Online Personalization: Issue Is With People Not Technology

Today I came across an article by Isaac Weisberg, titled Unintended Consequences of Targeting: Less Information, Less Serendipity – Part I. In this article Isaac argues that online personalization limits the exposure of information to the individuals. I agree that current personalization practices are very limited though it is more of an issue with the marketers engaged in personalization than with the technology. ( Note: Retargeting, Behavioral Targeting, on-site recommendations, customized emails etc. are all different forms of personalization). So it is not Personalization that limits the flow of information but it is the people engaged in Personalization.

The purpose of personalization is to provide information that is relevant to an individual and in order to do so you will eliminate a lot of information that the person is not likely to be interested in. However that does not mean that the person cannot be exposed to new information with the personalization.

The issue is that most of the marketers engaged in personalization (targeting) do not exploit the full potential of personalization and limit themselves to basic targeting. I highlighted one such issues in my post 5 Questions to ask before starting a Retargeting Campaign.

Personalization does not mean that you have to limit yourself to the same product or even the category. User’s behavior gives you a clue on what he/she likes. Use that to figure out complimentary items that you might be able to promote and even items that don’t make sense together but you have seen patterns from sales data that tell you that they might go together. E.g. particular pair of shoes is bought by lots of moms, so maybe kids’ shoes might make sense to promote to a user who has shown interest in those shoes. Isn’t that flow of information to the user?
I once worked with a client who used two mutually exclusive behaviors (people who read financial news and view international weather) to promote a totally unrelated product (high end international travel) with a great success.

So, yes exposing people to new information while doing personalization is quite possible as long as marketers doing the personalization are willing to use their creativity and move beyond their comfort zone.

Questions? Comments?

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Open Web Analytics and Online Marketing Jobs

• Online Performance Data Analyst  at Announce Media (St Louis, MO)
• Web Data Analyst at Genworth Financial (Richmond, VA)
• Web Games Analyst  at Arkadium (New York, NY)
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• Web Data Analyst at Alzheimer's Association (Chicago, IL)
• Web Analytics Manager at Tig Global (Chevy Chase, MD)

HiPPO: Wrong Advice That Will Get You In Trouble

HiPPO is an overly used in the web analytics community to make the web analysts feel good. But this term, in my opinion, does more harm than good to you.

Though I meant to write this post a long time ago, today a post by Steve Jackson - HiPPO could be your best friend finally prompted me to write it.

For those how don’t know, HiPPO is a term used to describe the opinion of the Highest Paid Person (HiPP) i.e. Highest Paid Person’s Opinion. This terms basically says that the person who gets paid the most (it assumes that this person is also the highest authority position) will make decisions that are not based on any facts but rather based on his/her gut feel. As a result his/her opinions are generally wrong. Really? Do you really think that they got into their position by giving wrong opinions?

Some experts even encourage analysts to publicly embarrass HIPPOs by proving them wrong? Really? How do you think it is going to help you? Will you have a job tomorrow?

As an analyst, your job is to help your organization make better and smarter decision by using the information you gain from the data. How is calling Highest Paid Person a HiPPO or embarrassing your boss in public going to help it?

To make your point and get someone to listen to you, you have to make friends and not enemies. Just thinking that all the opinions expressed by the HiPP are wrong and not based on fact will automatically put you in either a defensive or an offensive mode instead of a collaborative mode. You need collaboration to succeed. Web analytics is still not integrated into business optimization process and the wrong attitude towards HiPPO will hinder it further.

Think about this, if you are an analyst attacking a HiPP in the room, who do you think will win at end?

Thoughts? Comments?

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Open Web Analytics and Online Marketing Jobs

• Web Data Analyst
  at Genworth Financial (Richmond, VA)
• Web Games Analyst
  at Arkadium (New York, NY)
• Web Metrics Analyst
  at Omnitec Solutions (Alexandria, VA)
• Web Data Analyst
  at Alzheimer's Association (Chicago, IL)
• Web Analytics Manager
  at Tig Global (Chevy Chase, MD)
• Sr. Data Analyst
  at Capella University (Minneapolis, MN)
• Manager, Web Analytics, Search & Production Support
  at Asme (New York, NY)
• Web Analytics Manager
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• Web Analytics Manager
  at Juggle (Swansea, IL)
• Sr. Analyst Web Analytics
  at Williams-Sonoma (San Francisco, CA)

FTC’s Proposed Privacy Framework

FTC’s proposed a framework to protect the privacy of consumers. Part of this framework is a “Do Not Track” option that has raised a lot of questions among the web analytics and advertising community. Well since this is just a proposal at this stage nobody knows how it will finally pan out. At this point FTC has published the report to seek public comments. The report that FTC has put together is 122 pages long. I have extracted some important point from that report in case you don’t have the time to read the full report.

The basic building blocks of this framework are:

• Scope: The framework applies to all commercial entities that collect or use consumer data that can be reasonably linked to a specific consumer, computer, or other device.
  
