Search engines were revolutionary in the 1990s — the ability to type a query into a box and get relevant results was a novel thing at the time. Nowadays you can easily get the answer to any of your questions without cracking a book, but it hasn’t always been so simple. Such is the progression of technology.
What was once newfangled becomes commonplace after a while.
The paradigm around searching for information is changing again, shifting from typed queries to verbalized ones. Conversational analytics is the next step in search; think of it, akin to the difference between typing a search engine query into your mobile browser vs asking Siri whatever is on your mind.
Here are two ways organizations are using conversational analytics to drive business outcomes.
Understanding E-commerce Customer Behavior
An e-commerce retailer studies certain metrics to help them understand customer behavior. One of these is the bounce rate or the percentage of website visitors who exit a website after visiting a single page. Bounce rate can help merchants determine when a webpage could stand to be optimized, perhaps with a better copy or a more overt call to action.
Here’s another example: Retail companies can get a peek into shopper intent and behavior by analyzing how website visitors use the search bar. What queries do they enter? What products are people seeking? How do they phrase their search queries? How receptive are people to recommendations for similar products?
With conversational analytics, retailers can collect even more data about shoppers’ preferences and behaviors. As Chatbots Magazine points out, web or app analytics can show marketers bounce rate, but “conversational analytics will show you exactly what was last said to make a user leave a chatbot or voice application.”
This form of conversational analytics provides companies with transcripts of real verbal customer interactions, which they can mine to better understand their audiences and provide a more personalized experience.
Empowering Employees to Converse with Data
Conversational analytics is also empowering employees within organizations to converse directly with data, asking questions aloud and receiving answers in seconds. To this end, ThoughtSpot built upon its search-driven analytics capabilities by adding the conversational analytics tool SearchIQ to its platform. This allows users to ask questions in natural language — whether they type the query or speak it.
Research firm Gartner estimates 70 percent of white-collar workers will interact with conversational platforms daily by 2022. It only makes sense that as people turn to digital voice assistants in their personal lives, they’d be open to doing the same in their professional lives.
Even better, deploying voice-driven analytics technology has the potential to help organizations boost adoption rates — an ongoing challenge in the world of analytics — by making it more convenient for members of their workforces to interface with data.
Let’s say a merchandising manager has to make a decision about which products to stock in store for next season and which to feature online. Ordering more than what could be sold can be a costly mistake, so this person turns to the data: “What are the hottest Brand X products this year?” The conversational analytics platform understands this query and produces an interactive chart showing the top 10 Brand X products ranked by sales over the last year. This manager can keep asking questions until they have a clear understanding of product performance by brand, location, color, etc. Then they can use these insights to make an informed purchasing decision.
These are but two of the ways organizations are using conversational analytics to connect employees and data and to better understand customer behavior collected by chatbots.
