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

4 Data Ownership Questions You Should Ask: Creating a Culture of Analytics

These days most of the marketing solutions are provided as a service. These solutions send emails on your behalf, server ads on your site , serve your ads on other sites/networks, collect your web Analytics data, collect your social media data, collect usage of customer on social media platforms, trade your cookies etc. You get the idea.

As a result, most of your marketing data resides with 3rd party vendors and outside your company’s environment.  In some case you might have an explicit agreement with the company that allows you to have ownership of your data (e.g. Omniture, ExactTarget etc.) while in other cases you might implicitly assume that you have the ownership of data (e.g. Google Analytics, Facebook etc.).  Either way the data resides with someone else.  This lack of direct ownership of your data could potentially pose a threat to your data driven culture.  I am not saying that all of sudden you will lose all your data (though that is also possible) but there is a potential risk.

Source: http://mimiandeunice.com/2011/01/06/ownership/

In order to ensure that you are in control of the situation, you need to carefully evaluate your “Data Ownership” risks and have a well thought out plan to mitigate the risk. Here are few question you need to ask

1. What if the vendor(s) gets bought by one of your competitors?
2. What if one of the free tools all of a sudden disables your account because of some violation (perceived or actual) of their policy? (See What I Learned When Facebook Disabled My Account)
3. What if the vendor has a data breach?
4. What if you want to move to another vendor?
   1. What will happen to your historical data?
   2. Will you have access to all you historical data? For how long?
   3. Will you be able to port your data into your inhouse system?
   4. Will you be able to port your data into new vendor system?
   5. What will be the cost of porting your data?

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. Below 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.

1. Add social sharing in your emails – Let your loyal email subscribers help you. Add easy social sharing links/buttons to help them tweet, share on Facebook, linked in etc. If they like something in your email they will share it with their followers and friends. This will not only spread your messages but also will provide you with new subscribers.
2. Segment differently – If you are doing segmentation to send emails, it is possible that you might be able grow the list of people in your segment by thinking beyond your current segmentation criteria. For example if you are sending a particular emails to who have listed their title as “Web Analyst”, you can extend the list by looking for subscribers who have not listed themselves as “Web Analyst” but exhibited behavior that looks like “web analysts” e.g. downloaded a whitepaper on tag management.
3. Find Look Alike Using 3rd Party Data – You can go beyond emails and use 3rd parties to find “Look Alikes” of your loyal subscribers/customers. Find you loyal email subscribers/customers based on email opens/clicks/conversion and use their cookies to find more people like them using 3rd party cookie matching solutions such as BlueKai, i-Behavior etc. (Make sure not to cross the privacy lines when using these services).

“Email-Marketing” image is copyright by ePublicist and made available under a Attribution-NoDerivs 2.0 Generic license. Source: http://www.flickr.com/photos/epublicist/8585152039/sizes/l/in/photostream/

I would love to hear about other techniques that you might be using.
Related posts

1. Are You Depleting Your Email List?
2. Number One Email Marketing Mistake
3. 7 Ways to Create Relevancy in Emails

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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
• Data Analyst Springfield, MA – Baystate Health

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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

Do Number of Likes and Followers Matter?

This is a one of those questions that keep coming up during conferences, the classes I teach at University of Washington, client conversations etc.

The default answer by most of the people is along the lines of “Oh they don’t …. It is the quality…. What really matters is the impact on revenue/cost… “ and so on.
I do not deny that ultimately the impact of business in terms of revenue/cost is what matters but saying that Likes/Followers don’t matter is flat out wrong.  It is equivalent to saying Visits to your site do not matter, potential customers in your store do not matter, subscribers of your email list do not matter etc.
Likes/Followers are the foundation that is required to make your social media efforts successful. Without Likes you don’t have anybody to put your messages in front of.  Without them you have nobody to amplify your message and help attract others like them.
If you are posting random stuff that has nothing to do with your business then you will attract random fans and followers.  If you talk about stuff in your particular industry/vertical etc. then you will attract Fans/Follower who care about what you are saying.   If you are attracting the right types of Fans/Followers/Like then number of Like/Followers does matter.  You want more of them.

Related Posts

• Social Media Analytics Part I
• Sentiment Indicator: Social Media KPI
• Social Media Sentiment: Don’t Get Caught Up In Raw Counts

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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
• Data Analyst Springfield, MA – Baystate Health

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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

Are You Depleting Your Email List?

In all the effort to drives conversions marketers often forget to measure “Unsubscribe” metrics and their impact on the email marketing.  As I mentioned in my post “Number One Email Marketing Mistake”, 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.

