In my last post, I reviewed the ability of some of the most well known Twitter users to extend their reach through viral marketing. One well-known approach to viral marketing is to focus your message on a small number of highly influential people, who will then help to start a word-of-mouth chain reaction that effectively broadcasts your message to a wide audience at a low cost. Using this strategy requires that you can identify the most highly influential individuals in your target market. New research is now available to help facilitate the indentification process. Four researchers at the Max Planck Institute for Software Services recently published a landmark paper investigating how to measure and identify influence in social networks.
Measures of Influence
The researchers focused on Twitter users. With the cooperation of Twitter, they compiled a dataset used for the research that comprised more than 1.7 billion tweets among 54 million Twitter users containing nearly 2 billion follow links.
The researchers compared three different measures of user influence on Twitter:
- Indegree Influence, or the number of followers that a user has, an indicator of that user’s popularity.
- Retweet Influence, the number of retweets in the dataset containing a users’s name, a measure of their ability to propagate a message among their followers.
- Mention Influence, or the number if tweets containing a user’s name, indicating the ability of the user to initiate and maintain conversations with others.
The Million Follower Fallacy
One of the most interesting questions tackled by the study was to what degree the three measures of influence were correlated. The researchers focused on the 6 million most active Twitter users, and ranked each one according to each of the three measures. They then examined the correlation between the rankings, shown in the following table:
Correlation ranges on a scale of -1 to 1; a perfect positive correlation is 1 (meaning that a high rank in one measure tends to occur along with a high rank in another measure); a perfect negative correlation is -1 (meaning that a high rank in one measure tends to occur with a low rank in another measure); no correlation is indicated by a score close to 0. All three measures of influence were positively correlated. However, ties in rank among the lowest ranked in the 6 million active Twitter users artificially generated the relatively high correlation seen in the column “All” in the above table. The researchers therefore isolated the top 10% and top 1% of users based on their number of followers, and examined the correlations between the three measures of influence. The researchers reached the following conclusion:
After this filtering step, the top users showed a strong correlation in their retweet influence and mention influence…This means that, in general, users who get mentioned often get rewteeted often, and vice versa. Indegree, however, was not related to the other measures. We conclude that the most connected users are not necessarily the most influential when it comes to engaging one’s audience in conversations and having one’s messages spread.
This phenomenon has been dubbed “the million follower fallacy” and is one of the most important conclusions of the study: if your goal is to identify the users who are most likely to repeat your message to others in a viral marketing campaign, don’t look for the users in your target market with the most followers, look for the users with the most retweets and mentions.
As you move event further up the rankings, the overlap between the top 100 ranked users according to the three different measures of influence becomes smaller:
There were 233 distinct users that made the top 100 ranking in one or more of the three measures, and 67 that appeared on more than one of the top 100 lists.
Influence Across Different Topics
Another key question the team investigated was whether a user’s influence varied by different genres of topics. To address this question, they examined top-ranked influencers for three different topics which were among the most mentioned during 2009: the Iranian presidential elections, the H1N1 flu virus, and the death of Michael Jackson. Among the set of users who tweeted about any of these topics, only 2%, a set of 13,219 users, tweeted about all three topics, demonstrating the diversity of the topic genres.
Once again, the team looked at the correlations between the rankings on the topics, this time looking specifically at retweets and mentions among the most popular users, as measured by Indegree Influence.
Given the relatively high correlations among the most popular users in their ranks for retweets and mentions across these diverse topics, the researchers concluded that opinion leaders can hold sway over a wide variety of topics. This means that the opinion leaders can help spread a message outside their area of expertise. This is consistent with recent efforts to insert advertising links into popular user’s tweets. The fact that the degree of influence of users is a long-tail (power law) distribution also leads the authors to conclude that it is more economical to target top influentials to kick start a viral marketing campaign, rather than a massive number of less influential users.
How to Become Influential
The team next looked at three groups of users who tweeted about only one of the topics, to determine what factors make ordinary users more influential. These three groups of users had from 3 to 180 times fewer followers than the highest ranked influencers. In comparison to the top ranked influencers across all topics, this set of users that tweeted about only one of the topics saw their influence rise to a much greater degree over an eight month time period in 2009.
This lead the authors to conclude that through concerted effort, and focus on a single topic, users had the greatest chance of increasing their influence over time.
The key findings of the research are as follows:
- It is easier to kick-start a viral campaign by focusing on top influencers, rather than large numbers of individuals with a small degree of influence. This follows from the fact that all three measures of influence fall into a long-tail (power) distribution.