  Note: This is not limited only those who collect PII data, if you collect any information about a consumer then this applies to you. However commission is seeking input on how to determine
  “reasonably linked to a specific consumer…”
  
• Privacy by Design: Companies should promote consumer privacy throughout their organizations and at every stage of the development of their products and services.
  
  • Companies should incorporate substantive privacy protections into their
    practices, such as data security, reasonable collection limits, sound
    retention practices, and data accuracy.
  • Companies should maintain comprehensive data management procedures
    throughout the life cycle of their products and services.
    
    Note: You might need to assign a person to oversee that privacy of data is built into your products/services/process etc. Think, “Chief Privacy officer”.
    
    • Ensure physical data protection
    • Do not collect what is not required
    • Do not retain data for longer than it is required
    • Ensure accuracy of the data so that you do not harm someone because of the inaccurate data
• Simplified Choice: Consumers face considerable burdens in understanding lengthy privacy policies and effectively exercising any available choices based on those policies. Under proposed framework, companies should simplify consumer choice.
  
  
  • Companies do not need to provide choice before collecting and using consumers’ data for commonly accepted practices, such as product fulfillment.
    This also includes tracking for improving the sites (Web Analytics), fraud protections, legal compliance and first party marketing.
  • For practices requiring choice, companies should offer the choice at a time and in a context in which the consumer is making a decision about his or her data.
• Greater Transparency: Companies should increase the transparency of their data practices.
  
  • Privacy notices should be clearer, shorter, and more standardized, to enable better comprehension and comparison of privacy practices.
  • Companies should provide consumers with reasonable access to data about themselves; the extent of access should depend on the sensitivity of the data and the nature of its use.
  • Companies must provide prominent disclosures and obtain affirmative express consent before using consumer data in a materially different manner than claimed when the data was collected.
  • All stakeholders should work to educate consumers about commercial data privacy practices.

Feel free to leave a comment if I missed anything. You can read the full report at http://ftc.gov/os/2010/12/101201privacyreport.pdf.

Read my other articles on Privacy

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Open Web Analytics and Online Marketing Jobs

• Web Data Analyst
  at Genworth Financial (Richmond, VA)
• Web Games Analyst
  at Arkadium (New York, NY)
• Web Metrics Analyst
  at Omnitec Solutions (Alexandria, VA)
• Web Data Analyst
  at Alzheimer's Association (Chicago, IL)
• Web Analytics Manager
  at Tig Global (Chevy Chase, MD)
• Sr. Data Analyst
  at Capella University (Minneapolis, MN)
• Manager, Web Analytics, Search & Production Support
  at Asme (New York, NY)
• Web Analytics Manager
  at Conde Nast (New York, NY)
• Web Analytics Manager
  at Juggle (Swansea, IL)
• Sr. Analyst Web Analytics
  at Williams-Sonoma (San Francisco, CA)

No One Wants To Be Targeted But...

Yesterday I came across an article on eMarketer that showed that Behavioral Targeting brings clear benefits to publishers.

However when consumers are asked about Behavioral Targeting or data collections by websites they seem to dislike it.

It is clear from the first chart that behavioral targeting is working for everybody i.e. publishers, advertisers and consumers. If it were not working for consumers then publishers would not charge premium for it and advertisers would not pay premium for it.

So why are consumers so concerned? 

As I have stated before the biggest issue seems to the lack of consumer education and the perception of behavioral targeting.

Anybody will get concerned if you tell them that the websites are collecting too much personal information about them. The issue here is how the question is framed and the context it is posed in. If asked in a different way the responses would be different than shown in the chart above.

Let’s see how the answer will differ based on the questions asked. What do you think the answer will be to the following questions?

1. Do you like to be targeted?
2. Do you like that the websites collect a lot of personal data about you?

I think it will be something like “Hell No, I don’t like it”
Now, let’s frame the questions in another way:

1. Do you like to save you money on things you buy online? I am sure the answer will change from Hell No, to Yes.
2. Will it be ok if we understand your online behavior so that we provide you better offers?.... Sure
3. Understanding your behavior will require us to keep track of stuff you are buying and browsing. Are you ok with that?…. Sure or Maybe
4. We might also use your gender, age range etc. also to make sure you receive the right offers and message. You already have provided this to us and there is no need for any further action from you. Will that be ok? …Sure go ahead or maybe will be the answer.

Net results “No one wants to be targeted but they want the benefits” and seems like that value proposition is not clear to the consumers, the word "Targeting" gets them very concerned.

Solution

In addition to my "5 Steps to Successful Behavioral Targeting", here is what I think should happen

1. Behavioral Targeting should be renamed with a more consumer focused name. Marketers understand “Behavioral Targeting” but this name sounds too negative for consumers.
2. Educate consumers about online advertising and how using behavioral attributes helps consumers.

What do you think?

