Can Artificial Intelligence Solve Today’s Big Data Dilemma?

Author

Falon Fatemi

March 8, 2017

By now, we know artificial intelligence will be big. The question is: What else will it bring with it?

In the last four years, deals with AI startups jumped from 160 in 2012 to 658 in 2016. Companies are already using it for everything from self-driving cars to remote emotional detection to morality training.

To be sure, those are exciting applications of AI. But there’s a little-known one that, at least for the business world, has even stronger potential to shake things up: It’s called account-based intelligence.

Account-based intelligence is the latest iteration of the age-old one-to-one sales and marketing dream. Jaded marketing and sales executives may scoff, assuming we couldn’t do it then so we can’t do it now. But with AI, we finally have a chance to make it happen.

The Data Dilemma

Today, we’re closer than we’ve ever been toward one-to-one sales and marketing.

Why? For starters, we’re generating more data than ever. Each second, we produce 6,000 tweets, 40,000 Google queries, and 2 million emails. By 2019, global web traffic will surpass 2 zettabytes per year. In layman’s terms, one zettabyte is equivalent to 1 billion terabytes.

Data generation at that scale is the first step toward ABI because it requires granular information about every target company and prospect. But it creates a bigger problem: How can companies possibly dig through that much data for actionable insights?

Well, with good ol’ fashioned Google search and traditional marketing tools, they can’t. The web is just too massive and disorganized for any of us to know what’s out there.

That’s not to say companies haven’t tried. In fact, they’re spending millions of dollars mixing point solutions and data sources, yet conversion rates remain in the low single digits. Thanks to mismatched — and sometimes flat-out false — data, they’re spreading the wrong message to the wrong people at the wrong times.

So what’s a startup on a shoestring budget to do? When money is tight, founders can’t afford to throw it away chasing low-quality leads.

Unfortunately, today, there’s no easy answer. But tomorrow, there might be.

Intelligence At Scale

Until recently, computers struggled to parse unstructured data like Facebook content and YouTube videos. But thanks to recent advances in cognitive computing and processing power, that’s changing.

What does that mean for sales and marketing? Well, information about company leaders’ business decisions, attitudes, and demographics doesn’t come in neat little databases. It’s packaged in social posts, location data, browsing histories, and much more.

Now, the tools are finally emerging to help startup leaders to make sense of this “soft” data:

1. Data crawlers: Data crawlers autonomously mine the web for unstructured data. They examine entities, infer relationships, and ultimately allow you to build prospect profiles. With data decaying by as much as 70 percent per year, it’s essential these programs continuously crawl the web for the most up-to-date information.

How will startups use them to conduct ABI? Let’s say you’re looking for new customers. Crawling the web could reveal a new niche of customers whose demographics align well with current top customers. Those critters just crawled across an untapped market.

Back in 2015, Microsoft acquired Metanautix for this very purpose. Using crawlers, the big data startup sifts through enormous amount of nonrelational data. It then pulls insights from diverse sources more quickly and accurately than humans ever could.

2. Natural language processing: Natural language processing (NLP) examines interactions between computers and humans to pull meaning from conversations. By spotlighting certain words or phrases, NLP analyzes customers’ sentiments toward your brand. Alongside other data points, it can predict which audiences will be most receptive to your message. That’s essential for the “right people, right message” part of ABI.

Want to know what people are saying about your product on social media? NLP can dig into social posts, associate them with certain customer cohorts, and uncover what matters most to each group. You can use this to respond to customer criticisms and compliments, resolve user issues, and improve your product.

Give it a try yourself: AI startup IV.AI allows anyone wanting to test out NLP to use its platform. Type in any word or phrase to learn what emotions it conveys.

3. Machine learning: Machine learning lets computers learn and act without explicitly being programmed to do so. Essentially, it searches for patterns in data to inform program actions, taking into account each user’s context. True ABI requires dynamic models, and machine learning enables them to adjust automatically when new, relevant data comes to light.

Whether you know it or not, you’ve probably already benefitted from machine learning. Facebook uses it to personalize your news feed based on clicks and likes. Other companies employ it to forecast customer loyalty or purchase behaviors, predict product performance, and even forecast risk.

Google Now is probably the most advanced machine learning application yet. It learns user habits, mimics their conversation styles, and provides intelligent recommendations. If, for instance, you need to get to the airport for a flight leaving in 30 minutes, Now might analyze traffic delays and schedule an Uber to get you there in time.

AI is nothing short of amazing. It can find data you never could, distill meaning with startling accuracy, and, when leveraged with ABI, actually give step-by-step directions to your next best customers. It’s going to be the biggest thing in business in a century, and the best part is we’re only just getting started.

 

 

This article was written by Falon Fatemi from Forbes and was legally licensed through the NewsCred publisher network. Please direct all licensing questions to legal@newscred.com.

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