Google uses machine learning to fill in the blanks in your spreadsheet

Trying to think of some good uses for this!

Now, with the Smart Autofill add-on, Google is do much more with numbers and words by drawing on its Prediction API, an application programming interface that considers existing numbers or categories and then creates a model to make reasonable approximations.

via Google uses machine learning to fill in the blanks in your spreadsheet | VentureBeat | Big Data | by Jordan Novet.

Why Yahoo Might Have to Buy An Ad Tech Company

Because the products that Yahoo recently announced are not resonating in the online ad marketplace:

In introducing that collection of ad tech offerings, housed under the new brand Yahoo Advertising, the company boasted in a blog post of a “unified approach to digital advertising that only Yahoo can deliver.”The problem is, those products simply aren’t resonating in the online ad marketplace, say programmatic ad buyers and ad tech experts. Hence, the speculation that Yahoo could be in the market to buy some more ad tech.

via Why Yahoo Might Have to Buy An Ad Tech Company – CMO Today – WSJ.

LeadGenius has an army of specialists to find customers, populate your CRM, qualify leads, and even sell

LeadGenius has a small army of sales lead specialists armed with fancy tools to find customers, populate your CRM, qualify your leads, and even reach out to leads with customized pitches. All you have to do is own a CRM system, so you can access the work your mini-sales team is doing for you.Now this does come with a price tag: from $1,999 per month for up to 700 leads to $6,999 per month for up to 2,000 leads.

via LeadGenius grabs $6M because hiring an actual sales team is so last season | VentureBeat | News Briefs | by Kia Kokalitcheva.

One paper by Nobel Prize winner Jean Tirole that every internet user should know

A French economist wins the Nobel in economics.  Matt Yglesias points to another paper written by the winner that discusses the economics of digital media:

But I think many people will be most interested in his 2002 paper “Platform Competition in Two-Sided Markets,” co-authored with Jean-Charles Rochet. Among other things, the paper offers a powerful explanation of why so many leading internet companies — most prominently Google and Facebook — don’t charge for their products.

via One paper by Nobel Prize winner Jean Tirole that every internet user should know – Vox.

 

The Big Mystery: What’s Big Data Really Worth?

The setup: financial accountants are trying to figure out what data is worth on the books:

“It’s flummoxing that companies have better accounting for their office furniture than their information assets,” said Douglas Laney, an analyst at technology research and consulting firm Gartner Inc. “You can’t manage what you don’t measure.”

The Big Mystery: What’s Big Data Really Worth? – WSJ.

An estimate on how much Kroger makes from their data:

Mr. Laney and others estimate that Kroger rakes in $100 million a year from data sales. But Kroger executives are mum on the subject.

It’s too tough to implement an approach where firms are self policing themselves on how they treat data gathering (expense vs. investment).

Among the issues: how to account for time employees spent gathering data—as an expense or a capital investment?

Companies also would have to estimate the shelf-life of their data, figure out its future worth and track and report any changes in its value. Crunching those numbers would be relatively easy for a physical asset like a factory. But in the squishy world of intangibles, there’s little precedent for such calculations.

Ultimately, the quality and value of the data varies from firm to firm.  Additionally, how complementary processes are set up to leverage the data are just as important:

“Data is worthless if you don’t know how to use it to make money,” said Laura Martin, an analyst with Needham & Co. Information on individual users loses value over time as they move or their tastes change, she added. That makes data a perishable commodity and more difficult to value at any given moment.