How To Twitter Better
With a Histogram in Excel
How’s your Twitter Follower acquisition program going? If you use Twitter as a prospecting tool, you need a convenient system in place to monitor how well your Twitter account(s) are picking up followers. The Histogram in Excel is a tool custom-made for that job. All you have to do is record the total number of new followers that you pick up every day in Excel and then run a Histogram on that data once per month. You can visually compare Histograms from month to month to know immediately which direction your Twitter Follower Acquisition program is going.
What Is a Histogram?
A Histogram divides a large group of dissimilar objects into many smaller groups of similar objects. Excel allows you to arrange the smaller groups in these two ways:
1) By Size of Objects in Group - You can also arrange the groups by the size of the objects in each group. The group on the left will contain objects of the smallest size. Groups to the right contain objects of progressively larger size. This is the type of group arrangement that will be used to monitor your Twitter Follower Acquisition program:
2) By Number of Objects in Group - You can arrange the groups into a Pareto chart. In this case, the groups are arranged by the number of objects in each group. The group with the largest number of objects appears on the left side of the Pareto chart. Groups to the right get progressively smaller:
The embedded video below will provide step-by-step instructions on how to use the Histogram in Excel to monitor your Twitter Follower Acquisition program. Here is the video:
Here is a Step-By-Step Video Showing How to Determine If Your Twitter Follower Acquisition Program Is Getting Better Or Worse By Using An Excel Histogram:
you pick on all of your Twitter accounts every day. It is most convenient to record these daily figures on an Excel spreadsheet as follows:
. The Histogram will divide the overall group of daily follower pickup numbers into many smaller groups that have similar numbers of daily followers picked. The Excel Histogram will produce a number of smaller groups with containing objects (days) of similar size (number of followers picked up in a day). The groups are then arranged on a chart. The groups can be arranged by the size of the objects in the groups or by the number of objects in the groups (a Pareto chart). In this case, the groups will be arranged by the size of objects in the groups. Here is an example of such a Histogram:
each month. Here is an example of a monthly comparison:
You can clearly see that April’s Twitter Follower Acquisition program did significantly better than May’s. Something must have happened between April and May which hurt the Follower Acquisition program. The Twitter account owner needs to figure out what happened that caused the decline. The Excel Histogram makes this comparison quick, easy, and accurate.
Some Tips About Using Twitter for Customer Acquisition
I use Twitter quite a lot for prospecting. I currently have 9 Twitter accounts and, at the time of this writing, acquire about 300 new followers total per day. That’s not so many but I keep it conservative to avoid attracting Twitter’s attention. Here’s what has worked for me so far:. After a Twitter account has acquired 2,000 followers, the 10% Rule applies. The number of people you follow can’t exceed the number of people who follow you by 10%. In other words, if one of your Twitter accounts has reached 2,000 followers, don’t allow the Follows sent out plus the FollowBacks to exceed 200, until more people begin to follow you or you unfollow a few people. It is best to try to keep your tff (Twitter Following / Follower) ratio to be just a tiny bit under 1.10. I use TweetAdder to automatically keep my tff ratio 1.09 or lower for my Twitter accounts that have more than 2,000 followers.
Don’t unfollow anyone for at least one whole day after you begin following them. Twitter views this as churn. That’s a label you don’t want from Twitter. You’d be better off if you never unfollow anyone for at least 2 days, preferably 3. TweetAdder handles this for me pretty easily. The attached TweetAdder video shows how this is done.
If you need to set up more than 10 Twitter accounts, Google “proxy IP address” or “proxy IP server” to find out how. This limit is why I have only 9 Twitter accounts. I’ve heard of people with many more accounts, but it’s risky unless you really know what you’re doing.
. If you have set up multiple Twitter accounts based on derivatives of the same gmail account (joejohnson@gmail.com, joe.johnson@gmail.com, and j.oejohnson@gmail all forward to the same email account but can be used to set up separate Twitter accounts), be aware that if any of those accounts are suspended, all of the accounts will be suspended.
If you are using a tweet automation tool, it is best to tweet no more often than hourly and limit to 10 per day total per account. I use SocialOomph to automate my Tweets at regular hourly intervals during certain times of the day.
