Predictive Marketing

On Twitter, Timing is Everything

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.
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How Analytics is Revolutionizing Audience Development

I was recently invited to speak at the IAEE meeting in Boston to shed some light on how analytics can be used to increase attendance at events. In recent years event producers have found it more difficult to attract attendees, due to the rise of the Internet, the growing inconvenience of travel, and an economic recession. As event producers have struggled against these forces, they have in many cases not yet taken advantage of analytic techniques such as data mining, CRM, web analytics, social network analysis, and test and learn strategies to grow attendance levels. My session explored how to apply analytic techniques to radically improve the results of audience development campaigns. I have used these techniques on over 100 conferences, trade shows, and special events to achieve significant increases in attendance.

The topics I covered included the following:

The Lifetime Value of a Customer – A discussion of how to determine the lifetime value of a conference attendee is followed by the an examination of the much more difficult question of how to determine the lifetime value of an exhibit attendee. These attendees usually attend at no charge, and usually generate revenue only indirectly by attracting exhibitors and sponsors. In addition, I review an example of how knowledge of the lifetime value of an attendee can be crucial in decision making.

Closed Loop Marketing – A closed loop marketing system allows event managers to measure the results of all the various components of their audience development programs.  With accurate measurement of program results, they can accurately gauge the ROI of marketing programs, run controlled tests to optimize ROI, and identify key leverage points.

Email Optimization – Email is the keystone of many audience development programs. It is vital to optimize the revenue and response generated by email marketing through a comprehensive testing program. Properly done, email optimization can improve response by 50% or more, and in some cases double or even triple response. The presentation provides examples of how to identify key email test elements, implement carefully designed tests, and analyze the results.

Customer Profiling – Using the information about attendees collected during the registration process, prospects can be targeted with increased accuracy, and the results of marketing programs can be markedly improved.

Predictive Modeling – Moving beyond simple customer profiling, models can be developed that accurately predict which customers are likely to respond to promotions, and which customers are likely to defect. A case study is included on how predictive modeling helped triple conference revenue.

Segmentation Analysis – A highly effective way to identify which customers will respond to which promotions. Event managers can create custom-tailored marketing messages that address the needs of each segment to increase response, lower the cost of customer acquisition, increase retention, and increase cross-sales, up-sales, and referrals. An example of how a segmented campaign increased response by 20% is reviewed.

Web Site Optimization – Small increases in conversion rates can have a dramatic increase in registrations. An example of how minimizing abandonment rates during the registration process helped increase registrations by 30% is discussed.

Social Media Optimization –  Analytics can help event producers amplify the results of their audience development campaign through the optimal use of social media. By mining social networks to identify influential customers and prospects, adding social media profiles to the CRM system, and using predictive modeling to target high probability prospects, an event increased attendance by 30%.

As more event producers take advantage of these analytics techniques, they’ll be able to attract more and better qualified attendees to their events. Face-to-face meetings, the original channel of social media, will remain a vital method of marketing. Here are the slides from the presentation:

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Extend Your Reach on Twitter With Viral Marketing

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”.

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How To Maximize Your Reach on Twitter

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.

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Predictive Marketing