Text analytics mines reams of often ephemeral, unstructured data — from a voice recording of a customer call to emails or a Tweet — for meaningful insights that can inform business decisions, be it a branding strategy or a product launch.
And while retailers have hailed big data as the key to everything from delivering shoppers personalized merchandise offers to real-time metrics on product performance, the industry is mostly scratching its head on how to monetize all the data that’s being generated in the digital era.
One point of departure: Over 80% of all information comes in text format, Tom H.C. Anderson, CEO of OdinText, which markets its text analytics software to clients such as Coca-Cola KO +0.00% told Forbes.
So if retailers, for one, “aren’t using text analytics in their customer listening, whether they know it or not, they’re not doing too much listening at all,” he said.
Anderson and chief technology officer Chris Lehew shared how OdinText’s clients are leveraging what the startup dubs its “next generation” text analytics software, while also putting a few big-data myths to rest.
Myth: Big Data Survey Scores Reign Supreme
“A lot of people think that common structured data, especially survey data, is the gold standard, especially if it comes with a large sample size,” Anderson said. “Many retailers and other businesses glommed onto something called the ‘Net Promoter Score’ about a decade ago when the term was first coined by Bain & Co consulting, and frequently touted as linked to business growth. It was believed this one survey question, ‘how likely are you to recommend our business/service to a friend or colleague?’ asked on an 11-point scale, was the only customer satisfaction number you needed.”