Why human involvement is still required to move text analytics technologies leveraged with artificial intelligence from the trough of disillusionment to the plateau of productivity
Abstract
The text analytics market, which has been predicted to be worth US$21.7bn by 2025, is falling headfirst into Gartner’s well-known trough of disillusionment by failing to deliver real organisational value and meet user expectations. The might of marketing has duped clients with hyped promises of illusive actionable insights delivered through fast, sexy interfaces, yet the industry is not delivering the value it promises. This paper explores the reasons behind the failure to deliver this expected value. It will define the terms ‘value’, ‘insight’ and ‘actionable insight’. It will use these definitions to identify where and why industry practice fails to meet these fundamental expectations. A short case study is included to provide an example of how emotion analytics of consumer-generated unstructured text data can help deliver meaningful and genuinely actionable insights.
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Author's Biography
Paul Howarth is a world leader in extracting value from unstructured narrative datasets. In 2015, he founded Pansensic and led development of the Hybrid Text Analytics platform that leverages artificial intelligence technologies by teaching the machine with human curated ontologies, keyword sets and conditionalities. His experience is as an innovation, improvement and insight thought leader, having helped major global brands across multiple industries and sectors capitalise on insight extracted from their narrative datasets.
Citation
Howarth, Paul (2020, May 1). Why human involvement is still required to move text analytics technologies leveraged with artificial intelligence from the trough of disillusionment to the plateau of productivity. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 5, Issue 4. https://doi.org/10.69554/FYJS9477.
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