- If you are targeting individuals with a message with a view to extending your reach through viral marketing, the number of followers an individual has is less important than the number of times they retweet, and in turn, are retweeted. The number of followers a Twitter user has may indicate popularity, but this measure has a weak correlation to retweets and mentions.
- The most influential users can hold influence over a variety of topics, as measured by retweets and mentions.
- Ordinary Twitter users can best gain influence by focusing on a single topic, and consistently including links to useful and engaging content in their tweets, as opposed to focusing on conversations with other users.
Like all good research, the analysis presented by the authors suggests further areas for investigation:
- Are the same influence patterns evident in business-oriented communications, as opposed to the general interest topics specifically investigated in this research?
- The research focused on the users with the most rewteets and mentions. The data was not normalized to account for the number of their followers. What patterns emerge when the data is adjusted in this manner?
- Are retweets driven by the influence of the user, the content of the tweet, or the content of the link? If it is driven by all three factors, what is the relative importance of each?
- How can the research be used to predict the outcomes of social media campaigns?
The researchers are currently working with Twitter to make their entire dataset available to researchers. While the dataset is not yet available, you can check their website for updates on their data sharing plan. If and when the dataset becomes available, we can look forward to further detailed investigation of user influence in social media.
One of the many attractions of Social Media is the opportunity to amplify your message through viral marketing. In theory, if you can deliver the right message to a select number of the right people, you can reach thousands, or even millions of people on a shoestring budget. In previous posts, I have analyzed how to maximize the effective reach of your message on Twitter by deploying your tweets during the best time of day to your followers, and repeating that message at strategic times to extend your reach even further. The objective of both of these techniques was to reach as many of your followers as possible with your message. Let’s now examine the opportunity of extending your reach beyond your group of followers through viral marketing on Twitter.
The Lure of Viral Marketing
Every marketer dreams of the following scenario: You convey your message to a select group of individuals. Each of these individuals then repeats your message to one or more of their friends, who in turn repeat the message to one or more of their friends, and before you know it, your message has successfully reached millions of people.
The most recent example of this dream scenario was the Facebook campaign to have Betty White host Saturday Night Live. A 29 year old man from San Antonio started the campaign with the modest goal of gaining 5,000 fans on the Betty White to Host SNL (please?)! Facebook page. He reached his goal in a month and wrote a letter to Lorne Michaels, the Executive Producer of SNL, to encourage the selection of Betty as a host. The story was then picked up by major news agencies. A few months later, the Facebook page had 500,000+ fans, Betty White hosted SNL, and the show grabbed its highest ratings in 18 months.
Viral Marketing on Twitter
Dream scenarios are by definition rare. How much can you reasonably expect to extend your reach beyond your group of followers through viral marketing on Twitter?
The vehicle for viral marketing on Twitter is the retweet. It’s the indicator of how many times your message is repeated throughout the Twittersphere. To get an idea of what the typical results of viral marketing on Twitter are, let’s take a look at what some of the most retweeted users are able to achieve.
I have focused the above analysis on business or news oriented sites, since I am addressing the question of how business marketers can extend their reach through Twitter. Therefore, no celebrities or other non-business entities are included.
The data shows the total number of followers for each user, the average number of tweets they make each day, the largest number of retweets they generated from a single tweet during the week of May 13-19, and an estimate of the % increase in reach they achieved over and above their follower base with their best tweet of the week.
In the calculation of the percentage increase in reach, the analysis makes the assumption that on average, each user who retweets is followed by 300 people. Although 93.6% of Twitter users have less than 100 followers, I’ll use Hubspot’s estimate of an average of 300 followers for the most active 5 million Twitter users. This makes intuitive sense, since the users most likely to retweet are among the most active, and in a long tail distribution the average is higher than the median due to the effect of the users with the most followers.
The data is surprising. I would have expected that the number of retweets would have been much higher for the six users with more than one million followers. Mashable wins the award for most retweets at 1,018. The award for the greatest increase in reach goes to a tweet by HubSpot at 135%, more than doubling its reach via retweets. Although it was only retweeted 159 times, the much smaller number of followers of HubSpot in comparison with Mashable translates into a greater percentage increase in reach.
The data seems to indicate that the users with the relatively smaller following have the opportunity to gain the most in percentage reach. This is not surprising, since for users whose following exceeds one million, there is only so far that they can extend their reach.