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Clop.in - URL Shortener with Analytics

5 Things That Could Be Hindering Your Conversions

Forms are everywhere on the internet, some convert great while other don’t. There are several factors such as call to action, images, copy etc. that all contribute to the success of a form. However, even a well designed form might not convert well if some fundamental things are not taken care of. In this post I am listing 5 fundamental things that could be preventing the visitors from converting.

1. Consistency in Call to Actions – Consistency in call to action is critical for conversions. You cannot underline few links and not the other within the same context. Be consistent with your formatting. Making some links underlined while other not underlined makes user think harder than he/she should and increases the chances of bailout. See below; do you see the inconsistency in the links? I almost gave up on finding that “Register Now” link (yes it is obvious now because I have highlighted it).
   
   
   
   
   
   
   
2. Captcha – Captcha is meant to stop automated computer programs (spiders) from filling the forms but do you know that a Captcha can also deter people who are genuinely trying to fill your form? I suggest doing a simple A/B test on your form with a captcha and without a captcha to see if you captcha is eating up your conversions. This will help you determine if the captcha is worth the loss in conversion.
   
   
   
   
   
   
   
   
   
3. Confirmation Fields – Confirmation fields are the field that require users to fill in the same information again to ensure that user that has not mistyped the information e.g. password, email etc. However, confirmation adds one extra field that the user has to fill in, thus coming in the way of conversion. Take a close look at your confirmation fields and determine if you really need them. For example, is it really required to have the user confirm the password? If the user has mistyped the password during registration then won’t she be able to easily get it via “Forgot Password?” link? If yes, then do you really need to confirm the password during registration? Do you really need confirmation on sensitive information such as social security? It is scary (for most people) to provide social security number online and confirming it again just gives users another chance to bail out.
   
   
   
   
   
   
   
   
   
4. Form Validations – Validations on form fields ensure that the data user is entering is in the correct format. However many validations are not really required and come in the way of user trying to complete a form. Check your validations to ensure they are absolutely required, e.g. @symbol in the email address field, or not, e.g. “-“ between area code and phone number. Do not force the users into unnecessary and annoying validations. Keep in mind that a lot of data formatting can be done via client side JavaScript or backend processing without putting the customer through a lot of pain.
   
   
   
   
   
   
   
   
5. Data Fields – It appears to me that many companies like to collect the data just for the sake of collecting it without thinking how it will be used. Yes every piece of data you collect can eventually provide you more information about your customer but should it be really on your form at the expense of lost conversions? Your customers have limited time and adding more fields on your form might turn them away. Go through your form and remove any unwanted fields. If you don’t want to remove anything at this point, identify the fields and do a simple A/B test (one version as it is and the other one without those fields) to see how your conversions are getting affected.
   
   
   
   
   

Questions? Comments?

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5 Tips For Great Customer Service On Twitter

Picture from CNET.com

Twitter has grown leaps and bound in last 4 years and now has over 190 Million members worldwide. Many companies have now jumped into using twitter as a means to provide customer support. Why? Well because more and more people are getting on twitter and it is way less expensive then phone support.

Recently I turned to twitter for help with one my services. There were two main reasons for me to turn to twitter 1. publicly complain about the company because I was not happy with the service and phone customer support 2. I was hoping that someone at the company will pay attention and get back to me. I achieved both. I was pleasantly surprised to find that these guys were paying attention and immediately responded.

So how was my experience? Well not much better than phone support. Though the twitter support agent tried her best but she was limited by the process and to some extent the technology. I think twitter could be a great customer support tool. However, we have a lot to learn. If companies want to use twitter as a viable customer support channel then they should be willing to pay attention to what is being talked about their customer support and brand and learn from their mistakes.

Based on my experience, I have outlined 5 tips that can help companies provide better customer support on twitter.

Five Tips for Great Customer Service on Twitter

• Knowledge - Have similar knowledge of your products and offers as your phone counterparts have. It is frustrating to hear different answers from two different channels. Not knowing who is wrong and who is right adds to the customer dissatisfaction. Whatever you say or mention on Twitter is going to be indexed by twitter, search engines and many 3rd party tools and will be there forever. So if you give wrong information via twitter it can and will be used against you. So you don’t want interns to run you Twitter customer support.
• Expectations - Answer tweets promptly or set clear expectation about when the customer can expect a reply back. Every second a customer has to wait adds to the customer’s anxiety because he/she is not sure if you got their tweet or not. With phone support you know that there is a live person at the other end. With email there is an expectation that it will take a day for someone to respond or you can send an auto response. With twitter customer expect immediate answers. Live up to those expectations or set them properly upfront else twitter customer service can backfire.
• Resolution - If you can’t resolve an issue in 5 tweets then have a customer support agent follow up by phone or offer to send a DM when the issue is resolved. You get thousands of tweets in a day and it is hard for you to respond each of those and resolve them in 140 characters. Remember not everything can be solved and should be solved via twitter. Set up a proper escalation process. At least for now, twitter cannot replace the live conversation or in person resolution experience and satisfaction for every single issue.
• Timeliness - Do not leave anything to the next day. You cannot go home without solving an open issue. Pass those issues to the next rep or hand them over to phone support. Since tweets are most likely not getting tracked in a CRM system as your phone or email support is, it is hard for you to remember the previous conversation and it is really annoying for the customer to explain everything again the next day. Ideal solution will be to track all your tweets in your CRM system. I personally had to explain my case 3 times to the same customer support agent because it was not resolved on time and each time I had to start over again.
• Information – Do not ask anything that is not required. You are dealing with 140 characters so limit the information that customer has to provide. If a customer provides you with her phone number/account number etc. you don’t need to ask her details about the products she has bought or the service she is subscribed to. All that information should already be in your CRM system. Most of the customers don’t know what products or services they have bought all they know is that something is not working when it should. Use your CRM system to find detailed information about that customer and the products/services they have.

