You can view your competitors’ activity. Get more active if they are active by bringing out an interesting tweet or information to hold relevant conversation with your followers. This can attract more followers which in turn promotes consumer awareness.

You can monitor the number of your competitors’ followers. You can also infer how much traffic they drive to their sites/blogs with the number of followers they have on Twitter. Put in another way, the higher the number of followers they have, the chances of visits to their sites/blogs by those followers will be greater. To always stay in competition, deliver compelling information to your followers to gain more following and site/blog visits.

Comparing Your Twitter Data Line to Your Competitors

DigMyData generates a timeline graph to compare it to any of your competitors. Let’s assume that you already have linked your twitter account with DigMyData.

Go to Settings |  Twitter in DigMyData.

Click the    icon to add some of your competitors twitter ID to the tracking list.

Click Update to save twitter settings.

Click    Exit Settings to go to the DeepView chart.

Add a new chart set by clicking the    on the DeepView sidebar.

The following screen is displayed:

Enter the name for your new chart set then click Save.

Select the newly created chart set then click Add line to chart set.

Select a twitter configuration from the list to add it to your selected chart set or create a new calculation line using twitter configuration.

Click the newly added twitter line then select Show followers line to have it displayed in the timeline chart. Do this with the other newly added twitter lines for comparison.

In the below example, your twitter and your competitors’ twitter timeline is displayed. This will let you track each timeline over time.

Hugo Lindgren, the editor of the NY Times Magazine, writes:

Ideas, in a sense, are overrated. Of course, you need good ones, but at this point in our supersaturated culture, precious few are so novel that nobody else has ever thought of them before. It’s really about where you take the idea, and how committed you are to solving the endless problems that come up in the execution. The more I experienced this frustration firsthand, the more I came to appreciate how naturally suited I am to the job I used to think I never wanted to have when I grew up. Magazines give me a healthy, satisfying amount of creative license, as well as a very defined responsibility. Journalism keeps my imagination from flying off into the ether. At the core of everything is reporting, a real event. And editing allows me to collaborate with people whose talents make up for my weaknesses, especially writers who don’t seize up at the sight of a blinking cursor.

Mr. Lindgren goes on to describe how John Lasseter of Pixar creates movies:

 Pixar’s in-house theory is: Be wrong as fast as you can. Mistakes are an inevitable part of the creative process, so get right down to it and start making them. Even great ideas are wrecked on the road to fruition and then have to be painstakingly reconstructed. “Every Pixar film was the worst motion picture ever made at one time or another,” Lasseter said. “People don’t believe that, but it’s true. But we don’t give up on the films.”

Ideas are wonderful – but they are only the beginning. Go be wrong! (and then do it right)

Note that when the film was released in 1989, there was no MLB team in Miami. While the writers were not attempting to forecast the future of professional baseball, they knew that  Miami was one of the only major cities in the U.S. without a baseball team. Sure enough, the Marlin’s expansion came to Miami just 2 years after the movie was released. Cubs fans: keep hope! Despite your abysmal 2012 finish, your 104  year drought (the longest in U.S. major sport history) will come to an end in 3 years. Maybe. Probably not.

The truth is, all data in life is in the rear-view mirror. To look into the future, we rely on our understanding of the past. But what if our magic-8 ball is pointing us in the wrong direction?

For example, from Nate Silver’s new book The Signal and the Noise:

Since World War I, no Democrat had won the White House without carrying West Virginia—until, in 2008, Obama won big nationally without coming close in coal country.

From the same article:

“In 2008, Silver’s general election forecast, while perfectly sound, was only a marginal improvement on crudely averaging a bunch of opinion polls. Where he really stood out was in the Clinton-Obama primaries where the unprecedented contours of the race were ruining pollsters’ models. Silver was able to see that in this case, state-level demographic information about race, age structure, and educational attainment could drastically improve forecasts. Putting it together took math, but this was fundamentally a substantive conjecture—and a good one—about the underlying structure of American politics.”

To put it into our own math: Data + deep understanding of the context = accurate forecasting.  DigMyData’s forecasting model is more than taking last year’s numbers and adding 20%.

DigMyData’s will give you the numbers; add your context and make great decisions.

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