How your voice will help you understand data analytics
By Christmas 2016, Amazon’s Alexa was in 4 percent of American homes. Apple’s Siri handles more than 2 billion voice queries each week. And approximately 20 percent of Google search queries on Android devices are executed by voice.
Increasing adoption of voice interfaces like these point to a fundamental shift in how we interact with our devices. In the span of just a few years, we’ve gone from the tyranny of the wired desktop mouse to mobile’s portable touchscreens. In workplaces, we have shifted from manual record-keeping to voice-enabled automated time and attendance management. Not only this, we have also shifted customer relationship officers to the conversational command prompts of chatbots. Now it seems that we’re transitioning again, this time to conversational interfaces synced to the services and data we use.
With the growth of productivity platforms such as Slack, chatbots are especially well-positioned to become common voice interfaces, particularly in the enterprise space. This is great news for people who rely on complex data to do their jobs.
Easier access to the services that enable business has led to an explosion in the amount of data flowing from these interactions.This, in turn, fuels a growing demand for more efficient ways to collate, process, analyze, and access that data. The answer, increasingly, is not to be found in apps at all, but rather in emerging voice interfaces and chatbots that are fast becoming strong business intelligence allies.
Apps as redundant intermediaries
“The product is no longer just an ‘app’ or a ‘website’,” wrote Betaworks’ Matthew Hartman in a recent column. “It’s the brain behind many different instantiations.” Thanks to the rise of APIs and embeddable components, a new generation of technology companies are developing solutions that provide functionality and information access and are platform-agnostic.
Instead of being required to operate in one siloed environment, today’s users have access to a variety of data sources and back-end services that, in many cases, we’re not even aware of.
Speech recognition and machine learning interpret plain language queries and deliver results in a variety of formats. In the past, if you wanted to access complex data analytics in order to make informed decisions, you had to use a variety of services and collate disparate datasets. This process was simplified somewhat with a range of dashboard products that imported this data and delivered a consolidated, visual perspective on your data.
Moving into a post-app world
The next evolutionary step is to leverage machine learning and natural language processing to enable professionals to query these data analytics services by voice or through conversations with chatbots.
Services such as Sisense Everywhere, meanwhile, have integrated their complex data analytics engines with Amazon’s Alexa and Slack, using Sisense’s BI bot framework.
The benefits of this approach include being able to request specific data points using a variety of interface options without needing to scroll through various screens and reports. Demand for platform-agnostic BI is high, with 51 percent of respondents to a recent Sisense study indicating that they’re interested in accessing analytics via voice-activated virtual assistants. In addition, 47 percent were interested in accessing data via productivity tools, and 12 percent via augmented reality.
There is, of course, a big difference between using voice commands to query data and relying on a completely non-visual environment. “Via voice you’re going to get a very thin interaction,” Steve Wilson, Citrix’s VP of core infrastructure, recently told MIT Technology Review. “If you want to go in-depth, you’ll have to look at a screen.”
Users have a tremendous amount of choice when it comes to apps. Each of the major app stores offers literally millions of products. And yet, according to ComScore’s 2016 US Mobile App Report, nearly half of all users download zero apps in any given month.
To make matters worse, app market share is dominated by Facebook and Google, which, between them, account for almost 70 percent of app usage. This leaves a minuscule market share for all other developers to compete over.
The apps that will thrive are those that deliver the most convenient interfaces to the data services that users already favor.
As voice interfaces and chatbots deliver access to a growing array of data-rich services, apps, and even screens, will become less dominant. These trends will become commonplace in the business environment, too.
The proliferation of data that businesses increasingly rely on to make decisions will necessitate more efficient and smarter interfaces to distill useful data points to inform these decisions.
You could be talking to your data sooner than you thought.
Hira Saeed writes about AI, chatbots and Big Data.