Making Sense of Big Data: Just Say the Words

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When did you wake up last Thursday? Which restaurants did you consider visiting—but didn’t—last week? How many sweaters did you browse before buying the grey one? You may not remember, but someone else does.

Those people are savvy marketers. Businesses are working to harvest as much data about their users as possible. They want a full sweep of demographic and behavioral data on both existing and prospective customers, better known as everyone. While businesses have gotten savvier about collecting and warehousing the data, there’s still a serious gap in understanding the data. What good are reporting tools if they take a Master’s degree to understand?

The idea that voice enabled technologies are about to breakthrough as the next, most important platform is the hot topic in business right now. Brands are working hard to stay on top of the fast moving developments in the space, strategizing integration with voice assistants like Alexa and Google Assistant, honing their “brand voice” and mobilizing their data teams for the oncoming wave of voice data they’ll need to leverage to stay ahead of the competition.

But there is another, possibly even more important development voice technology will bring that is hardly being discussed at all – the advent of voice-enabled analytics.

Much of the conversation at this point focuses on the important fact that voice technology is going to produce a massive influx of voice data that businesses will have to make sense of. And this is true. But fortunately, analytics technologies have largely already caught up to the extent that businesses will be able to store and analyze it all in a way that wouldn’t have been possible just a few years ago.

Voice-enabled analytics are the flipside to this situation. What many haven’t realized yet is that just as voice technology is making life easier for consumers (and producing data at the same time), it will make life much easier for business leaders – as they leverage voice platforms to quickly and simply analyze data that used to require teams of analysts and data scientists to collect and parse.

Imagine a scenario where a fashion CMO needs to know how many sweaters the company sold in certain cities, between specific dates, and what the weather was at the time. A complex ask like that would normally go to the analytics team who would take days, perhaps longer, to collect and analyze the data, and then present it in actionable terms. In a business environment where fast, informed decision-making is critical, traditional analytics still leaves leaders behind the curve a lot of the time.

But with analytics that uses voice technology, the CMO doesn’t need to wait for a team of analysts to come back answers – he or she can gain insights in real time, simply by asking the platform questions with their voice.

The implications for businesses are huge. As the number of sources and the sheer amount of data increases, we have developed much better methods to store and digest it. But the methods for creating actual, usable insights haven’t progressed at the same rate. This leaves businesses leaders who don’t possess deep analytics expertise—which is to say, most of them—with lots and lots of good data on their hands, but totally helpless to leverage that data themselves on the fly. Voice technology would put that power into their hands (or rather, their voice), giving instant, real time results with very little training or technical knowledge needed.

These methods will also solve one of the most persistent problems in data analytics – objectivity.

Today, the queries we use to make sense of our data are still produced by humans, and are therefore still subject to human biases. Data is too often used to confirm what we’re thinking, rather than bring fresh insights we haven’t imagined yet. This creates knowledge gaps between what we think should be happening with our businesses, and what is actually happening in plain fact.

All of this leads up to one critical benefit – faster decision making. With fewer human inputs, analytics technology driven by voice commands will be able to drill down and report the essential facts on the ground, using AI to sort out what’s important, instead of presenting competing scenarios driven by human opinion. Data analytics has already been a game changer for businesses, but voice technology is set to push it even further, making it much more accessible, more useful and more powerful.

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