Insight delivery from market research is a very complex process, which is why adding insight equates to adding value for market researchers and marketers. Insights are hardly an automatic result of research and often, it needs human expertise to determine the proper goals, interpret results, or provide common sense checks for solutions.
However, with the entry of technologies like AI, ML, NLP and NLG in the insights and research industry, the very process of insight generation is rapidly changing. These technologies are impacting every area of research right from data collection, analysis to even complex areas like report writing.
Understanding the language of the machines with NLG
Natural Language Generation or NLG is a software process that automatically turns data into human-friendly prose. It consists of techniques to automatically produce human-intelligible language, most commonly starting from data in a database.
NLG takes facts that a machine can understand but a human being cannot, and turns them into a language that humans can understand. It must also be noted that NLG is very different from NLP (Natural Language Processing). The two fundamentally differ in their functions, while the NLG software writes the NLP software reads.
In order for any NLG software to produce human-ready content, the format of the content must be outlined clearly through templates, rules-based workflows, and intent-driven approaches and then fed structured data from which the output is created.
Though there are some limitations, NLG still has useful applications in generating product descriptions from inventory data, creating financial portfolio summaries and updates at scale, BI performance dashboard text explanations and personalized customer communications to name a few.
NLG will define the future of business writing
Whether it is earnings reports, SWOT analysis, or market research, with a template and data in hand, Natural Language Generation can generate business content pieces at scales previously unimagined. According to Gartner by 2018, 20% of all business content will be authored by machines and by 2019, NLG will be a standard feature of 90% of modern business intelligence (BI) and analytics platforms. Forbes and The Associated Press use NLG to generate and publish corporate earnings stories.
NLG will make market research data understandable and useful
One rapidly growing use of NLG is written analysis for BI and analytics platforms. While diagrams, graphs and charts are very helpful when it comes to representing the health of a company, dashboards with complex visualizations can overwhelm users who aren’t data scientists or experts on the specific data set they are viewing.
With tonnes of data to parse through, it is difficult to know what matters or exactly what one needs to know about. NLG provides expert-level analysis and advice in concise, insightful terms to each user regardless of their data expertise. NLG also makes manually writing reports, summarizing and explaining key insights a less daunting task for insights professionals.
Complex personalization at Scale
NLG empowers businesses to generate complex personalization at scale, creating improved customer communication and experience with your organization. For example, retail organizations can send targeted unique offers or financial services firms can deliver portfolio summaries to thousands of clients with each summary using the customer’s unique set of information to speak directly to the individual.
Content delivery at scale
NLG enables users to deliver content at unprecedented speed and scale. Users can generate thousands of content narratives in a fraction of the time it would take to write them manually. The process of writing hundreds of reports by insights professionals is time consuming and expensive.
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With NLG the data for each report can be transferred and converted into insights-rich reports in minutes. The efficiency and speed that NLG delivers is incredibly beneficial to the insights and research industry, especially those who deal with large volumes of data and content.
In its current state NLG still needs human guidance as it cannot not pull unstructured data to generate written text. That said, the market for this technology is all set to explode. According to industry insiders the market for NLG is booming and is all set to reach $1 billion by 2020.
Because businesses today know that time is money and are increasingly looking for ways to leverage technologies that will enable them to save time by doing the heavy lifting work of putting data into usable formats. In the future NLG will expand analytics to a broad audience as well as reduce time and cost for generating insights and content.