If you have multiple Twitter accounts and use an automation tool to Tweet at regular intervals, makes sure that no accounts are tweeting the same thing at the same time. In the past, I’ve had a few Twitter accounts suspended for this reason. I’m much more careful now when I’m setting up the timing, intervals, tweet content, and tweet rotation on SocialOomph. All accounts tweet at different times and with different tweets. The attached SocialOomph video shows how this works.
If you are using Twitter for prospecting, consider automating at least some parts of your Twitter interaction. If you are trying to achieve large numbers of Twitter followers, automation is almost mandatory. I’ve had good luck with the following 3 tools: TweetAdder, SocialOomph, and bit.ly. Here is a little description of each and how I use it, along with a video so you can take a look at how I use these tools.
TweetAdder – TweetAdder automates the following tasks for me:
1) Automates Follows sent and Follow-Backs for each account.
2) Automatically keeps my tff ratio at 1.09 for all of my accounts with more than 2,000 follows.
3) Automatically unfollows anyone who doesn’t follow me back within a time limit that I specify. I usually keep that time limit at 3 days for all accounts.
4) Provides a “safelist” of accounts I’m following that won’t be unfollowed.
5) Creates a “who to follow” list for each account based on any of the following criteria that I specify: Tweet keywords, Profile data, Location, Followers of another user, and Users followed by another user.
6) Allows for completely different settings on each of my Twitter accounts.
7) Can be used to automate tweets but I find that SocialOomph is the best tool for that.
8) Can be used to automatically send replies and direct messages, but I avoid doing this because can come across as “spammy” to recipients.
9) It’s quite easy to use and very intuitive. I probably spend 15 minutes total daily on all 9 of my Twitter account making little adjustments here and there, and then, with the push of 2 buttons, all automated tasks of all accounts run all the way to completion.
Here’s a video to show you how I use TweetAdder to manage Follows and Unfollows for all of my accounts:
Here is a Step-By-Step Video Showing How to Use TweetAdder To Add 300 New Followers to Your Twitter Program Every Day:
If you are interested in TweetAdder, you can click here to check it out. It has a free trial. If you find it useful, there are 4 pay versions that can be purchased with a one-time fee as follows at the time of this writing: Managing 1 Twitter profile - $55, managing 5 Twitter profiles - $74, managing 10 profiles $110, and managing unlimited profiles - $187. I’ve purchased the unlimited version, but I’m only using it to manage 9 Twitter profiles at the moment.
I’ve also heard that another similar tool called Hummingbird does a great job at managing Follows and Unfollows, but I don’t have experience with it so I can’t provide any insight into it. I can say that TweetAdder has done a very fine job for me so far and I’m now averaging about 300 new followers a day with not much effort on my part.
– SocialOomph works great to automate Tweets for all of my accounts. SocialOomph has so many uses that I probably haven’t tapped into even 30% of its functionality, but here’s what it does for me:
1) Schedules tweets for any Twitter account that will continuously repeat themselves at any interval 24 hours or greater that I specify. This makes SocialOomph a real Set-And-Forget tool, if you want that.
2) Creates a series of Tweets that I specify which will be sent out on a rotating basis at the same time every day (or at any interval 24 hours or greater). I use this function to prevent any of my Twitter accounts from sending out the same Tweet at the same time every day.
3) Auto-follows anyone who follows me.
4) Has a very good URL shortening service, but I’ve using bit.ly for a long time and have had good results with bit.ly so I’ll stick with bit.ly.
Here is a short video showing how I use SocialOomph set up a rotating series of Tweets that will be sent out by one of my Twitter accounts at the same time everyday:
Here is a Step-By-Step Video Showing How to Use SocialOomph To Automate Your Twitter Tweets and Get More Followers:
If you are interested in using SocialOomph, click here to try a free version. The free version, however, does not provide the service of recurring tweets, which is the main reason that I like and use SocialOomph. Maybe I’m just lazy but I just love “Set and Forget.” You can easily upgrade from the free version to the pay version.
The pay version of SociaOomph costs $29.97 per month at the time of this writing. I’ve been using the pay version of SocialOomph exclusively to automate recurring and rotating Tweets for all of my Twitter accounts and it’s worked very well so far. Here is a link to SocialOomph if you are interested.
bit.ly – bit.ly is not only great for creating very short URLs but it also provides excellent analytics. I use Google Analytics tracking data to monitor anything happening on my site, but offsite, I use bit.ly to track clicks. I exclusively use bit.ly to track offsite clicks so all of the click-through information is maintained in one place.
