Posts Tagged ‘public opinion’

This post was inspired by Tuesday’s #SM48 Twitter chat led by Ken Burbary. This particular chat, hosted by Hashtag Media is a weekly gathering of likeminded social media practitioners who discuss a particular topic within social media. This week’s topic was “segmentation”, which fascinated me right off the bat, due to my background in both: traditional and “new media” marketing. During the Twitter chat, we discussed the differences between traditional segmentation vs. segmentation in and via social media channels. The discussion really made me think, as it put an interesting spin on the traditional notion of segmentation.

Traditional marketers have always segmented their users based on a set of common characteristics, thereby creating a customer profile with distinct needs, wants, beliefs, demographics, psychographics, etc. Each segment was assigned its own marketing strategy, with “the 4Ps of marketing” as the underlying framework. Each segment got its own promotional message, through the appropriate media channel (Promotion), sold via an appropriate channel (Place), and sometimes got its own version of the product or product extension (Product) at its own Price. Collecting data to power these insights via traditional market research methods was expensive, and could only be done every so often. Yet, segmentation was the best attempt that we as marketers had to give our customers what they needed, when and where they needed it.

Enter social media. Brands no longer need to ask us what we need, we tell what we want to whoever is listening, and it is my hope that most brands are starting to understand how important listening and engaging is (if you don’t, contact me straight away!). But instead of 10 major customer segments, a brand now has 10 million individuals who have disparate and pronounced needs. How do we segment now? Should we segment down to the individual, or a slightly larger cluster? I believe there’s room for both. We should be listening and analyzing larger trends in our target market’s social media conversations. This will fuel our pricing, product and corporate messaging decisions. Additionally, due to the one-on-one nature of social media, we have the ability to tell our story to the individual in a conversational format. This becomes less about marketing and more about a conversation. Imagine if your friend had a problem, and you offered him / her a solution. Well, this is just like that.

This is what community managers like me do. We scour the social web to find mentions of our brands, our competitors’ brands and product categories. We listen for customers with good brand experiences, bad experiences, and non-customers (these non-customers can be new to the category or just new to your brand). We listen, digest and engage appropriately. What does it mean to engage appropriately? Simply having a conversation within the context of a person’s situation or need. For example, if I hear someone on Twitter saying “I am looking for a an affordable professional social media monitoring solution, competitor X is too expensive”, I can start a conversation with this person about how to get the most out of our tool with the least money. If someone says “I’m looking for a solution that measures sentiment in Portuguese”, I can talk to this person about our foreign language capability. I wouldn’t talk to either person about something that they have no interest in, such as workflow and alerts. Not to say that other features are unimportant; however, when you have 140 characters to make a first impression, it has to be relevant to that person’s expressed needs. Don’t “show up and throw up” and start reciting your company’s top 5 differentiators. Mold your message to the situation and the person. That’s segmentation at its best.

How do you segment your customers? Do you use social media for one-on-one engagement? Do you also let larger trends drive your larger product and strategy decisions? The comments are yours!

Photo source: http://www.flickr.com/photos/thomashawk/2671532954/

To find out how Biz360 can power your insights, visit us here, or get started here. Thanks for visiting!

If you have been following this series of events then you know that for 3 weeks running Biz360 used social media measurement to successfully make Amercian Idol contestant predictions.   

Yesterday at 3:00 pm when we needed to make our finale prediction announcement, there was less than a 1% difference between the final contestants, Adam and Kris.  Many were saying it was too close to call.  But we had promised a prediction and a number of colleagues and clients were making inquiries – we didn’t want to let them down.  After all, the show can’t announce a draw now can they? 

While the difference between the two contestants was small enough that an accurate statistical prediction was impossible due to the limitations of margin of error – we went ahead and predicted Adam Lambert as the winner based on the data we had at the time.

What made this week’s prediction different than those in previous weeks? 

This week was particularly challenging because not only was it an impossibly close margin, but 40% of the source coverage being measured came from Microblogs (mostly Twitter).  The week before for example, consisted of closer to 20% of Twitter-type coverage.  Microblogs are about as real time as it gets, which means it is a dynamic moving target, evolving as public opinion takes shape.

We started out this exploration by asking the question:  Can social media predict American Idol?  At this point if we look back at yesterday’s positive and neutral coverage, Kris did wind up slightly ahead of Adam.   Adam landed at a share of 49.34% while Kris was at 50.66%.  Overall, we believe we have demonstrated that it absolutely can. 

As a side note, a number of people were requesting a Dancing With The Stars finale prediction also.  Yesterday before the finale show, we made a correct prediction analysis for the twitter community using our Community Insights solution. Even though Shawn Johnson was the expected underdog, her social media coverage lead us to predict her to win.

American Idol was a fun vehicle to prove the concept — but imagine the applications for companies.  Throughout this exploration, people continue to be amazed with the idea that we can take thousands and thousands of relevant aggregated posts and conversations, and very quickly consolidate them into real, usable data.   The time period between the performance show and results show is only 24 hours.   Also, the people making these posts are handraisers, volunteering their unsolicited feedback.  So the quality and bias of the consumer opinions is minimal when compared to traditional research methods of gathering feedback.  Our clients are benefitting from this streamlined path to their customers by using Biz360 solutions like Community Insights and Opinion Insights to listen. 

We have helped our clients use the power of social media to assess consumer feedback on product and specific product features.  But I thought it would be fun to see if we could use it to make mainstream entertainment predictions. 

 Answer:  YES, it can!    

We used our Social Media solution, Community Insights, to correctly analyze consumer opinion and predict the last two American Idols to be voted off the show.     Social media measurement is a potent consumer research tool that enables near real-time consumer insights  - I think we have only hit the tip of the iceberg as to how this information can be applied.