3 Tips for Expanding Tweet Reach and Engagement

Twitter feeds keep flowing with over 9000 tweets every second (Source: http://www.statisticbrain.com/twitter-statistics/). Unless your followers are constantly watching their twitter stream the chances are that your tweets will not be seen by a lot of them.  Below, I have listed three tips that will ensure that your tweets/content gets noticed and reaches most of your followers.

1. Tweet Same Content Multiple Times in a Day  – There are a lot of people like me who log into twitter few times a day (or after a gap of few days) and then and do a quick scan of timeline (or search).  They go back few hours in their twitter timeline and if your tweet did not happen to be in the timeline or searches at that time then they never see it.  Keeping this in mind, you need to tweet same content multiple times in a day to make sure your tweets are in the timelines of most of your followers when they login to twitter. In my post “Best Time to Tweet”, I suggested following timeline to tweet (this is just a suggestion and you should figure out your own timeline based on your followers and goals)
   1. Tweet at 9:00 AM PST (If all of your follower are in one time zone then tweet at 9:00 AM in your time zone).
   2. Tweet again the same message at 1:00 PST (4:00 EST) – (you might skip this if your followers are local.
   3. Tweet again the same message at 4:00 PST( If all of your follower are in one time zone then tweet at 4:00 PM in your time zone).
   In addition, I suggest adding another one later in the evening.
2. Tweet Same Content on Different Days – If you have content that is evergreen then it make sense to tweet it again. Just like above, it might take few tweets over few days/months to get your tweets noticed by your followers. Additionally, tweeting your content again after few days/months will put your content in front of your new followers and those who might have missed it previously.  However, going overboard with such strategy can potentially cause issues with some of you long time and ardent followers as they will see the same message over and over again. I use this strategy to tweet my old blog posts, which results in new retweets and followers. (I do it automatically- more on this in future).
3. Add Images to your Tweets – Late last year, Twitter started showing full images (instead of a link) in the timeline, just like Facebook does. A study (http://blog.bufferapp.com/the-power-of-twitters-new-expanded-images-and-how-to-make-the-most-of-it) showed that tweets with images got 150% more rewteets than tweets without images.  I suggest, you start including images in your tweets, when it make sense, and do your own tests to see how images affect the engagement with your tweets.

Follow me on twitter at @anilbatra

5 Reasons To Use Google Experiments

Google Experiments is an A/B testing tool that is available within Google Analytics interface.  This post is not about what A/B testing is, why you should conduct A/B tests and what other tools are available but really to make a case for using Google Analytics as your testing platform.  I am not getting paid to write this or have any affiliation with Google. This post is in response to a question I received from a reader of my blog.

1. Free –There is absolutely no cost for the Tool. You can’t beat Free, it is a great way to start with A/B testing and learn about how testing works. I strongly recommend that you try this tool before moving to more sophisticated paid tools. Additionally, if you are just trying to make a case for Testing within your organization then cost does become a barrier and this tools removes that barrier.
2. Easy To Setup – Easy to use wizard allows you to choose the pages to test and setup test parameters.
   
3. Easy Implementation – Once you are done with setting up (point 2 above) the page(s) you want to test, you have to implement some code on your site.  It may sound daunting but that code is very easy to implement. Google provide you the code after your setup is done and all you have to do is stick that on your pages.  Since you already have Google Analytics installed, you are already half way through. Easy setup makes it easy for you to cross the IT/development team barrier.
4. Setting up Objective– If you have already defined the Goals in Google Analytics, you can use them as the objective of your test. During your setup you can pick a goal that you have already defined in Google Analytics as your desired optimization objective. If you have not defined them already then you can quickly define them while setting up your test.
5. Segments – Many tools just gives you the final results based on the data of entire population or based on some predefined segments.  In case of Google Experiments, you can pick Segments that you have defined in Google Analytics and see how each variation is performing for each of your segment. Since not all segments behave in similar fashion this kind of analysis helps you drive even more conversion by understanding which variation of your pages(s) work better for which segments.

