Predictive Analytics Pays Off for E-Businesses and Investors

Loraine Lawson
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Predictive analytics is apparently lucrative for businesses, investors and, of course, predictive analytics companies.

In a recent Forbes column, Lutz Finger noted that predictive analytics companies are attracting multi-million dollar investment deals. Most recently, a company called Blue Yonder secured $75 million in funding from a global private equity firm, which is the “biggest deal for a predictive analytics company in Europe….”

If you’re not familiar with Finger, he’s a director at LinkedIn, an expert on social media and text analytics, and the co-founder and former CEO of Fisheye Analytics. The column shares highlights of his interview with Blue Yonder’s CEO Uwe Weiss, so it’s no surprise that it makes the case for predictive analytics as a sound investment.

It’s not a hard case to make. Gartner predicts a compound annual growth rate of 34 percent from 2012 to 2017, and estimates the market will reach $48 billion. To give you an idea of how that compares, Gartner says MDM was worth $1.16 billion last summer.

Finger contends that predictive analytics investments are stable against economic cycles. Because people will continue to buy, even during downtimes, he reasons that predictive analytics will continue to have a place.


“Even in an economic downturn, predictive analytics embedded into critical enterprise processes such as pricing, replenishment, logistics, and supply chain yield management will be cost-effective,” Finger writes. “Predictive analytics will always be needed and indeed the market opportunity here is huge.”

I can’t speak to that except to say that I’ve seen CIOs get mighty stingy about new investments during downturns. They tend to go into “keep the lights on” mode, but I’m sure a solid business case could sway other executives.

Predictive analytics is certainly paying off for e-commerce companies. India’s leading newspaper, the Business Standard, recently examined how four India-based e-commerce sites are using predictive analytics to improve conversion rates.

The article notes that improving sales conversions boils down to a three-step process:

  1. Understand the customer’s shopping mission by tracking the customer’s online path to the e-store.
  2. Define what the customer is likely to buy and how this can be fast-tracked through recommendation. This step is all about personalizing what the customer encounters in the online store.
  3. Set the right shopping context, whether that’s time, location or even weather.

Data

The bulk of the article is devoted to explaining how predictive analytics makes each step possible.

The piece examines in depth how e-commerce sites use mobile apps and APIs to collect data. It’s no big secret that companies do that, of course, but I was surprised to learn that companies can actually collect more valuable data through mobile apps than other means, thanks to a tracking software development kit embedded in the app. The API collects browsing data, buying history and other data about the person’s shopping preference, the piece notes.

"It has more to do with connecting mobile data with personal data and their interaction with the app," Amitabh Misra, chief technology officer for Snapdeal, told the Business Standard.

The article also notes that even when you’re invested in predictive analytics, it can take serious work to turn the data into sales. For instance, e-commerce site Myntra prepared for one sale a month in advance, including conducting an in-depth analysis that lasted over 10 days. The payoff was worth it, though — the site generated 20 times the usual traffic and managed to wrap up a two-day sale in one day.

Loraine Lawson is a veteran technology reporter and blogger. She currently writes the Integration blog for IT Business Edge, which covers all aspects of integration technology, including data governance and best practices. She has also covered IT/Business Alignment and IT Security for IT Business Edge. Before becoming a freelance writer, Lawson worked at TechRepublic as a site editor and writer, covering mobile, IT management, IT security and other technology trends. Previously, she was a webmaster at the Kentucky Transportation Cabinet and a newspaper journalist. Follow Lawson at Google+ and on Twitter.



Add Comment      Leave a comment on this blog post
Feb 26, 2015 1:34 AM Robert Robert  says:
Nice post Loraine Lawson. I really appreciate this. Predictive analysis is what is necessary for investors in case of e-business so to bring success. Reply

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