Teneo Enables DIY Voice Analytics for the Customer

Discover how a conversational AI platform can help improve customer engagement and deliver a vital competitive edge.

Business professionals are turning to DIY voice analytics in order to gain faster insight into data, but without the inclusion of free format text, most users are missing out on the most valuable part.

Gartner’s IT glossary defines the term ‘self-service analytics’ as business intelligence where ‘line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own’. This line of thinking, a DIY approach to BI and analytics, makes perfect sense in the age of fast-paced big data. When dealing with large volumes of complex data, how can you predict which data you will need in advance? If you are a busy business professional, who doesn’t have time to wait for the data science team to generate the data for you, then DIY data is the obvious answer. You download the data, load it into your spreadsheet application of choice, and you are – quite literally – in business.

But can you access the right type of data in the right type of format? A common rule of thumb states that 80% of digital data consists of unstructured data, typically text. However, spreadsheets are notoriously poor at dealing with such text data, which means that most of the data are beyond the reach of most business professionals. And the problems don’t stop there.

Self-service analytics users armed with spreadsheets are not only barred from the biggest volume of data, they are also likely to miss out on the most valuable part. Text data is tremendously rich and contain potentially invaluable insights. The words and sentences from text data are the basis for identifying the voice of the customer. This voice is the key to unlocking the context and meaning behind the neatly ordered rows of numbers found in structured data.

So in the DIY spirit of self-service analytics, how can business professionals be empowered to deal with messy, unstructured text data using a spreadsheet? At Artificial Solutions we take this problem so seriously that we have come up with a solution. As the makers of the Teneo platform, which lets companies build intelligent conversational digital employees as well as other AI interfaces, we specialize in letting businesses collect vast quantities of text data containing those vital customer voices.

But such a collection of data can only provide value when it can be accessed and analysed. Our solution comes as part of the Teneo platform: a purpose-built API for querying text data and transforming it into rows and columns.

For a business professional, the thought of an API for making queries in a bespoke query language might not sound like a great improvement on dealing with unstructured data. But turning business professionals into programmers is not the purpose of the Teneo analytics API.

The Teneo Analytics API lets the IT or data science team set up pipelines and web apps with user friendly buttons and menus. Using such menus, the business professional can slice and dice the data as needed and transform text data using natural language processing and machine learning techniques. And of course, export it all along with contextual data, such as dates or locations. For the business professional, this means access to unstructured data, while letting a self-service user interface take care of the API calls behind the scenes.

Self-service analytics empowers business analysts and managers to make decisions based on the data they need using their tools of choice, without forcing them to become programmers. The Teneo analytics API extends that capability to the voice of the customer, through its powerful query language and access to natural language processing and machine learning for text data.

By enabling business users faster, and more accurate, access to actionable data. Enterprises can not only react swiftly to market changes, but expand into new revenue streams too.

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