(You can rearrange the above 5 tips to form a TIKER, Timeliness, Information, Knowledge, Expectations and Resolution, solution for Twitter Customer Support)

Remember, twitter (or any social media) is a new platform for customer support and it will take time before you can have a proper process and everything worked out. You should be prepared to take criticism and learn from the criticism because there were will be people who will write blog posts and tweet if your twitter customer support does not meet their standards.

Hope this helps. If you have a customer support story then leave it as a comment.

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15 Things to Test in your Email Campaign

Email open rates and click through rate have both declined over recent month as reported by eMarketer (Avg. Open rate is 11.2% while Avg. CTR is 1.6%).

This seems like a bad news for emails. What is going on? Is Social Media responsible for this decline or are there other reasons?

Who knows what the future holds for email marketing but for now email is alive and marketers can improve both the open rates and click-through rates by just doing a little bit more than they are currently doing.

The key to email success is giving customer what they want and in a format that they want. Nothing revolutionary but something that’s often forgotten in email marketing.
All this boils down to

1. Segmentation and Personalization
2. Testing

To address the first point, read my blog post “ 7 Ways to Create Relevancy in Emails.
In this post I am addressing the 2nd point i.e. Testing. Below are 15 things that you should test in your email campaign.

Open Rate Improvement
Below are the 5 things to test to improve the open rate of your email newsletter.

1. From Email Address
2. From Name
3. Subject line
4. Day of delivery
5. Time of the day

Click through Rate Improvement
Below are the 10 things to test to improve the click-through rate of your email newsletters.

1. Layout of the newsletter e.g. 2 column v/s 3 column
2. Colors e.g. background color, side columns colors, colors of different sections and links
3. Fonts and formatting of titles, text etc.
4. Images – e.g. size, placement of hero image (main image)
5. Images along with stories v/s stories without image
6. Article length – how many words should you show in the newsletter article summary before you make the users click to your site
7. Above and below the fold content – test if moving content above and below the fold impacts the click-through rate
8. Left and right placement of the links, stores etc.
9. Anchor text length in links – Do people click on longer links more than shorter links?
10. Action words v/s non-action words in hyperlinks e.g. Does “Download Now” works better than “you can download the whitepaper”?

Keep in mind that if you don’t give customer what they want then it will first show up in dropping click-though rates, leading to lower open rate and finally resulting in unsubscribes and demise of your email marketing.

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The Web’s New Gold Mine: Personalizing Your Online Experience

Past weekend, WSJ published a story titled Web’s New Gold Mine: Your Secrets on online tracking and advertising (behavioral targeting). It appears to me that the author of this article is either confused between malware and cookies is or she is just doing what she is supposed to do to sell the story i.e. using words that instill fear in people.

The article projects any tracking, business and advertisers do to serve relevant ads or personalize the users experience on web, as malicious. Businesses have been trying to understand consumer preferences and then make personalized recommendations ever since the humans existed. We do it offline all the time. So how is online tracking for the same purpose malicious?

My dad used to run his clothing store in India, way before internet existed. He used to gather all the information (in his brain) about consumers browsing and purchase behavior to make personalized recommendation to existing customers and new customers. He used all that information to determine what products, colors, sizes, quantities etc. to stock. He knew almost all of the existing customers by their name and what they preferred. Was that spying? Nope. Customer loved it.

If someone can understand me and provide me exactly what I want then why won’t I like it? If they miss the mark well then I have a choice of not paying attention to them.

Do you know that Visa, MasterCard and American express have more information about you than any cookie or advertising company has? Your super market collects your information and tries to guess about what you might buy next. Have you ever got a coupon from an automated coupon dispenser when you check out from your local super market? Well do you know that it is based on your current and past purchases, you zip code etc? Do you ever worry about that or happily walk away with the coupon? Why is the fuss about online tracking for the same purpose? Don’t you love personalized recommendations from Netflix or Amazon?

