With data and analytics gaining importance in the business world, newer ways of leveraging this valuable resource are constantly being developed, tested, and improved by enterprises. Businesses are using increasingly intelligent tools to analyze the different types of data that are generated by them. The data analyzed by analytics can have multiple sources, such as the business’s operations and processes, its employees, its products, its customers, its market, and anything else that may have even the slightest impact on the organization. However, analyzing the large volumes of data generated and collected by these businesses is not an easy task. It requires the businesses to first clean and sort the data, and then convert it into a usable, structured format. The structured data is then analyzed to derive insights that help businesses plan their actions with greater certainty.
While nearly every business uses some or the other form of data analytics to drive its strategy and operations, there is a lot more data that is available to it that goes unused. This body of unused data can potentially help businesses to gain much deeper insights than the data they already use can. This is the data generated in the form of digital content — documents, audio, social media data, customer communications, reports etc. The sheer volume of this data, while promising valuable business intelligence, also brings with it the daunting task of cleaning, sorting, structuring, and analyzing it. And that is the reason for most businesses being unable to utilize this data. However, with the introduction of technology like AI can unlock the true power of analytics. One way in which it can be achieved is through content analytics.
An introduction to content analytics
Content analytics, as defined by Gartner is, “…a family of technologies that processes digital content and user behavior in consuming and engaging with content, such as documents, news sites, customer conversations (both audio and text), and social network discussions, to answer specific questions.”
Content analytics is the set of tools and applications used by businesses to make sense of the large volume of data generated in the form of digital content across various platforms, primarily the internet. Sources like social media, public websites, and customer communications can provide enterprises with detailed and extensive information about various factors affecting their performance and results. To leverage content analytics, businesses use artificial intelligence tools powered by natural language processing (NLP) capabilities to extract meaningful information. These tools help in spotting hidden trends and subtle patterns that can help businesses uncover the kind of information they’ve never had access to. This helps them solve their biggest problems or enable them to identify new problems that they previously never knew existed.
For instance, analyzing instances of social media mentions and their pages on different platforms can enable businesses to identify previously undiscovered problems in their products or services. Or they can perform a sentiment analysis to know the general opinion about their offerings. Analyzing social media content can also help them recognize emerging trends and customer demands, which can not only help them improve their marketing processes but also redesign and improve their products.
The need for content analytics
Understanding unstructured data
Content analytics leverages technologies like natural language processing to understand content written or recorded in natural language. Since a majority of data on the internet is in the form of unstructured, natural-language content, using content analytics can enable businesses to utilize the major chunk of data that they have been unable to process. And the use of advanced forms of NLP can potentially minimize the need for manually converting the unstructured information into usable insights, and save time and effort for the enterprises. For instance, a business can analyze their customer complaint records to find their customers’ biggest issues and help them solve the identified problems to ensure greater customer satisfaction.
Gaining deeper insights
The unstructured data analyzed by content analytics, such as those from consumer forums and can help businesses gain access to detailed analyses of their products and services. They can use social media analysis to identify the trends that are popular with their target demographic. This can help them devise marketing strategies, campaigns, and offers that are more effective at capturing their target audience’s attention. This will ensure that they invest their resources in the right places and get the maximum ROI.
Establishing a competitive edge
Businesses that have more information always have a competitive edge over their peers. Using insights gathered from various sources to drive their actions enable these enterprises to stay ahead of the curve, even during turbulent periods in the market. Content analytics not only helps businesses gather information regarding their customers, but can also help them to know what other players in their industry are doing. This will not only help them to keep up with the competition but also help them to learn from their competitors’ mistakes. For instance, the insights gained from the social media buzz surrounding a competitor’s failed marketing strategy and the collective response by the audience to the strategy will help a business understand what went wrong. They can then use that knowledge to avoid similar mistakes and create more effective plans.
Thus, using content analytics, businesses can make better business decisions regarding their processes, products, and strategies. This will help them stay relevant to their customers and competitive in their market.
The future of content analytics
While the field of content analytics is just beginning to gain attention in the mainstream market, many leading businesses have already realized its importance. There is also a continuous push to develop newer, better technologies to perform content analytics in a more effective manner. To do so, the existing natural language processing capabilities of artificial intelligence systems must be improved. While NLP technology is quite adept at understanding text in natural language, they are not quite as good as we’d like them to be, for more advanced content analytics purposes. With time, content analytics will also become more adept at gathering insights from more forms of digital content, such as images and videos. This will enable businesses to obtain even more data from online sources.
With the continued spread of digitization, the amount of data generated by people will only increase with time. As people spend more time interacting with digital technology, they’ll generate more content indicating their interests, behaviors, and preferences. This will make businesses invest increasingly in technologies that can interpret different forms of content. It may even lead to an era where digital content and content analytics become the primary sources of market intelligence for businesses.