Getting an unsubscribe is easy, however getting more people to subscribe is very difficult and expensive. Email marketers need to have a long term view and protect the subscribers they have. They need to treat reducing the unsubscribes as critical, if not more, as driving people to subscribe.

I have come across some cases where the list situation is so bad that the unsubscribes will completely wipe out the marketers ability to do emailing marketing in next few year.   In order to ensure that you have a viable list, you need to closely watch and analyze the unsubscribe and subscribe metrics, few metrics that you should look at are:

1. Total Unsubscribes/Total Email List in your database– This will help you understand what % of emails you can actually email to.
2. Percent Unsubscribes/Email Sent – This will help you figure out if you need to adjust your email frequency.
3. New Unsubscribes/New Subscribes – This ratio if greater than 1 than you are heading for trouble. Lower than 1 indicates that the direction is good though you need other numbers to understand the full impact.

In addition you should look at you ability to grow the list and see how soon you will hit the growth plateau. Once you hit the growth plateau, reducing the unsubscribes becomes even more critical.
Related Post: 7 Ways to Create Relevancy in Emails

Tell a Story with the Data: Creating a Culture of Analytics

Many organizations fail to create a culture of analytics, not because they don’t understand the value of analytics, but because the analysts fail to craft a good and relevant story with the data.  We have all seen reports filled with pretty charts, graphs and numbers.  After going through all the data if the audience doesn’t have a clear understanding of what the reports are telling and what they should do with those charts and graphs then the analyst has failed in his/her job, no matter how pretty the reports are.
Let’s face it, numbers are interesting for a while but a lot of numbers without a story leaves audience either unsatisfied or bored.  However a well-crafted story with data weaved in can keep your audience involved. It is still the data presentation but with a solid story that ties the data back to the business objective.
Data Analysts need to become better story tellers if they want to build a culture of analytics at their organization. Here are some of the elements of a good data story

1. What are we observing
2. Why does it matter
3. How does it look compared to past performance, competitor, baseline, goals etc.
4. Are we going to be able to achieve the goals
5. What is effective and what is not
6. What can we do today
7. What did we learn that we can apply in future

Anything that is not relevant to the goals/objective of the business/stakeholder should be removed from the story (move detailed data to the appendix).  The KPIs should form the foundation of the data story.
Focus on the story rather than the tables of endless data and you will find that the people are willing to listen.
Other posts in the series

• Standard Definitions of Metrics: Creating a Culture of Analytics
• Context is Critical: Creating a Culture of Web Analytics
• The Curse of Knowledge: Creating a Culture of Web Analytics
• Creating a Culture of Web Analytics

Number One Email Marketing Mistake

Number one mistake marketers make with email marketing is to send “Irrelevant” messages to their customers. It is not because they don’t understand that sending relevant messages drive higher conversions. It because they think that email messages are “Free” and incremental cost of sending messages to “non-target” customers is Zero. They hope that, by sending emails to everybody, some of the “non-target” customers will respond to their message thus causing overall conversions to go up. However, this is a big mistake because what they don’t realize is that ultimately they will lose the privilege to this “Free” marketing. Here is how you can see this unfolding and ways you can measure the impact

1. In the beginning, engagement with the “irrelevant” email starts to slow down. People still open emails with a hope (if brand is one that they trust) that they might find something relevant to them. This issue will be evident in your declining (or low) click-through rate.
2. Then when people get tired of opening irrelevant emails, they start to rely on subject lines to see if there is anything relevant for them. This issue will become evident in declining (or really low) open rates of emails.
3. Over time, all the irrelevance ultimately annoys people. Nobody wants a clutter of irrelevant emails. Next step they take is to remove themselves from them madness. You will see this manifest itself in higher or constantly going up unsubscribe rate.
4. All this madness will ultimately lead to SPAM complaints. As these grow the domain will be blacklisted and with it will go the privilage of “Free” marketing.

So if you are one of those who think “Email” marketing is free, it is time for you to stop and reevaluate how you are doing your email marketing. Here are few tips to ensure that you continue to do you “Free” marketing:

1. Segment your customer base and only send relevant message to them , e.g. if a customer has never bought Women’s products from you then don’t send them an offer for 50% off on Women’s Clothing (See my post about Nordstrom’s email marketing Relevancy Matters in Email Marketing and 7 Ways to Create Relevancy in Emails)
2. Continuously test your segments to improve your Open Rate, CTR and Conversion Rate and Conversions
3. Based on your learning, further segment and develop micro segment to further drive relevance and effectiveness
4. Keep in Mind: Always be Relevant and Always be Testing