Editor’s Note: Before I’m accused of navel gazing or self aggrandizement for posting this let me explain why I think understanding the potential of social influence is important for researchers.
First we have the more pragmatic marketing angle: if you are tasked with helping to grow a business then knowing the dynamics of how to utilize all available channels to grow brand awareness is important. And if you want to shape the perception that goes with that awareness then understanding how to maximize influence is also vital; my belief is that influence is the “carrier wave” of brand perception. It’s both a by product and a component.
Second, as researchers we need to understand this topic because it is an important part of brand tracking, A&U, mix modelling, and a host of other research-related practice areas. Social media will only continue to be an evolving disruptive force in marketing, so the more we can get a handle on how it works and can be harnessed for marketing impact, the better we can do our jobs.
Since GreenBook’s mission is to help research organizations grow their businesses and their understanding of emerging tools, using our own industry as a test case makes good sense. In the case of influence tracking we do that annually via our Summer version of the GRIT report via survey-based data collection. Since we’re in that midst of that right now, when Ray suggested an experiment in July to compare new approaches to understanding influence within our industry (at least within the Twittersphere) I thought it was a great idea, and today Ray has unveiled his findings.
This is a snapshot of one defined time period (when I happened to be on vacation, much to my chagrin!) using 4 different approaches to measure relative influence within Twitter. In this post Ray gives a meta analysis of the key findings and links to a longer and deeper exploration of each tool used and it’s findings. It’s a great primer on how marketers and researchers can use these (and other) tools to understand the role and applications of social influence. It’s good stuff; enjoy!
By Ray Poynter
Back in July I asked ‘Who are the most influential market research people on Twitter?’ After some banter we narrowed the question to the #MRX tag and mid-July I asked for nominations. Jeffrey Henning prepared a special version of his #MRX tweeted links report, and we have had input from ColourText, Texifter, and NodeXL.
You can read the full report by clicking here , and the full report includes several links back to much fuller and interactive information form some of the people who have made this report possible.
But here is a meta-analysis of the findings. To produce the list I tabulated who made the top ten of at least one of the lists, counted how often they made the top ten, and ranked them by that. So this meta list is a follows:
A five means the account was identified as ‘influential’ or widely linked or widely reacted to or linked to popular links by most of the routes used in the report. A 1 means the account made one of the top ten lists.
Of course, this does not mean these 27 are the most influential, nor does it mean the people at the top are the most influential, and it does not mean that influence exists in the way it is often assumed to (see this great TED talk by Sinan Aral on this topic).
I’d like to give my thanks to NodeXL, Jeffrey Henning, Texifter, and ColourText for helping produce this report, and to @lennyism for his support in getting the idea off the ground and for helping share the results.