What is dark data and how can businesses find customers from dark data

“ Data is the new oil”

                                                  Clive Humby, Tesco

In today’s technology-driven world, data proves to be the most valuable asset of a business besides other assets. A business can’t run its operations without data. The evolution of data has made businesses smarter and more efficient than they were in past. As per Forbes “2.5 quintillion bytes of data flooding out online every day at our pace, but that pace is accelerating with the growth of the Internet”. Data provides a pool of opportunities for businesses to explore and enhance their efficiency. But unfortunately, most of the times businesses focus on processed data ignoring the power that unstructured or raw data holds. Thus, losing their relevance in the competitive market.

According to a recent IBM study, over 80% of all the data generated is dark or unstructured data. It consists of spreadsheets, images, audio files, phone calls, email attachments, inactive databases, employee files, analytic reports and account information. The analogy of the oil for data specifically suites raw or unstructured data that is a raw resource and needs to be refined to extract more value.

Businesses need to harness the power of dark data in order to reach new markets and know their customers. The marketing and advertising sector are totally dependent on the insights they get into the customers’ behaviour and their interaction with the product or brand. Dark data have these useful insights if utilized properly through data analytic tools and software. Let’s have a look at what is dark data and how can it help businesses to find customers.

What is dark data:

Gartner defines dark data as the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing). Companies collect this data from multiple sources – server networks, digital transactions, call records and web traffic to name a few. Dark data can be categorized as

• Untapped Internal Data:
  This is an example of untouched data already present in an organization’s repository and is mostly text-based e-g emails, documents and messages.

• Nontraditional Unstructured Data:
  This data comprises videos, images and audio files that cannot be analyzed through traditional analysis techniques.

• Deep web Data:
  This is the largest body of untapped data generated by academics, government agencies, communities, third-party domains, etc., that is present on the internet and is not indexed.

It is regarded as dark data because the whereabouts of this data is often ambiguous and forgotten. It holds a massive potential to increase the profits of a business as the data is unanalyzed and can provide undiscovered insights. The data that is not important to one department of the business usually is of great importance to the other so it is important to monitor and keep track of the data. Dark data also possess a great threat to businesses as it is very much prone to be hacked.

How data turns into dark data:

Data becomes dark for a variety of reason i.e., it is unstructured, behind the firewall, has dense volume and lack of connection between different sets of data. To analyze the unstructured data, companies need a proper strategy or plan. It is important for a business to enhance and manage the performance of its employs and processes to comprehend the data flooding every minute into their systems. Most of the times companies lack proper tools, expertise and strategy to process the data thus discarding a huge amount of valuable data.

There can also be another reason that is a lack of metadata. Missing metadata, inferior quality or incorrect metadata is the major cause of data not appearing in search queries. Hence the data is transformed into dark data. Data analytics consultants can help businesses in this regard by leveraging useful insights contained in the dark data.

Dark Data Analytics:

Most of the dark data is scattered in a highly unstructured manner across the organization. As a result, it is very difficult to locate and analyze it. However, with the latest technology and software, it can be harnessed and the information it has can be unveiled.Dark data analytics means to analyze everything present on the internet that is not indexed by the search engines (deep web). It also targets raw qualitative data such as emails, text messages, audio, video, customer log files, account information, financial statement, etc. present within an organization. Dark data can be analysed as follows:

1. Discover your dark data:
   The foremost hurdle for businesses to extract full value from the data in their repository is the lack of provenance and accessibility to the right data. Businesses need an improvised data management system in order to bring this dark data into use. It has to be monitored where the data is coming from, who is using it and what it is transformed into. Companies should take the following steps to sort the raw data:
   
   • Collection of metadata from internal and external sources
   • Accumulation of business assets and data to build a business glossary
   • Metadata management
   • Sharing the newly discovered metadata repository with data scientists, business users and data stewards.
   • According to Splunk’s “The State of Dark Data” report, 75 per cent of the business leaders surveyed suggested that if organisations implemented tools that allowed less technical employees to analyze large data sets, it would help them alleviate the dark data problem.
     
2. Generate Trustworthy Data:
   It has to be made sure that the data discovered is not bad data or the data that the organization themselves can’t understand. The data has to be helpful in obtaining insights, making informed business decisions and data strategies. Dark data can only be of value and earn a profit when it is easily discoverable, understandable and accessible. It is possible when businesses have an effective data management system powered by AI and automated tools. The sorting of good data and bad data makes it easy for businesses to trace its origin and where they deliver their value. The data that can easily be traced is authentic and trustworthy data and helps businesses make informed decisions and reduce risks.
   

How can dark data help businesses find new customers

The dark data occupies a considerable chunk of space on an organization’s storage devices. It is better to keep it rather than discarding because it is the source data which may help in determining whether the original processed data is authentic or not. Furthermore, it helps businesses look into their customer’s lives from a different perspective and glean multiple insights. Looking into the raw data is the non-traditional way of analysis which can contain a variety of useful information.

The International Digital Corporation predicts that organizations that can analyze all relevant data and deliver actionable information could achieve an extra $430 billion in productivity gains over their peers by 2021. Companies which do not take advantage of their raw data encounter lost revenue opportunities, lower efficiency, quality issues, and diminished productivity.

Here are some of the ways in which dark data can help businesses:

1. Decipher customer behaviour:
   The pre-eminent advantage of dark data is that it gives insight into different sets of customer behaviour through hidden data that would not have been brought to light. Processed data such as customers’ feedback only gives surface-level information and monitor conscious behaviour. By studying raw data such as surveillance cameras footage, customers interaction patterns with the website or the product, the search history and the media they share on social media can help businesses discover new opportunities. It can help companies to segment audience according to their needs and launch products that appeal to their interest. It also gives a competitive advantage of bringing innovation to the services and enhance the customer experience.
2. Dark and Deep Web helps enhance customer service:
   The data for the deep web can not only help in identifying potential threats but can help businesses to curate competitive intelligence and target scientific research, activist data, or even hobbyist threads.
   The dark web to which notorious connotations are attributed most of the times can surprisingly help businesses especially entrepreneurs to enhance their customer service and introduce customer-friendly features. Surface Web businesses, even giants like Amazon and eBay, could borrow a page or two from a Dark Web vendor’s book. As the deep web is developing at a faster pace than the surface web, it helps businesses set their game up and please customers, giving them the guarantees, the bonuses, good service and discover new markets.