To Sum It All Up:
The Excel Histogram is a fast and accurate analysis tool that will immediately tell you whether your Twitter Follower Acquisition Program is improving or not.
A great combination to build a larger Twitter following includes TweetAdder, SocialOomph, and bit.ly.
SocialOomph
7) Don't let different accounts Tweet the same thing at the same time.
6) Tweet no more often then hourly and 10X per day.
5) Take care if you use derivatives of the same gmail account
4) Don’t set up more than 10 Twitter accounts from 1 IP address.
3) Wait at least 2 to 3 days to unfollow anyone.
2) Keep your Following / Follower Ratio to 1.10
1) Limit follows to 350 per account per day.
The maximum allowable number of new Follows per day per account is 1,000. This includes Follows sent out and Follow-Backs. Your best bet is to stay way below this limit to avoid triggering Twitter’s attention. If you limit the daily Follows sent out by any single account to 350 or less, you should have no problem. I use TweetAdder to automatically keep Follows plus Follow-Backs within this limit.First and foremost, play it safe.
Try to stay under Twitter’s radar by not being too aggressive in acquiring new followers. Twitter will suspend accounts if any of its limits are breached. It is now becoming harder and harder to get a suspended account reinstated. The larger of a Twitter following you have, the more you have to lose if Twitter suspends one or more of your accounts. It is probably best to stay well within the limits of the following rules:3) Record each monthly Histogram on an Excel spreadsheet and then compare them
2) Run a monthly Histogram on this data
1) Record the total combined number of new followers
Steps To Using the Histogram to Monitor Your Twitter Follower Acquisition program:
Excel Master Series Blog Directory
Statistical Topics and Articles In Each Topic
- Histograms in Excel
- Bar Chart in Excel
- Combinations & Permutations in Excel
- Normal Distribution in Excel
- Overview of the Normal Distribution
- Normal Distribution’s PDF (Probability Density Function) in Excel 2010 and Excel 2013
- Normal Distribution’s CDF (Cumulative Distribution Function) in Excel 2010 and Excel 2013
- Solving Normal Distribution Problems in Excel 2010 and Excel 2013
- Overview of the Standard Normal Distribution in Excel 2010 and Excel 2013
- An Important Difference Between the t and Normal Distribution Graphs
- The Empirical Rule and Chebyshev’s Theorem in Excel – Calculating How Much Data Is a Certain Distance From the Mean
- Demonstrating the Central Limit Theorem In Excel 2010 and Excel 2013 In An Easy-To-Understand Way
- t-Distribution in Excel
- Binomial Distribution in Excel
- z-Tests in Excel
- t-Tests in Excel
- Overview of t-Tests: Hypothesis Tests that Use the t-Distribution
- 1-Sample t-Tests in Excel
- Overview of the 1-Sample t-Test in Excel 2010 and Excel 2013
- Excel Normality Testing For the 1-Sample t-Test in Excel 2010 and Excel 2013
- 1-Sample t-Test – Effect Size in Excel 2010 and Excel 2013
- 1-Sample t-Test Power With G*Power Utility
- Wilcoxon Signed-Rank Test As a 1-Sample t-Test Alternative in Excel 2010 and Excel 2013
- Sign Test As a 1-Sample t-Test Alternative in Excel 2010 and Excel 2013
- 2-Independent-Sample Pooled t-Tests in Excel
- Overview of 2-Independent-Sample Pooled t-Test in Excel 2010 and Excel 2013
- Excel Variance Tests: Levene’s, Brown-Forsythe, and F Test For 2-Sample Pooled t-Test in Excel 2010 and Excel 2013
- Excel Normality Tests Kolmogorov-Smirnov, Anderson-Darling, and Shapiro Wilk Tests For Two-Sample Pooled t-Test
- Two-Independent-Sample Pooled t-Test - All Excel Calculations
- 2-Sample Pooled t-Test – Effect Size in Excel 2010 and Excel 2013
- 2-Sample Pooled t-Test Power With G*Power Utility
