why internet marketing

Sean Gorman is the president and founder of FortiusOne, which brings data and mapping solutions to the mass market through its location analysis software. With FortiusOne’s GeoIQ platform, geo-enabled data is easily shared, visualized and analyzed for more collaborative and better-informed decisions.

The web will continue to generate data at an explosive rate. It will generate even more now that mobile devices have created yet another path to reach that data. For example, mobile traffic alone is predicted to exceed more than two exabytes per month by 2013. There are more than 90 million tweets per day and more than 60 billion images on Facebook. This is just the tip of the iceberg.

Out of this bounty of data emerged “data science” and a plethora of new tools to deal with the size and speed of information. Hadoop, Hbase, Cassandra, MongoDB, NodeJS, Hive, R, and Pig are just a few of the tools and techniques that have emerged to wrestle the growing juggernaut of data. The explosion in new tools and the demand to implement them has far exceeded the number of data scientists available.

When we look at the insight and intelligence that companies like LinkedInclass="blippr-nobr">LinkedIn, Facebookclass="blippr-nobr">Facebook and Twitterclass="blippr-nobr">Twitter have been able to mine about the preferences and behaviors of their users, it is no surprise that data scientists are in high demand. It is not just social media data either — financial, CPG, marketers and even governments are turning to the new skills and techniques to answer new business questions.

The rapid rise in demand and the shortage of trained experts has led to the emergence of tools to democratize access to big data. Innovative startups like Datameer and Factual have simple spreadsheet interfaces for doing basic slicing and dicing. Larger players like Googleclass="blippr-nobr">Google have launched FusionTables to allow slicing and visualization of medium (100MB) data sets.

The Challenges of Big Data/>

This sprawling mass of emerging data brings with it a host of challenges. As we slice and dice data, how do we keep track of the many permutations that it creates? What bits are meaningful and validated? How do we move beyond just counting and binning the data and answer more meaningful questions for businesses?

As a technology community, we’ve done a brilliant job of crowdsourcing data, making its creation and curation a social enterprise. We’ve even made the creation of code social through the open source movement and tools like Github. Yet for all our innovation, we’ve done little to harness the collective class='blippr-nobr'>Internetclass="blippr-nobr">Internet community to analyze the data we create. While our analyses and visualizations are elegant and often beautiful, they are too often built in isolation.

If we were to peer into the not too distant future, how could we use the collective to analyze data and archive its evolution to let others further examine particular pieces of data and run in new directions? Let’s watch an analysis evolve socially as many hands look for patterns across a large data stream.

We’ll start with a chunk of data comprised of all tweets mentioning “Walmart” during Black Friday, November 26, 2010, using hypotheticals. “John” examines the data and extracts all the tweets that came from mobile devices and plots them on a map:

He posts the results and data on his blog so others can extend or tweak the analysis. “Kate,” one of his readers, checks out the data and thinks it looks cool, but finds it too hard to see a pattern with so many dots on the map. Kate then takes John’s data and forks it with her own analysis, counting all the tweets about Walmart in each county:

Seeing Kate’s analysis, another reader, “Bill,” wonders what the relationship is between tweets about Walmart and their store location. How often are Walmart stores nearby when someone is tweeting about Walmart? He finds that 67% of the variation of tweets is explained by the number of Walmarts located in each county.

Another potential reader, “Lauren,” a Walmart Marketing VP, finds this pattern very intriguing. This analysis shows that when a promotion is sent to people discussing Walmart, there is a high likelihood that a store is nearby to redeem it. Next, her mind runs to other variables she could plug into the equation: population, demographics, competitor mix, weather, traffic, etc. She could fuse and filter the collection of contextual data — for example, if someone is tweeting from a mobile device a mile from a Walmart, and the location has a density of 30- to 40-year-old single moms, as well as a forecasted heat wave — in order to target advertisements.

Leveraging these dynamic results, Lauren can query into the inventory analytics and immediately push out a promotion for kiddie pools and squirt guns. She can automate this algorithm to generate new promotions based on the streaming data and adjust to inventory levels in real time.

