to privacy regulations, and safeguard individuals’ privacy rights.

Second, too much personalization can be too personal.

Even though datafication enables your business to create customer profiles based on their activities and behaviors for better target marketing, it can also lead to overly personalized experiences that individuals might find uncomfortable.

This might include ads targeting very specific aspects of your customers’ lives.

For datafication to work, businesses need to accumulate vast databases of personal, private, and sensitive information. It is essential that companies adequately secure these databases.

If not, you can become a target of cybercriminals. They can illegally distribute and misuse information for financial gain, espionage, or other malicious activities.

To mitigate these risks, you must prioritize cybersecurity measures like network security, encryption, and access control. And always keep your security practices up to date.

Data bias can occur when the data sample is not representative, leading to inaccurate conclusions or even discrimination. This can further perpetuate existing social and economic gaps.

This emphasizes the importance of ethical considerations and transparency in developing and deploying data-driven systems.

There are a number of benefits to becoming a data driven enterprise, as well as some challenges along the way.

So, here is a list of the pros and cons of implementing datafication in your everyday business:

With a responsible and ethical approach to datafication, many of these cons can be effectively resolved, ensuring a more beneficial use of data.

Collecting and analyzing data helps you make better decisions, streamline workflows, and improve customer experiences. With our customer data platform, People, you can responsibly collect, unify, store, segment, and analyze data.

Furthermore, with our customer engagement solution, Moments, you can design communication using different channels, goals, metrics, segmented audiences, and more. You can measure the conversion, adjust settings, segment audiences, and analyze the funnel. Moments allow behavior-based communication – depending on your customer activity, you can trigger specific messages on multiple channels with one communication flow.