In the context of the Quirk’s conference, this post highlights the top changes that artificial intelligence (AI) brings to the text analytics world.
Audrey will be attending “The Meaning Behind the Words: How Advanced Text Analytics Can Uncover Deeper Insights” panel on Feb. 28 at Quirk’s. We find this talk particularly interesting because both speakers Chelsea Gibbons and Isaac Rogers are experts in qualitative data research. Audrey will be tweeting live from the event; follow him on twitter.
How AI-Powered Text Analytics is Different
Inspired by the topic, I wanted to add some of the Keatext expertise into the mix, namely how AI technology changes text analytics. Making the analysis of customer feedback such as open ended surveys and reviews accessible to any company will have dramatic effects in many industries.
Here’s our list of top dramatic changes:
Time to insights
This is the main reason people build machines: speed! Let’s assume it takes an analyst 3 minutes to process a comment, an open ended answers or a review. In comparison, and AI-driven text analytics solution is able to process at least 500 comments/minute.
You may be thinking… the AI is fast, but is it smart? The short answer is yes, see for yourself. We can demo on your own data.
An AI is smart when it uses natural language processing and not a dictionary. This means it can extract information relevant to CX no matter what industry. It will group similar words together, even if a user comes up with a new way of describing a product or a service.
At an average of 25$/h for a data analyst, large studies using qualitative data are inaccessibly expensive to most organizations. AI-driven text analytics is possible at a small fraction of that price. Uncovering insights from unstructured text will become available to any company interested in data-driven decision making.
Depending on the report it may be challenging for managers and executives to see the data for themselves. Manually digging up excel sheets or complicated databases is not what most decision-makers have time for. A sleek interface on a web app changes this dynamic. Once the insights have been uncovered, others can go and see for themselves.
How this will change the business landscape
Evidence-Based Decision Making
Very often product managers have to make decisions based on incomplete data or a hunch. By harnessing the power of AI, product managers have direct access to the thoughts and feelings of consumers. This will allow them to create a feedback loop between the consumer and the product.
Creating a loop between large scale consumer feedback and business decision makers means organizations of any size can become agile. This is sure to propel any business forward, keeping them on track with the kind of innovation that will satisfy customers.
With fast feedback, every change can be measured quickly. How has your re-branding impacted perception? Which feature should your development build next? Was the new service implemented consistent across all your locations? Knowing these things quickly, at a statistically significant level means you can be as lean and reactive as tiny startup, no matter your company size.
This concludes our thoughts on the main benefits of AI-powered text analytics and how these capabilities will change the business landscape. We’re excited to hear what the speakers have to say about the path towards insights.
We’ll be writing up the key takeaways from Quirk’s next week. Watch this space!
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