The Limits of Viral Marketing on Twitter
The above examples show how much the best tweets of some of the most retweeted users are able to extend their reach via viral marketing on Twitter during a typical week. The two best case scenarios, for HubSpot and Avinash Kaushik, range from a 60% – 135% extension of their reach. In terms of the dream scenario for viral marketing, these gains may not seem like much, but in practical terms, any time that you can increase the effectiveness of your marketing by 60%+, that’s significant.
Twitter is not the best platform for viral marketing. Tweets are ephemeral; they come and go. Twitter lacks the permanence of a blog post or a Facebook page, making it harder to achieve the explosive exponential growth of a true viral campaign. And the dream scenarios of viral marketing are not achieved via a single marketing medium; they are achieved through a perfect storm of mutually reinforcing marketing media. For example, the Betty White campaign was heavily reinforced by traditional news media.
When it comes to Twitter, it may be best to remember Avinash Kaushik’s tweet: “Success on twitter comes fm participating in conversations & adding value. It does not come fm “social media campaigns”.
Tweets are ephemeral. Chances are, unless a person is engaged with Twitter when you tweet, they aren’t going to have the opportunity to read it. Not only do people ignore or lose track of old tweets, they are dropped from the Twitter database. Unlike a blog, which is long-lived and indexed by Google for future reference, tweets are heavily time-dependent. If you’re running a business trying to reach as many customers as possible with your corporate message, the timing and frequency of your tweets are critical to your success.
In a previous post, I examined the question of what time of day is best to tweet. To determine the answer, I analyzed two sets of data representing the behavior of two different groups of followers. It turned out that each group had a different best time of day to tweet, and that a single tweet reached between 10% and 24% of the followers.
That brings up the question: if you employ multiple tweets, what percentage of your followers can be reached? Guy Kawasaki recommends posting your most important tweets 4 times, 8 to 12 hours apart, to reach as many of your followers as possible. Let’s take a look at this question for the same two groups of followers analyzed in my previous post.
A quick review: I collected data over the course of several weeks for two Twitter groups – followers of a company supplying services to event professionals, and followers of a company selling CRM software. The data set consisted of several thousand tweets, including the username, the time and day of the tweet, and the tweet itself. For the purpose of this analysis, I assumed that the best indicator of a given follower’s availability to read tweets was whether or not they had tweeted within a given hour. I was then able to determine for any given hour of the day, how many unique followers were active, and presumably reading their Twitter stream.
To figure out the impact of multiple tweets on reach, I then ranked all of the hours in the day in order of how many unique twitterers there were during any given hour. Choosing each hour in order of priority, I then eliminated duplicates.
The results for the group of event professionals are as follows:
The graph displays the percentage of unique followers that can be reached for each tweet. For example, a single tweet during the best hour of the day can reach 24% of the followers, two separate tweets during the two most active hours of the day, 40%, and three 50%. The graph shows that using Guy Kawasaki’s rule of thumb, that you can reach 60% of your followers with four tweets (we’ll see later that these four tweets should not take place 8 – 12 hours apart). For this group of event professionals, it takes eight tweets to reach 80% of the followers.
Now let’s examine how reach is affected by multiple tweets for the CRM software group:
As you can see, there are dramatic differences between the two groups in the extent to which a given percentage of followers can be reached with the same number of tweets. For example, it takes ten tweets to reach 60% of the CRM software group, compared to the four tweets needed to reach 60% of the event professionals group.
Each group is different. If your business needs to make sure its message is reaching the widest possible audience, you need to develop a similar analysis for your group of followers.
The graphs above show only the number of tweets required to reach a given percentage of followers, but not what times to tweet. The chart below reveals when each tweet should be deployed to achieve the reach shown in the graphs above.
Note that the first three tweets for each group, while not in identical order, occur in the 10:00 AM – 12:59 PM time period. After the first three tweets, the best time for additional tweets varies according to the group. In both cases, Guy Kawasaki’s rule of thumb – four tweets 8 – 12 hours apart – would not maximize reach. To be fair to Guy, his rule of thumb may well work for his group of followers. The point I’m making here is that you can’t generalize – there is a different strategy to maximize reach for each group of followers.
- If you are trying to maximize the effective reach of your message, the ephemeral nature of a tweet puts a premium on the timing and frequency of your tweets.
- A single tweet will only reach a fraction of your followers. For the two groups examined, the range was 10% to 24%.
