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