It’s for this reason that accuracy is less important for Discovery purposes – as long as the deployed software consistently looks at each comment in the same way, it will quickly highlight prominent words and phrases. The ideal Discovery phase should prioritize speed of analysis above all other criteriaĭiscovery is all about speed – it’s key to understand what people are saying quickly in order to act, especially before your competitors do. That said, there are proven methods to maximize the value in unstructured data. Typos, misspellings, multiple word meanings, language trends and variability of sentence structure are all everyday occurrences that effect how textual data is treated. Instead, an accuracy level of 85-95% is much more realistic and achievable.Įven the most disciplined human could never understand, analyze and categorize every comment accurately every time. Trying to reach 100% accuracy should not be the sole objective of text analytics users – while adjusting and tailoring rules and categories is key for achieving a high level of accuracy, too much interference could actually lead to reduced insight and action from the data set. There are better methods than trying to achieve 100% accuracy in coding Using Maru’s Text Analytics, maximum accuracy is achievable but it needs to be considered in a framework of best practice golden rules for unstructured data analysis.
Speaking to people keen to use automated verbatim analysis tools, they’ve often been promised 100% accuracy from this sort of technology in the past, only to find that this is never the case.Īccuracy is frequently dependent on a number of different factors. When sharing the Maru Text Analytics capability with clients, one of the first questions we are often asked is ‘What level of accuracy can I achieve?”
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