In my opinion advertisers/publishers/network should invest in consumer education and make tracking and targeting more transparent and articles like this should help with the education instead of branding all tracking as bad.

Comments?

Is Email Dead?

Declaring things dead is nothing new. Every day someone declares something dead. For example, in 2007 many people were declaring page views and even web analytics dead. Well here we are three years later and neither of those is dead yet.

Now many Social media “experts” including Facebook’s COO have declared that email is dead and social media will takes it place. Ben and Jerry’s in UK dropped their email campaigns in favor of social media.
Is email really dead? Is it a question of either or will both exist going forward?


Email is Still Alive

Few recent studies show that email is not dead (yet). According to an article by eMarketer, email still drives shopping over social. 37% of the shoppers prefer email as the promotion delivery method while only 9% prefer social. Considering that social media (online social media in its current state) is still in infancy these numbers are great but this also shows that email is not dead yet.

According to ExactTarget’s “Subscribers, Fans and Followers” report, most internet users engaged with brands only via marketing emails. They also found that there is significant overlap between the three channels and vast majority of social media fans or followers were also email subscribers. Nearly a third subscribed to emails in addition to being fans of brands on Facebook. (Source: How Are Email, Facebook and Twitter Audiences Different?

Considering that both email and social media are important, many marketers are using the power of email to spread the word about their social media presence. Two-thirds of the marketers surveyed by eROI say that they are integrating social media into email.

Conclusion

For now, email and social are co-existing. I suggest that you start integrating your social media into email campaigns if you are not already doing it. Every customer segment behaves differently and you need to look at your own data rather than reply on some social media expert's advice to draw any further conclusions.

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Follow the Shopper

Shoppers, via their online and offline actions, provide a ton of information to the marketers. Smart marketers can and should leverage this information to understand shoppers motivations and needs to create a better relationship with the shoppers and ultimately make more money for their organizations.

Every customer touch point is a goldmine of data. It starts from the keywords that shoppers use to arrive to your site, the links that they click on to get to your site (and the sites they visited before they came to your site), clicks on emails, clicks on banners, every click and every action on your site, purchases etc.. All these actions by the shopper provides you with the information that you can use to follow the shoppers.

What does following the shopper mean?

In simple terms, following the shopper (visitor) essentially means using the shoppers behavioral data to understand the shoppers’ needs and then serving them with personalized ads/messages/offers , wherever you see them online, to bring them back to you site to buy from you. (This concept goes beyond online though).

Following the shopper has several other names such as Behavioral Targeting, Retargeting, Remarketing etc.

Who is following the shoppers?

Pretty much all the major eTailers follow the shoppers (read my posts on Behavioral Targeting to see how widespread this is).

eCommerce giants have been following the shoppers for years using some combination of in-house solutions and 3rd party solutions. Recently they have also tapped into cookie exchanges to reach shoppers who have never been to their site.( More on cookie exchanges in future post).

Can small retailers with limited budget do this?

Yes they can. Until recently small eTailers did not have the know-how or the money to engage in such activities. But that has changed now, Google has came to the rescue of small/medium retailers with Adword remarketing. More and more small/medium companies are now “Following the Shoppers”.

Sounds good, right? But wait before you jump into it.

Remember, Remarketing is not easy and there are privacy concerns. You should think and plan before you leap into remarketing because if it is not done right then you can make your customer uneasy and risk losing them forever. (see my post titled 5 Questions to Ask before Starting a Retargeting Campaign).

Where can I learn more?

Well you can start on this blog and shoot me any questions you might have. Tomorrow, I am going to be moderating a panel at OMMA Behavioral in San Francisco on this very subject.

If you read this in time (before the panel) send me the questions that you would like answered and I will ask the panelists. The panelists include:

• Michael Andrew, Director, Search and Analytics, Mediasmith
• Michael Blais, Manager, Interactive Marketing, eBay
• Chris Duskin, Director, Product Management, Omniture, An Adobe Company
• Scott Jensen, Interactive Marketing Director, Extra Space Storage
• Matt Karasick, Sr. Director of Product Management & Marketing, Advertising Decision Solutions, Akamai
• Thomas Knoll, Community Architect, Zappos

So go ahead and email me your questions or tweet your questions to @anilbatra

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Looking to fill your Web Analytics or Online Marketing position?  Post your open jobs on Web Analytics Job Board.

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
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Understanding your Followers on Twitter

Every day I come across some scheme telling me how I can gain more twitter followers. Many so "Twitter experts" talk and write all day long about how to get more twitter followers. But how do you know if you have (or are gaining) the right kind of followers? Some of your follower constantly engage with you and you probably know who they are. But what about the rest of them? Who are they? What do they do? Are they the right audience for you? How can you create a right message to get their attention?

