What is Datafication?

Datafication – Turning big data into business solutions

Datafication refers to the collective tools, technologies, and processes used to transform an organization into a data-driven enterprise. After converting processes to data, they can be tracked, monitored, and optimized. Even if data isn’t used, businesses can still acquire large amounts of data, store it, and then decide later on how they will utilize it.

Storing data away for future use is similar to the concept one of “dark data,” which is data that has been ignored up until now because of technological limitations. Gartner defines “dark data” as the information that organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetization). This unused, “dark data” usually comprises the majority of company data assets. Thus, organizations need to take care in what kind of data they store. Storing and securing data can often incur more expense (and sometimes greater risk) than value.

New technologies have enabled lots of new ways to “datify” our normal activities:

GPS devices on smartphones, such as Google maps, are able to track where we are at certain times of the day
Going for a jog/walk – one can monitor distance, speed, pulse, heart rate, number of steps
Sleep schedule – quality of sleep, duration, number of sleep interruptions during the night
Shopping – how much food to purchase, finding lowest prices, monitoring quantities consumed in a household
New smart technologies are making it easier to truly get to know our customers and allow us to make better marketing decisions.

Business examples of Datafication

Netflix

Netflix is a provider of on‐demand Internet streaming media, operating in over 40 countries with some 33 million streaming members. Historically, its operation was more physical in nature with its core business in mail order‐based disc rental (DVD and Blu‐ray). The operating model of Netflix is that a subscriber creates and maintains a queue (an ordered list) of media content they wish to rent (e.g., a film).

With Netflix’s current streaming technology, they are able to gather data based on what the consumer previously watched in order to predict what they will watch in the future, and can suggest titles picked personally for them. Using wide-scale data, Netflix can gather information on what are the most popular shows and movies, who is watching what, and are able to keep their content hip and relevant to what audiences want to see.

Vinted

Tech fashion startup Vinted decided to customize its initial customer onboarding experience by using advertising data. The company tracks dozens of advertising sources and the performance of each ad creative displayed. By funneling data, such as the product image and message displayed, in the ad to the customer, Vinted was able to pull the ad creative shown and generate the onboarding process dynamically when the customer opened the app for the first time. By creating a more contextually relevant in-app experience for new customers, Vinted was able to increase their conversion rates and customer engagement from the onset.

Social media is also a great example of datafication users daily lives:

Facebook datafies our friendships, posts, interests, and locations.
Twitter datafies our followers, following, Tweets, time of day, and interactions
LinkedIn datafies our professional contacts, locations, likes, posts
Business big data allows us to learn things on a large-scale macro level that we couldn’t accomplish in the past.

Facebook ads, for example, are able to target specific ages, locations, genders, interests and more in order to get a company directly in touch with their target market, and not waste advertising money on those that fall outside of that market. Using social media platforms such as Facebook allow companies to gather all of this crucial information from potential customers directly from their profile.

Former market research tactics of focus groups were severely limited – now through the use of datafication, we can scale at a huge rate.

So, what can datafication do for your business?

It's time to ask yourself a few questions:

Are you are using the data sources that you have at your fingertips most efficiently to engage your customers?
How are you best using your advertising data?
How are you best using your in-app data?
How about your partner data?

More and more companies experiment with using customer sourced data and injecting it into apps for contextualizing the customer experience. Good targeting was just the first step. Now we're entering an era where marketers can move large quantities of data around to do boost innovation and contextualize conversations with customers.

Future companies’ marketing effectiveness will be separated by how effectively they are using their customer data. If you haven't already, now is the time to begin taking big steps in connecting your customer data. These actions can help to customize your offer and create a brighter future for your company and for your customers.