Twitter is a medium of the moment. The life-span of a tweet is exceedingly short. If a tweet it is not read quickly after being posted, chances are that it won’t be read at all. The lifetime of a tweet appears to be social media’s answer to the mayfly.
In one of my previous posts, I examined the question “When is the best time of day to tweet?”. It turned out that there was no one universal answer to that question. The best time to tweet depended on what time of day your particular set of followers were active on Twitter. Recent evidence regarding Twitter usage patterns illustrates exactly how important it is to time your tweets so that you are reaching as large and audience as possible.
So what is the effective lifetime of a tweet? Sysomos, a leading provider of social media monitoring and analytics technology, analyzed 1.2 billion tweets to find out how many of them generated some sort of reaction. The key points from the Sysomos analysis:
- 92.4% of all retweets happen within the first hour of the original tweet being published. Thus, if your Tweet is not retweeted in the first hour after it is posted, it probably won’t be.
- 96.9% of @ replies happen within the first hour of the original tweet being published
- 23% of tweets generate replies, while 6% generate retweets.
- Of all tweets that generated a reply, 85% have only one reply. Another 10.7% attracted a reply to the original reply – the conversation was two levels deep. Only 1.53% of Twitter conversations are three levels deep.
The following graph summarizes these important findings:
Like many things in life, on Twitter, timing is everything. If you want your message to be read, to engage your audience, and to be retweeted, you need to know when your followers are online. Every group of followers is different in terms of the periods of peak activity during the day. Remember that:
- A single tweet will only reach a fraction of your followers.
- 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.
New research is underscoring the influence of social networks in marketing. Researchers at Telenor, a mobile phone carrier in Scandanavia, developed a map of social connections based on calling patterns between subscribers to analyze the adoption of the iPhone since 2007. The research showed that an individual with just one iPhone-owning friend was three times more likely to own one themselves than someone whose friends had no iPhones. Individuals with two friends who had iPhones were more than five times as likely to have purchased an iPhone.
What is groundbreaking about this research is not the realization that friends and colleagues influence what you buy, but the unprecedented ability in today’s connected world to track, measure, and quantify the effects of social influence. This newfound capability calls for a dramatic overhaul of the way that businesses determine the value of their customers.
The Lifetime Value of a Customer
Traditionally, determining the lifetime value of a customer has long been the starting point for calculating the ROI of a marketing campaign. The lifetime value of a customer is defined as the net present value of the profit a business will realize on the average new customer over a period of years from that customer’s purchases. This number is critical, because it indicates exactly how much it is worth to acquire a given customer. Armed with this information, a business can manage its marketing programs not as an expense, or for short term profits, but as a long-term business investment.
A New Metric – The Network Value of a Customer
As the research on iPhone adoption illustrates, with the rise in the popularity of social networks, it has become increasingly clear that the true value of a customer goes beyond how much he or she might buy from you directly. Traditional measures of customer value ignore the influence a customer may have on how much others buy. For example, if a customer buys your product, and then, based on his recommendation, three of his colleagues buy your product as well, his effective value to you has quadrupled. On the other hand, if a prospect makes his decision based purely on what others tell him about your product, you will be better off spending your marketing dollars on his colleagues.
The implication for marketers means that the lifetime value of a customer can no longer be considered to have captured the true value of a customer. The advance in the understanding of how social influence effects purchase decisions has lead to the creation of a new metric – the network value of a customer. The network value of a customer is the expected increase in sales to others that results from marketing to that customer.
The Factors That Determine The Network Value of a Customer
Which customers have a high network value? There are few businesses that have access to the kind of data that the Telenor researchers had at their disposal – billions of call records. However, by considering the characteristics of customers that have a high network value, there is data that you can collect that will begin to help you identify and target the customers that you have with the highest network value. The customers with high network value share these common characteristics:
- A high level of satisfaction with your product
- Is highly likely to recommend your product to others
- Is highly connected to other potential buyers
- Is highly influential, an opinion leader
How to Target Customers With High Network Value
Even if you don’t have access to billions of records detailing the social connections and behavior of your customers, like the researchers at Telenor, there is data that you can easily collect about your customers that can help you target the customers that you have with the highest network value. They include:
- Collect a Net Promoter Score from each customer – The metric is simple to collect and straightforward to determine, as described on netpromoter.com:
By asking one simple question — How likely is it that you would recommend [Company X] to a friend or colleague? — you can track these groups and get a clear measure of your company’s performance through its customers’ eyes. Customers respond on a 0-to-10 point rating scale and are categorized as follows:
- Promoters (score 9-10) are loyal enthusiasts who will keep buying and refer others, fueling growth.
- Passives (score 7-8) are satisfied but unenthusiastic customers who are vulnerable to competitive offerings.
- Detractors (score 0-6) are unhappy customers who can damage your brand and impede growth through negative word-of-mouth.
With this one metric you can capture the first two characteristics of a customer with high network value – they 1) have a high level of satisfaction with your product, and 2) are likely to recommend it to others.
- Collect social network information about your customers – many companies are starting to ask customers for their Twitter and/or Facebook usernames, in addition to other contact information such as email address. The very fact that a customer is willing to give you this information is an excellent indicator that the customer is actively involved with you product. In addition, it allows you to invite them to follow/friend you on Twitter and Facebook. Also, in the case of Twitter, it allows you to follow them, and collect vital publicly available information about them that indicates how many friends and followers they have, how many tweets they have made, and their bio. This will give you a measure of the third characteristic of high network value customers – how highly they are connected to other buyers.
- Perform a social network analysis of your Twitter and Facebook followers – you can analyze your own Facebook and Twitter followers to determine which customers:
- have the highest number of connections
- are most likely to pass key marketing messages along to their followers
- have the highest influence and are opinion leaders
This information allows you to fill in the final piece of information you need to get a handle on the network value of a customer – the fourth criterion, whether they are highly influential and an opinion leader. Now you’re ready to start testing and scoring groups of customers according to their network value.
Optimize Your Marketing Programs
Clearly, ignoring the network value of a customer may lead to suboptimal marketing decisions. By collecting the information you need to assess the network value of your customers, you can now model both the likelihood that a given customer will buy from you, and the influence that customer has on other’s buying decisions. Then you can select a subset of your customers, and determine not just how much they will buy from you, but the total amount of revenue that they might generate from their influence over others. This enables you to determine the optimal set of customers to market to that will generate the highest ROI.
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”.