Understanding your Followers

One way to understand your followers is to look at their twitter bios and analyze the stuff they are tweeting about. This will help you gain understanding of their motivations. But all this is not trivial, so I started looking for a tool that will help me do this. Well, I had partial success and found a tool called TwitterSheep . TwitterSheep allows you to build a tag cloud based the bios of your followers on twitter. However it does not allow you to build a tag based on the tweets of your followers.

Still More is Required

As mentioned above this tool does not provide all the information that you need to understand your followers. Knowing what your followers tweet about; will be even more powerful than just their bios. Their tweets will tell you exactly what triggers their interest and help you in engaging with them. But TwitterSheep does not do that yet. So for now I will take whatever I can get (Hope TwitterSheep team is paying attention).

Competitive Analysis with TwitterSheep

Twittersheep is also a great addition to my competitve analysis tool. You can build a tag cloud for the follower of your competitors and see how their followers compare to yours (See below how @alaskaair follower compare to @virginamerica.).

Alaska Air twitter followers bio

 Virgin America twitter followers bio

I have not yet found any other tool that will let me build a tag cloud of what my follower are tweeting about but I will let you know if I find one. If you know of such a tool then please let me know. If you are a developer looking to build more stuff on twitter API’s then here is an idea for you, ping me and I can provide you more information.

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

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Looking to fill your Web Analytics or Online Marketing position?  Post your open jobs on Web Analytics Job Board.

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
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3 Ps of Dashboard Creation

In a recent article on Ad Age, I came across an interesting article around increasing importance and emphasis on Dashboards. I always thought that Dashboards are native to analytics and that it ought to be adopted by everyone organizations by now. Aren’t discussion around Dashboard as old (even older) than Web/Multi channel analytics.

After reading the Ad Age article along with my experience with clients I have come across an increasing need by clients to PROVE the effectiveness and efficiency of ad spend. Presently, marketing executives appear to be singularly focussed on ROI. The question we ask ourselves is that is it the holy grail of all measures? Should we move away from ROI as a single measurement of performance and add other factors to provide a (more) comprehensive view or a meaningful picture of marketing effectiveness? If so how do we share or present this data? When we ask these questions the importance of Dashboards and Scorecards become increasingly relevant and important.

Are there any fundamental (building block) principles one can apply at a tactical level to drive this initiative...Here, we list some key principles we have found useful as practitioners. Call it the 3P framework 

Process & Priority

Whether you are a CPG, B2B, Telecom, or Retail it is critical to align yourself with your corporate strategy. If the priority is to democratize data then every effort should be made to integrate online and offline systems to share the data up and down the value chain. Usually creating a deployment plan for Dashboards is a good start. One doesn’t have to create an all encompassing, visually appealing dashboard from the get go. Start somewhere, even if it is excel, ensure data integrity, and most important think action/outcome as opposed to numbers. The next important area where organizations generally miss out on is creating target and benchmarks. If you don’t aim you can’t hit the target. Consider targets based on priority or goals based on historic measures and ad spend. This will be the first step towards transparency and data democracy in your business unit or organization.

Performance Measures

Ask yourself this question: If you were the top brass in your company or your marketing organization what would you care about? This question is easy at first but as you drill in you will find yourself in a rabbit hole. At least I still do. Executives will think about Branding, Voice of Customer, and Demand Generation. CXOs will always have an interest in understanding these activities. It’s important for you as a practitioner to obtain these inputs which ought to be the second step in the Dashboard creation process.

A CFO would care about:

• Net Present Value: How much value an investment will result in? Usually, this is done by measuring all the cash flows over time to a future date. If I had 100K in 1910 how much will the 100K be in 2010? Usually calculating NPV is difficult because you don’t know what discount rate to use (rate of inflation vs. Treasury index) but one can think in these terms when considering large scale projects and it’s potential return.
• Payback Period: Say you invested 100K in your marketing program, if it returns 50K per year then you would have a two year payback period. It is a good metric for calculating and minimizing operating costs.

A CMO would care about:

• Customer Satisfaction: It measures how products or services meet or better yet surpass customer expectations? In a competitive market space, CS is a key differentiator and a key element of business/marketing strategy.
• Brand Awareness: It measures the consumers knowledge of brand existence or recall as many like to call it. It is usually qualitative in nature.
• Cost Per: These are the compound metrics which Anil has written about and it’s all about integrating disparate data sources to provide a transparent view on the success of a program. I am sure you get the idea now, having carefully selected measures will not only allow you to get a pulse on the reality, it will also allow you assign accountability to the right people. If for example, customer sat is low, consider taking immediate action on areas where this can be mitigated. If your Cost Per’s are underperforming, you can pick up the phone and ask your marketing guy/gal/agency as to where or how the money is being spent and to have them consider optimization strategies.