Answers Included/>

One of the early premises of Web 2.0 was that data would be “the Intel inside” and firms like NAVTEQ that provide data would be the big winners. Today we are seeing crowdsourcing increasingly commoditize data, and projects like OpenStreetMap replacing the NAVTEQs of the world. As the market moves up the chain, the future value will be the meaningful questions we can answer with data. This will mean more focus on the “science” side of “data science.” The more social and collaborative we make the science, the better the answers we’ll create at a scale that is needed for an explosive market.

More Data Resources from Mashable:

- 5 Predictions for Online Data in 2011/> - Facebook vs. Google and the Battle for Identity on the Web [OP-ED]/> - How a Physically Aware Internet Will Change the World/> - What You Need To Know About Data Portability/> - How Online Retailers Can Leverage Facebook’s Open Graph

Image courtesy of iStockphotoclass="blippr-nobr">iStockphoto, fpm

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I am declaring 2011 the Year of the Online SMB.

For the uninitiated, SMBs are small and medium businesses. They are the Holy Grail for business service providers because there are so darn many of them. They account for around 95% of the businesses in the US. (Either that or they supply 95% of the jobs but either way, it's pretty impressive.) I like the definition of an SMB being under 100 employees, but up to 500 employees can be deemed an SMB also. There are no hard and fast criteria for determining SMB status but we all know one when we see one.

Why do we know them? Because they are regular people trying to make their way in life and live the American Dream of being their own boss etc, etc. They are also the business people who wear so many hats that they don't have time to do half the things they need to do to be successful. They are often local business people who still feel that real relationships (ones that might actually involve an in-person look in the eye and a handshake) are important. They also are told by the Internet industry that they need to be doing all the latest and greatest Internet tricks in order to be truly successful.

This last point has resulted in some serious push back and skepticism about Internet marketing by the group, and deservedly so. They are usually fiercely independent—often to a fault. They frequently represent the best (and the worst) of the American entrepreneurial spirit, and they don't like it when someone calls them stupid, which is what the Internet marketing industry does in not-so-concealed fashion. I would say that most times the people saying these things don't even realize how they sound (which is another problem with the industry but I will not address that here).

As a result, SMBs are not as advanced as the Internet Retailer 500s of the world, but they are poised to take full advantage of Google's play into the local space. Google Place Pages, Hotpot, Boost, Tags, and whatever else Google has up its wealthy sleeves are all pointed directly at the SMB market, both B2C and B2B. Get the hint?

Google is entering a mammoth struggle for the SMB marketing budgets with the likes of Facebook, Groupon and others. They are so dedicated to this market that they are even staffing real people (that's right, warm bodies with no chips installed) selling to the SMB market.

All these factors lead to my prediction that 2011 will be the Year of the SMB. Not only will there be enough critical mass to see a real impact for many more small businesses, but there will even be an understanding of just how Google and Facebook's Places concepts will allow SMBs to enter the Mobile Age without having to spend tons of money reinventing their Internet wheel. Have you ever seen how good a fully-optimized Google Place Page looks on an iPhone or Android device? It's pretty cool.

Want another reason I am so confident that this is a safe prediction? It's the influx of Android devices (which are optimized for Google service delivery) that are hitting the market at a rate of 300,000 activations per day. It brought me into a completely other phase of the mobile age as I went from BlackBerry user to Droid X user,now using Google's free Navigation service to put Place Page layers over the GPS directions to see where restaurants and services are. I have even discovered new local businesses in my little town because of this device. I honestly thought I knew about every place here but Google proved me wrong.

Suffice it to say that I am bullish on 2011 being the year that the SMB gets into the full swing of the online marketing world. It's exciting to think about because we need more stories about people from more walks of life than the Fortune and Internet Retailer 50s who are having success online. Those stories are old and recycled to death.

I look forward to 2011 being a year of telling the hundreds, even thousands, of success stories that will help SMBs not only to be more successful but to pull this economy out of the ditch it seems to want to remain in.

What are your thoughts on my prediction?

Originally published on Biznology.

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