- By analyzing the times during which your followers tweet, it is possible to develop a strategy to predict the percentage of your followers that you can reach with multiple tweets.
- It is also possible to determine the best times of day for multiple tweets. Note that the muliple tweets don’t necessarily have to take place during one day; they can be spread out over several days so as not to annoy your most attentive followers.
- Every group of followers is different. You need to analyze the tendencies of your followers to determine the optimal strategy for maximizing the reach of your most critical messages.
Twitter has become an increasingly popular and important tool for businesses to keep in touch with their customers. Twitter is a medium unlike any other. Each tweet has a limited life-span – if it is not read within a short time of its being posted, the chances of it ever being read drop exponentially. The constant stream of new tweets from the group of individuals each twitterer is following makes it unlikely that the tweet will be read if it is a few hours old. For few twitterers capture all of their tweets in RSS feeds, or take the time to examine all the latest tweets from more than a handful of individuals. For a business hoping to broadcast a message that is read my the most followers possible, timing is of the essence.
So then, what is the best time of day to tweet? There have been several approaches to answer this question:
- Gary McCaffrey examined the Twitter referrals to his websites and concluded that any time between 9:00AM and 3:00PM is best.
- Malcom Coles claims that according to his survey, 4:01PM is the best time to tweet.
- Guy Kawasaki recommends posting your most important tweets 4 times, 8 to 12 hours apart.
- The Social Media Guide recommends 9:00AM Pacific Time as the single best time to tweet.
- Hubspot’s “State of the Twittersphere” report indicates that global tweets peak between 10:00 PM and 11:00 PM.
As you can see, there are a lot of different opinions about the best time to tweet. In order to develop the best answer possible to this question, I collected data over the course of several weeks for a business whose followers consist primarily of event professionals.
The data set consisted of several thousand tweets, including the username, the time and day of the tweet, and the tweet itself. For the purpose of this analysis, I assumed that the best indicator of a given twitterer’s degree of engagement was whether or not they had tweeted within a given hour. So in order to determine the best time of day to tweet, what is most important is not the number of tweets being posted at a particular time, but the number of unique users posting tweets. Here’s the data, in Eastern Time:
For this group of followers, there are actually two optimal hours to tweet – 10:00 – 11:00 AM and 12:00 – 1:00 PM. Tweets during these two hours reach 23.7% of the total number of followers, an 18% advantage over the next best time, 11:00 AM – 12:00 PM, and a 31% advantage over 1:00 PM – 2:00 PM. These increases in total available audience are highly significant to a business with thousands of followers.
Notice that, for this particular group, a tweet during the hour beginning at 9:00 AM, the beginning of Gary McAffrey’s time window, would only reach an available audience that is two-thirds the size of that available during 10:00 – 11:00 AM and 12:00 – 1:00 PM. Malcolm Cole’s suggestion of 4:01 PM reaches an available audience that is less than half the size – only 41% – of that of the best time to tweet. Guy Kawasaki’s formula of four tweets varied over 8 – 12 hour intervals is a hit-or-miss proposition. In this particular case, the Social Media Guide is right on the money – the hour beginning at 9:00 AM Pacific/12:00 PM Eastern is best.
But does this pattern hold for every group of followers? Or does each group of followers have a unique pattern, a sort of “time fingerprint”? To answer this question, I examined a second group of followers of a CRM company. Here’s the data, once again expressed in Eastern Time:
This group is far different! The group following the CRM company is much more likely to be active during the morning hours, and is more evenly distributed over the entire day. As a result, a tweet to this group reaches a maximum of 10.8% of the total available audience, as compared to the group of event professionals, which peaked at 23.7%. The CRM group reaches its maximum at 11:00 AM – 12:00 PM, rather than the hour before or after, as in the previous case. So while a close approximation, the Social Media Guide guideline of 12:00 PM Eastern Time would for this group reach an audience 17% smaller than the peak time period of 11:00 AM – 12:00 PM.
As these two data sets demonstrate, there is no one best time to tweet for every business. Each business has a unique set of followers with their own Twitter “time fingerprint”. You have to track the habits of your own set of followers in order to determine the best single time of day for your business to tweet.
Develop this graph for your own set of followers. How much different is your group compared to these two?
One of the most important insights from these two examples is that at any given time, you can only reach 10% – 24% of your followers with a single tweet. In a future post, I’ll examine what percentage of a group of followers can be reached with multiple tweets.