Presentation

In the Process and Priority section I talked about this briefly. I have often seen that practitioners get too detailed. It becomes almost second nature for them to add more metrics. Usually, these are perceived to be intermediaries. It is really important to consider dashboard design. Keep in mind some best practices:

• Data overload: At most have no more than 7-10 performance measures. This way end users are not overwhelmed and data is actionable as opposed to regurgitable.
• Lack of Benchmarks: Smart marketers understand the value of benchmarking. Context is king. It allows you to measure yourself against past performances as well as set standards for ongoing campaigns.
• Scoring System: Consider the “traffic light” scoring system. This is a quick indicator and allows users to focus on areas which need attention. 

Thoughts? Comments?

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This is a guest post from my friend and ex-coworker Kanishka Surana. Kanishka is currently the Head of Web Analytics for Ogilvy. He runs Ogilvy's Web Analytics group in North America, he has been in the Web Analytics space since 2002 and has worked in London, Seattle, Greece, Seattle, San Francisco, Salt Lake City, and most recently in New York.
Before that Kanishka worked at Gerson Lehrman Group a pioneer in proprietary research space. Kanishka and his wife Mini live in New Jersey.

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Looking to fill your Web Analytics or Online Marketing position?  Post your open jobs on Web Analytics Job Board.

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
• Landing Page Optimization Analyst at Red Ventures Armed Forces - Europe

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Optizent - Convert any page into a landing page for your organic search engine traffic

Best Time to Tweet?

Do you know what the best time to tweet is? Recently a client asked me this question and I am sure there are a lot of you wondering the same thing. When you tweet you want to make sure it reaches a lot of people (can I say that you want to get the biggest chirp for the tweet?).

So I did some research to find out what other have to say and here is what I found

• According to Gary McCaffry, based on the traffic to his site from twitter, the best time to tweet is anywhere between 9 AM – 3 PM PST.
• Another blogger, Malcolm Coles, who surveyed 120 twitter users to find out the best time time to tweet,, says that the best time to tweet is 4:01 PM.
• Social Media Guide says that best time to tweet is 9:00 AM PST, this will allow you to hit people across the globe
• Fasctompany says that the best time to get Retweeted is 4:00 PM EST. Fast company also lists many other factors that can help in Retweets.
• According to techandlife.com, if you have a large international following then you should repeat your message, 3-4 times a day to make sure it reaches all your followers. Personally I have not followed this rule but I repeat my message at different times on different days. I guess it is time for me to do some testing.
• Guy Kawasaki says - “take your most interesting tweets (as measured by how many people retweet them, perhaps) and post them again three times, eight to twelve hours apart. “
  
• If you can identify your influencer (I will discuss those tools in another post) on twitter then you can use Tweet o’Clock to figure out when is the best time to reach your influencers.

What does this all means? When should you tweet?

Based on this information I suggest the following

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).

Analyze the data and see which tweets got the most clicks, @ or RTs. Repeat this few times and see if the pattern holds. If it does then you will know the best time to tweet. Once you figure out the best time, use that time to tweet and vary your other tweet to a different time and see which one works the best (A/B testing of Tweet time).

If tweeting at particular time is an issue then keep track of the day/time you tweet and see if there is a pattern. This experiment should help you determine the best time to tweet for you. You might also be interested in:

• Twitter Analytics
• 3 KPIs for Measuring Twitter Success
• All of my posts on Twitter

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Looking to fill your Web Analytics or Online Marketing position?  Post your open jobs on Web Analytics Job Board.

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
• Landing Page Optimization Analyst at Red Ventures Armed Forces - Europe

Segmentation and Personas Part 1

The Web is all about choices and Analytics is all about understanding the choices by analyzing the behavior patterns:

Who are my right customers? Why do they make the choices that they do? What opportunities are worth chasing? What features will provide the most value? What is the best time-to-market, and most important which customers are most important.

While it’s difficult to make ALL the right choices, one has to make most of them right for the campaign, site, or product to succeed.

Enter Personas

This is a must have tool for marketers for helping them make the right choices. Personas is essentially a technique for capturing the important learning(s) from analyzing users and customers and identifying and understanding the different types of people who use the site.

It is a description of an imaginary but very plausible user that “personifies” these traits. The three key traits which personas help identify are:
Behavior, Attitudes, Goals.

How can Personas Help

• Rallying – Personas can help you build a common vision. If you look at any website, there is so much information that most marketers look at it at an aggregate level. There are literally thousands of details about a user (think pathing, content affinity, referring sources, tools usage, yada yada yada). An analyst, can’t possibly measure or conclude key behavior traits by analyzing these data points. Personas can help group these types at a high level and provide a human face to the types of people.
• Testing and Optimization – As a side benefit, you can test specific creative tactics on these personas. Messaging for the Net Generation (Gen Y) would be different than the messaging for Gen X (Baby Busters) . If you can identify the key behavior traits by type then you can build a test plan around it to drive conversions on the site.
• Targeting – Anil is one of the great thinkers around the topic of One on One personalization. His entries on Behavioral Targeting are a delight to read. Imagine, armed with “statistically significant” behavior data (or traits) you can proactively market or provide content to drive usage and ultimately convert the user. That’s the ultimate promise and the holy grail of marketing isn’t it?