Keep in mind that no matter how good your conversions are, there is always a room for improvement and A/B testing helps you with it. As Bryan Eisenberg would say, Always Be Testing.

9 Email Marketing Posts That Are Worth Reading Again

Many old post are still relevant after few years but are hard to find on a blog. So I have gone back and found 9 such blog posts on “Email Marketing” from my blog. Below are these 9 posts:

1. Email Personalization Not Working? Read This
   This posts explains why the email personalization might not work. The bottom line is that you have update your personalization criteria over time and test it.
2. 3 Techniques for Expanding your Email Reach
   Email marketers are facing a tough time with growing emails remaining unopened and unsubscribes. Acquiring new subscribers using old techniques is expensive. In this post I have listed 3 techniques that you can use to spread the word of your emails/newsletters beyond the email list that you are sending the emails to.
3. Are You Depleting Your Email List?
   Email marketers, in order to maximize short term conversions, often bombard irrelevant emails in subscribers inbox However this short term mentality results in erosion of long term viability of their email marketing, due to increase in unsubscribes causing depletion of email lists.
4. 15 Things to Test in your Email Campaign
   This post talks about 15 things you can test today.
5. Targeting Cart Abandonment by Email
   Targeting Cart Abandonment is a great way to drive conversions however, use incentives/offers cautiously.
6. Conversion Tip: Making the Most of the Email Confirmation Thank you Page
   Use your Confirmation page effectively, this posts shows an example of a good page and a not so good page.
7. Number One Email Marketing Mistake
   Number one mistake marketers make with email marketing is to send “Irrelevant” messages to their customers. Find out why this strategy has a far-reaching impact on your email marketing program.
8. 7 Ways to Create Relevancy in Emails
   7 tried and tested ways of creating relevancy in emails are described in this post.
9. Relevancy Matters in Email Marketing
   This post shows an example of an email that missed the opportunity to convert.

Email Personalization Not Working? Read This.

I am a big believer in targeting and personalization and have written extensively about it in this blog. However, targeting and personalization is not “set it and forget it” strategy. It needs to be continually tested to make sure that it is working and driving value. Sometimes you have to test and see if “no-personalization” will yield better results than personalization.

To make my point, let’s take an example:

I get a weekly promotional email from a prominent marketing company. They personalize the email subject line (good so far).
Here are few subject lines

• How [XYZ Company] Should Kickoff New Clients
•  Ensure that [XYZ Company] delivers great PPC campaign
• The rules of online branding that [XYZ Company] needs to know

Note: Instead of [XYZ Company] they use the name of the company I used to work with.

However there is an issue with the way they do personalization. Do you see the issue?

The issue is that they use the name of the company I USED TO WORK FOR. I left that company over a year ago and the subject line is so irrelevant to me that I don’t even open the emails. Though rest of the subject line may be relevant, adding personalization (company name) just makes me ignore that email.

This is a perfect example of why personalization fails.

This can be easily avoided by analyzing the data to figure out which subscribers are not responding to these personalized messages and test a different kind of personalization or completely drop the personalization.

Company names, titles, associations, job roles etc. change and your personalization needs to change when that happens. The key is to actively analyze the data and test.

Do you have any other examples of Failed Personalization? If yes, I would love to see those.

Also see: 7 Ways to Create Relevancy in Emails

One Tip for Enhancing Anonymous Visitor Data

Let’s face it, Web Analytics data is pretty limited when it comes to visitor analysis.  Many of you might have some data on users who have registered or purchased from you and some of you might be connecting the onsite activity of visitors with the other data you have in your database. However, considering that you have less than 10% conversion rate (or registration rate) there are over 90% of the visitors on your site that you have no information on.

Image Source: imnmarketer.com

This is where 3rd party data providers come to your rescue. These data providers can provide a lot of valuable missing data and bridge the gap. Companies like BlueKai and iBehavior can augment anonymous cookie pool or known customer base with additional attributes that you don’t have.
For example, say you have a segment called “Engaged Users” that is all based on anonymous cookies visiting your site and taking certain actions e.g. downloading a whitepaper.   Since it is all cookie based, all you have is their referring information, onsite behavior and browser/OS but you don’t know the mix of gender, income level, kids/no kids, interests etc. within this segment.  Imagine if you had these other attributes about your anonymous visitors then how rich will your analysis and recommendations be.  If you can see the value in richer analysis then it is time for you to start thinking beyond the data you collect.

