DATABERG
Dark Data is usually defined as the information assets organizations generate during regular business activities but generally, fail to use for other purposes. Dark Data is usually characterized as unstructured, scattered, overwhelming, non-stored, and incomplete. As the latest research demonstrates, around 80% of data is no leveraged by companies.
Until recently, the technology was not sufficiently advanced to harness such an enormous amount of data and to access more sophisticated data sources. Today, the situation has drastically changed - we live in an era of innovations and digitalization. The increasing number of companies take advantage of valuable Dark Data, for it provides new insights, creates new revenue opportunities, develops new partnerships, and shifts businesses into the data-driven century.
The data available at an organization represents an essential intangible asset that can be exploited for decision making, both on operational and strategic levels. Data-derived insights have a significant economic impact and value when leveraged correctly and promptly. Using data-derived insights allows us to move from decision making based on intuition to make informed and sound decisions. Leveraging data analytics for decision making can make the difference and set a company ahead of its competitors.
Why is Dark Data a valuable asset?
Dark Data is valuable because it tends to provide information that is not available in any other format. It helps the companies to make efficient decisions in the future based on the analysis of the insights originating in the past. In the end, by exploring hidden datasets, we will be able to nourish our intelligence with new and better insights, and that will become a critical competitive advantage for our business.
Dark Data has the potential to create new revenue sources, streamline processes, and reduce costs. It helps to understand the relationships between apparently unrelated pieces of information.
By exploring the Dark Data and experimenting with in-depth analysis, various insights can be found on businesses, consumers, which may not be possible from data currently in their possession. With access to better data sources and more information, the quality of analytics improves dramatically.
How to transform Dark Data into valuable insights?
Dark Data is different for each industry and individual company, but common examples include network transactions, distributed databases, industrial networks, WiFi technologies, etc.
Overall, it's data that's left behind from processes and is scattered across every level of a business. So, how can a company make better use of this sensed data? Well, it's all about identifying what data can be relevant for our business and putting in place data capturing technologies that allow us to collect these data for processing and transforming it. So in the end, we need to implement the ETL process to these data, to make it ready to nourish our data lakes, BI systems, or advanced analytic tools. That way, we will enlighten this new and highly valuable data stream.
Why is Dark Data important for marketing and sales?
Marketers are placing an extra focus on collecting and assimilating consumer data at every point of contact. While some organizations have mountains of data stored in their data warehouses, the reality is that there are still tons of data being lost during the processes and customer interactions or touch-points. Such Dark Data sources as network transactions or distributed databases can be precious for the marketing/sales department.
Due to the growth of Dark Data, the potential of how this data could impact every element of the marketing is enormous. The ability to access and analyze this data before someone else does will be one of the most significant differentiators of marketers who advance and innovate at speed and at-scale and marketers who don't. Data-driven marketing leaders, compared to mainstream companies, are looking at marketing under a different microscope. Machine learning and big data analytics, coupled with access to the cloud, will become the modern marketer's.
Dark Data analysis helps deeply understand our customer, monitor our service and customer experience, and get the insights needed for the expected hyper-personalization of nowadays consumers. But it can help us also to monitor and manage brand reputation, quantify the impact of your communication and marketing strategies, as well as engage with actual or potential customers directly via micro-targeting.
Developing a robust data strategy can help your company gain a competitive advantage in an increasingly data-driven world. Moreover, Dark Data use enables you to get insights into customer journeys, identify customer dissatisfaction earlier, and solve customer problems faster.
As for product development, data allows marketers to exploit customer insights to develop new products/business models and to optimize pricing schemes. Also, they get a chance to offer personalized products to groups of customers or individuals; leverage data to up- or cross-sell.
Dancing in the dark
With so much information out there to collect, process, and analyze, it is no mystery that the majority of companies are not using data to its full potential. Whether you view Dark Data as an opportunity or a problem, you cannot deny its importance in this digital era.
To start wisely use your Dark Data, think about what you could be missing within all that dark data and create a strategy to find more meaning: set a limit on the volume of data you will measure; think about your current resources and how much you can accomplish with that; create parameters around the channels and a timeframe of data that you will analyze; determine what type of data you need to leverage that to help your business in strategic ways related to the customer experience, marketing, operations, and sales efforts.
