Although most of my Cambridge-based colleagues don't want to bring it up, last night's Super Bowl was exactly the spectacle we've come to expect from the nation's most-watched event. We saw hundreds of new commercials (some good and many bad), a crazy half-time show (with a random tightrope walker), and one other thing . . . what was that? Oh, yeah, a football game.

In the weeks leading up to the game, I noticed a trend around the game itself. Dozens of blog posts and news articles claiming they could predict the Super Bowl winner using social media. Although most of these were fluff pieces to fill a slow news week and capitalize on the nation's renewed interest in the NFL, my research skepticism kicked into overdrive with some of them. Not to call anyone out directly, but with all of the PR teams sending me press releases about "predicting" the outcome, I just can't let this slide. So, can social media predict the outcome of the Super Bowl? No.

Each of these predictions came from collecting and analyzing social data. Some predictions came from simple metrics like the volume of mentions around one team against the other. A few of the predictions used the sentiment of mentions — such as a positive mention for the Patriots versus a negative mention for the Giants. And some predictions even used influence calculations to understand how different market segments discussed their favorite teams. In the end, this means that some of the predictions were right and some were wrong. But hey, it was a 50/50 shot anyway. Even with coin-flip odds, it seems that more than half were wrong . . . but that actually distracts from my argument, because even if they guessed right, they were wrong to do so.

Last week at Facebook's developer conference, the massive social network announced a few big changes. Loosely veiled in the enhanced features is a startling amount of new data, giving Facebook even more capabilities to track and learn from consumers sharing behavior, networks, purchases, songs they listen to, and so on.

While there were no direct announcements about what this means for marketers, it's still brought a fair amount of discussion around social marketing, customer data, and the future of consumer privacy online. Last week I tweeted a link to this summary (and pointed out the URL's passive aggressive analysis). But since then, the concerns around Facebook's use of data have only increased. So what does this mean to Customer Intelligence professionals?

The way I talk about customer privacy and social data - the information you can collect and manage from social media channels - is that it's a big, gray, squishy, and constantly moving line. It's not black and white. It's not a thin line. And the overall sentiment about how privacy online works seems to shift constantly. The best thing Customer Intelligence teams can do today is to make sure they're on the right side of that line.

Every summer we play host to the Forrester Groundswell Awards, a contest to find the best examples of social media success. This will be our fifth year running the awards (and my fourth year helping organize and judge entries), and I'm eager to see how far we've come in the industry. To see highlights of previous years, check out this earlier post on past Forrester Groundswell Award Winners.

These awards are a great opportunity for you (or your clients) to get recognized for your work. We publicly highlight the best applications here on the Forrester blogs, announce the winners at Forrester Conferences this fall, and often use many of the winning (and runner-up) entries in our research throughout the year. So if you want exposure for your success, it's an easy way to get your work in front of the masses.

So entering is easy, but how do you win? Here's a list - borrowed from the Forrester Groundswell Awards' creator, Josh Bernoff - to help give you the best chance:

1. Put numbers in your entry to demonstrate that your applications created business value.

2. Include a link to an online site where we can see how your application works.

3. Enter in a category where you can stand out: B2C, B2B, international, or corporate applications, with clear objectives.

4. Start now. The best entries take a while to prepare, and you may need to get your client's permission.

Social influence is one of the hottest issues for Customer Intelligence and Interactive Marketing professionals today. Not a day goes by that I don't talk with marketers or vendors about how to identify, measure, and utilize influential sources online. But for all the interest, there's not much out there defining or standardizing how influencers work — or what online "influence" even means. As a result, I'm kicking off some new research covering how social media makes it possible to find and engage with your brand's influencers. My last research on this subject — now over a year old — is still one of my most-read reports, proving that there's a need for an update.

As luck would have it, thanks to @SarahSGlass, who's a researcher on our Interactive Marketing team and our Customer Intelligence Community Manager, and @Mike_Grant_FORR, we have a perfect venue to open the discussion around social influence: a tweet jam. Yes, "tweet jam" sounds silly, but it's a great way to connect with others and to share and learn about an interesting topic. Our Interactive Marketing team holds a weekly discussion on Twitter, using the #IMChat hashtag, around certain marketing topics and has had great success so far.

As much as I believe in the power of social media data, I've always stood by the fact that if you just monitor social media, you'll only learn about social media. If you want to learn about your customers, you'll have to look at them across all of their varied communication channels.

With this concept in mind, today NM Incite and Clarabridge announced they are joining forces — and data — through an integration partnership. The strategic alliance gives customers the ability to feed NM Incite's social data through Clarabridge's text analytics platform, run sentiment analysis, and combine it with other voice of the customer (VoC) data. This partnership signifies two important areas for Customer Intelligence professionals:

• Successful VoC programs require access to social media. Social media is important in the customer feedback space, but it's not the silver bullet. It is a series of channels to monitor consumer discussion and gain customer insight — but it's just one set of many areas to learn about customers. A complete picture of a customer comes from any of the fragmented ways they communicate — including surveys, chat transcripts, call logs, and more. Just yesterday my colleague Andrew McInnes — our resident VoC expert — published research on the importance of listening to social media as part of the customer feedback process. Check out Andrew's blog for more VoC coverage.