Also, see 3 Techniques for Expanding your Email Reach

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Analytics Jobs

• Marketing Analyst – Mobile (Zappos.com) Henderson, NV – Zappos.com Inc. Or ITS Affiliates
• Senior Web Analyst Las Vegas, NV – Zappos.com Inc. Or ITS Affiliates

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Books that I am reading or have read recently

1. You Should Test That: Conversion Optimization for More Leads, Sales and Profit or The Art and Science of Optimized Marketing
2. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
3. Data Points: Visualization That Means Something

 

Promotional Codes: Conversion Killers?

Promotional Codes also know as Promo Codes, Discount Codes, Coupon Codes, Offer codes etc, are supposed to drive sales, right? However they can have a reverse action and can actually kill your conversions, if not properly used. Here two examples of discount code implementation that can disrupt customers flow and possibly kill conversion.

1. Pomo Code Box:  A customer who does not have a discount code but comes across a text box/button that asks for one during the checkout process is likely to stop and think.  If a customer does not have any kind of urgency to buy the product, he/she will likely try to look for a discount code online.  If he/she does not find one then chances are that you might lose that conversion.
2. Pomo Codes that are not applied automatically: If you advertise a discount code on your site then go ahead and apply it automatically during the checkout process. Do not ask the customer to fill in the discount code manually.  Many customers don’t read the instructions, and if during check out they don’t see what was promised to them then they will leave.  For example see the Nautica.com screenshot below. They advertised 40% off with a discount code.  As you go through the checkout process, they don’t apply the code automatically. Customers have to take an extra step to enter the code manually.  Do you think all the customers will read the instructions (written in red)?

Here are few things that you can do/test to minimize the cart abandonment due to discount codes:

1. Visible discount Code Box v/s a link to open a discount code box–  Customers who have the discount code might actually find it even though it might not be obvious to other customers (you should test this).
2. Automatically apply the code so that customer can see the actual price he/she will be paying
3. If you are going to provide a prominent discount code then provide a bare minimum discount to everybody (and auto fill it). The code could even be for Free Shipping over $75.00 etc.  The point is make sure that everybody feels like they got something (you should test that).

Also check out

1. 5 Things That Could Be Hindering Your Conversions
2. Are Form Validations Invalidating Your Conversions?

25 Twitter Hashtags Used By Digital Marketing and Analytics Community

Hashtags (keywords that follow #) are a great way to jump to topic and join the conversation on twitter. Below I have complied a list of 25 commonly used hashtags by Digital Marketing and Analytics community that you might want to track as well.

Follow me on @anilbatra

1. #measure
2. #msure
3. #bigdata
4. #analytics
5. #insights
6. #data
7. #emetrics
8. #trend
9. #reports
10. #segmentation
11. #segment
12. #seo
13. #search
14. #ppcchat
15. #cro
16. #landingpages
17. #webdesign
18. #custexp
19. #mktg
20. #marketing
21. #ecom
22. #ecommerce
23. #ecomchat
24. #ux
25. #smdata

Other tags that were provided by the readers of this blog #attribution
 
Let me know if I missed any.
Follow me on at @anilbatra

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Other Twitter Posts:

• Best Time to Tweet?
• Twitter Analytics
• 3 KPIs for Measuring Twitter Success
• All of my posts on Twitter

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Analytics Jobs

• Marketing Analyst – Mobile (Zappos.com) Henderson, NV – Zappos.com Inc. Or ITS Affiliates
• Senior Web Analyst Las Vegas, NV – Zappos.com Inc. Or ITS Affiliates

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Books that I am reading or have read recently

1. You Should Test That: Conversion Optimization for More Leads, Sales and Profit or The Art and Science of Optimized Marketing
2. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
3. Data Points: Visualization That Means Something