Just last week, a client let out a sigh: “We have all this text data (mostly customer reviews) and we know there is tremendous value in that set but outside from reading it all and manually sorting through it, what can we do with it?”
With text becoming a bigger and bigger chunk of a company’s data intake, we hear those questions more and more often. A few years ago, the “number of followers” was about the only metric people would get from their Twitter accounts. Today, we want (and can) know much more; What are people talking about? How do we escalate their complaints? What about the topics trending across data sources and platforms? Those are just some examples of questions we’re asking of NLP (Natural Language Processing) applications at our disposal.
Besides the more obvious social media stuff, there are many areas where text analytics can play an extremely valuable role. Areas like customer support (think of all the ticket descriptions and comments), surveys (most have open-ended questions and their answers often contain the most valuable insights), e-mail marketing (whether it is analyzing outbound campaigns and using text analytics to better understand what works and what doesn’t, or compiling inbound e-mails) and lead-gen (what do people mention when reaching out to you) to name a few. From time to time we even come across more obscure requests like text descriptions of deals made in the past that need critical information extracted (for example contract expiration dates) or comparisons of bodies of text to determine “likeness” (when comparing things like product or job descriptions).
The “common” way to deploy text analytics service today is an API integration. There are quite a few services out there (Alchemy API, Rosette spring to mind) that allow anyone with an account to submit data into their API, and receive back results. While perfectly doable, it means that the customer needs a developer’s/engineer’s capacity and what company has these valued employee sitting around with nothing better to do?
Enter Geneea and their app in the Keboola Connection App Store:
While Geneea also offers API service to exchange data with their Interpretor platform crowned with the Frida dashboard, they early on recognized the potential of the Keboola Connection platform. It is Keboola’s job to remove the complexity (and the need for aforementioned developer time) from accomplishing data tasks. This is why having a strong NLP partner has been one of our key priorities. Check out what they can do with your text here.
Today, we have multiple customers utilizing the app to process text data for the use cases described above. Once your data is managed by Keboola Connection, setting up the text data enrichment with the Geneea app takes less time (actually, about 20% of it) than you just spent reading this blog!
Ready to attack your own text analytics opportunity?
Check out what Geneea wrote about their app on their blog.