- Mann-Whitney U Test in Excel as 2-Sample Pooled t-Test Nonparametric Alternative in Excel 2010 and Excel 2013
- 2-Sample Pooled t-Test = Single-Factor ANOVA With 2 Sample Groups
- 2-Independent-Sample Unpooled t-Tests in Excel
- 2-Independent-Sample Unpooled t-Test in Excel 2010 and Excel 2013
- Variance Tests: Levene’s Test, Brown-Forsythe Test, and F-Test in Excel For 2-Sample Unpooled t-Test
- Excel Normality Tests Kolmogorov-Smirnov, Anderson-Darling, and Shapiro-Wilk For 2-Sample Unpooled t-Test
- 2-Sample Unpooled t-Test Excel Calculations, Formulas, and Tools
- Effect Size for a 2-Independent-Sample Unpooled t-Test in Excel 2010 and Excel 2013
- Test Power of a 2-Independent Sample Unpooled t-Test With G-Power Utility
- Paired (2-Sample Dependent) t-Tests in Excel
- Paired t-Test in Excel 2010 and Excel 2013
- Excel Normality Testing of Paired t-Test Data
- Paired t-Test Excel Calculations, Formulas, and Tools
- Paired t-Test – Effect Size in Excel 2010, and Excel 2013
- Paired t-Test – Test Power With G-Power Utility
- Wilcoxon Signed-Rank Test As a Paired t-Test Alternative
- Sign Test in Excel As A Paired t-Test Alternative
- Hypothesis Tests of Proportion in Excel
- Hypothesis Tests of Proportion Overview (Hypothesis Testing On Binomial Data)
- 1-Sample Hypothesis Test of Proportion in Excel 2010 and Excel 2013
- 2-Sample Pooled Hypothesis Test of Proportion in Excel 2010 and Excel 2013
- How To Build a Much More Useful Split-Tester in Excel Than Google's Website Optimizer
- Chi-Square Independence Tests in Excel
- Chi-Square Goodness-Of-Fit Tests in Excel
- F Tests in Excel
- Correlation in Excel
- Pearson Correlation in Excel
- Spearman Correlation in Excel
- Confidence Intervals in Excel
- Overview of z-Based Confidence Intervals of a Population Mean in Excel 2010 and Excel 2013
- t-Based Confidence Intervals of a Population Mean in Excel 2010 and Excel 2013
- Minimum Sample Size to Limit the Size of a Confidence interval of a Population Mean
- Confidence Interval of Population Proportion in Excel 2010 and Excel 2013
- Min Sample Size of Confidence Interval of Proportion in Excel 2010 and Excel 2013
- Simple Linear Regression in Excel
- Overview of Simple Linear Regression in Excel 2010 and Excel 2013
- Simple Linear Regression Example in Excel 2010 and Excel 2013
- Residual Evaluation For Simple Regression in Excel 2010 and Excel 2013
- Residual Normality Tests in Excel – Kolmogorov-Smirnov Test, Anderson-Darling Test, and Shapiro-Wilk Test For Simple Linear Regression
- Evaluation of Simple Regression Output For Excel 2010 and Excel 2013
- All Calculations Performed By the Simple Regression Data Analysis Tool in Excel 2010 and Excel 2013
- Prediction Interval of Simple Regression in Excel 2010 and Excel 2013
- Multiple Linear Regression in Excel
- Basics of Multiple Regression in Excel 2010 and Excel 2013
- Multiple Linear Regression Example in Excel 2010 and Excel 2013
- Multiple Linear Regression’s Required Residual Assumptions
- Normality Testing of Residuals in Excel 2010 and Excel 2013
- Evaluating the Excel Output of Multiple Regression
- Estimating the Prediction Interval of Multiple Regression in Excel
- Regression - How To Do Conjoint Analysis Using Dummy Variable Regression in Excel
- Logistic Regression in Excel
- Logistic Regression Overview
- Logistic Regression Performed in Excel 2010 and Excel 2013
- R Square For Logistic Regression Overview
- Excel R Square Tests: Nagelkerke, Cox and Snell, and Log-Linear Ratio in Excel 2010 and Excel 2013
- Likelihood Ratio Is Better Than Wald Statistic To Determine if the Variable Coefficients Are Significant For Excel 2010 and Excel 2013
- Excel Classification Table: Logistic Regression’s Percentage Correct of Predicted Results in Excel 2010 and Excel 2013
- Hosmer-Lemeshow Test in Excel – Logistic Regression Goodness-of-Fit Test in Excel 2010 and Excel 2013
- Single-Factor ANOVA in Excel
- Overview of Single-Factor ANOVA
- Single-Factor ANOVA Example in Excel 2010 and Excel 2013
- Shapiro-Wilk Normality Test in Excel For Each Single-Factor ANOVA Sample Group
- Kruskal-Wallis Test Alternative For Single Factor ANOVA in Excel 2010 and Excel 2013
- Levene’s and Brown-Forsythe Tests in Excel For Single-Factor ANOVA Sample Group Variance Comparison
- Single-Factor ANOVA - All Excel Calculations
- Overview of Post-Hoc Testing For Single-Factor ANOVA
- Tukey-Kramer Post-Hoc Test in Excel For Single-Factor ANOVA
- Games-Howell Post-Hoc Test in Excel For Single-Factor ANOVA
- Overview of Effect Size For Single-Factor ANOVA
- ANOVA Effect Size Calculation Eta Squared (?2) in Excel 2010 and Excel 2013
- ANOVA Effect Size Calculation Psi (?) – RMSSE – in Excel 2010 and Excel 2013
- ANOVA Effect Size Calculation Omega Squared (?2) in Excel 2010 and Excel 2013
- Power of Single-Factor ANOVA Test Using Free Utility G*Power
- Welch’s ANOVA Test in Excel Substitute For Single-Factor ANOVA When Sample Variances Are Not Similar
- Brown-Forsythe F-Test in Excel Substitute For Single-Factor ANOVA When Sample Variances Are Not Similar
- Two-Factor ANOVA With Replication in Excel
- Two-Factor ANOVA With Replication in Excel 2010 and Excel 2013
- Variance Tests: Levene’s and Brown-Forsythe For 2-Factor ANOVA in Excel 2010 and Excel 2013
- Shapiro-Wilk Normality Test in Excel For 2-Factor ANOVA With Replication
- 2-Factor ANOVA With Replication Effect Size in Excel 2010 and Excel 2013
- Excel Post Hoc Tukey’s HSD Test For 2-Factor ANOVA With Replication
- 2-Factor ANOVA With Replication – Test Power With G-Power Utility
- Scheirer-Ray-Hare Test Alternative For 2-Factor ANOVA With Replication
- Two-Factor ANOVA Without Replication in Excel
- Creating Interactive Graphs of Statistical Distributions in Excel
- Interactive Statistical Distribution Graph in Excel 2010 and Excel 2013
- Interactive Graph of the Normal Distribution in Excel 2010 and Excel 2013
- Interactive Graph of the Chi-Square Distribution in Excel 2010 and Excel 2013
- Interactive Graph of the t-Distribution in Excel 2010 and Excel 2013
- Interactive Graph of the Binomial Distribution in Excel 2010 and Excel 2013
- Interactive Graph of the Exponential Distribution in Excel 2010 and Excel 2013
- Interactive Graph of the Beta Distribution in Excel 2010 and Excel 2013
- Interactive Graph of the Gamma Distribution in Excel 2010 and Excel 2013
- Interactive Graph of the Poisson Distribution in Excel 2010 and Excel 2013
- Solving Problems With Other Distributions in Excel
- Solving Uniform Distribution Problems in Excel 2010 and Excel 2013
- Solving Multinomial Distribution Problems in Excel 2010 and Excel 2013
- Solving Exponential Distribution Problems in Excel 2010 and Excel 2013
- Solving Beta Distribution Problems in Excel 2010 and Excel 2013
- Solving Gamma Distribution Problems in Excel 2010 and Excel 2013
- Solving Poisson Distribution Problems in Excel 2010 and Excel 2013
- Optimization With Excel Solver
- Maximizing Lead Generation With Excel Solver
- Minimizing Cutting Stock Waste With Excel Solver
- Optimal Investment Selection With Excel Solver
- Minimizing the Total Cost of Shipping From Multiple Points To Multiple Points With Excel Solver
- Knapsack Loading Problem in Excel Solver – Optimizing the Loading of a Limited Compartment
- Optimizing a Bond Portfolio With Excel Solver
- Travelling Salesman Problem in Excel Solver – Finding the Shortest Path To Reach All Customers
- Chi-Square Population Variance Test in Excel
- Analyzing Data With Pivot Tables
- SEO Functions in Excel
- Time Series Analysis in Excel
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