Are there any cons or pitfalls

There are obviously things to watch out for. The biggest ones are prioritization and validation:

As a practitioner I have seen that a lot of research, thought, and homework done in building personas. Usually Strategy gets involved along with Product/Brand Owners and Senior members of the client and is handed down to executors.

What is important to understand is that your website is not for everyone. People will come to your site, tease you, perform competitive shopping, look for products, research about products etc.

It’s not okay to say that your website is for everyone. If you think that way you are deluding yourself. This is extremely difficult for most marketers to grasp. I try hard to explain to my clients is to focus your efforts or release or a landing page on a single persona. It doesn’t mean that the website or landing page will not be useful or usable by others, but if you gradually build the user experience around each type or user profile you will ultimately do a great job in attracting the highest quality users to your site. That’s the promise of Qualitative surveys and Quantitative analysis.

Another pitfall I have seen is that teams create personas based on their "assumptions" which usually comes from the Highest Paid Person In the Organization (HIPPO). In my mind this is guesswork and not based on any analysis; the right thing to do here is to take time to analyze your web data, interview/take time to talk to real users and verify if these personality types or personas really exist.

So are you using or thinking about personas for your website? Does your agency recommend taking the approach? Share it with us.

Next time we will talk about different techniques both qualitative and quantitative to measure personas.

Thoughts? Comments?

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This is a guest post from my friend and ex-coworker Kanishka Surana. Kanishka is currently the Head of Web Analytics for Ogilvy. He runs Ogilvy's Web Analytics group in North America, he has been in the Web Analytics space since 2002 and has worked in London, Seattle, Greece, Seattle, San Francisco, Salt Lake City, and most recently in New York.
Before that Kanishka worked at Gerson Lehrman Group a pioneer in proprietary research space. Kanishka and his wife Mini live in New Jersey.
This is first of a series of posts that Kanishka will be doing on this blog.

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Looking to fill your Web Analytics or Online Marketing position?  Post your open jobs on Web Analytics Job Board.

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
• Landing Page Optimization Analyst at Red Ventures Armed Forces - Europe

5 Web Analytics Misconceptions

There are several misconceptions in web analytics (created by some author/bloggers/experts) though many others have tried to clarify them from time to time but they keep reappearing. I recently had a conversation with someone who was so much in love with one of the misunderstood metrics, listed below, that it prompted me to write this blog post. So without much delay, here are the most common five misconceptions that I come across all the time:

1. More Page Views are good – Unless you are an ad supported site that sell advertising via CPM (cost per thousand impressions) more page views might mean that the visitors are lost on your site and can’t find what they are looking for. More pages views/visit could indicate issue with your site navigation. For effective analysis, set your baseline and then watch for significant deviations (up or down) from the baseline.
   
2. All that bounces is bad – I have written 2 detailed posts showing why all that bounces is not really bad. Bounce rate is one metrics that people overly obsess with. Keep in mind all bounces are not bad. The things that cause high bounce rate are:
   1. Links to external sites that you want visitors to click
   2. Ads on your site take visitors out of your site
   3. Returning visits might bounce because they might come to your site to read your daily/ weekly/monthly update
   4. Visits that are for a specific reason e.g. find your phone number
3. Focus on reducing the bounce rate and everything will be ok- Well that’s the advice many people give without even looking at the other data points and analyzing if reducing the bounce rate will really help you achieve your goal or not. Reducing the bounce rate might not be the most effective way to increase ROI. You should create a monetization model and determine the impact that reducing the bounce rate will have before you start creating different version of a high bounce page to A/B test to reduce your bounce rate. I have seen cases where you won’t get positive ROI even when you reduce the bounce rate to 0%.
   
4. Time on site (or page) shows how much time people are spending on the site – As I wrote in my blog post titled Understanding the "Time Spent on the Site" Metrics there are many issues with measuring the actual time spent on the site or a page. One of the main reasons is that the last page that a user views/reads on your site is not counted in this calculation. So if you have a non-ecommerce sites then the chances are that the visitors spend most of their time reading the last page but that page won’t not counted in this metrics and hence your time on page and time on site metrics will be way off. As long as you know that you need to watch the trend instead of using this metrics as a absolute measure of time spent on site then go ahead and use this metrics.
   
5. Referring Sites report shows all the traffic sources including campaigns – Well… not really. There are a lot of reasons for the referring source to be lost from the time the visitor clicks on the link to the time they arrive on your site, two big reasons are
   • Server redirects – This happens a lot with ad serving. Suppose you buy an ad though a 3rd party company who then uses an ad network to place your ads on a publishers site e.g. yahoo, each party does some processing and redirect of its own. In doing all these redirects the referring information is lost or shows one of the sites that does the redirect. For example, you might see atdmt.com showing up in the referring sites which means you were serving ad via Atlas even though the ad might have been served on MSN.com. Many URL shortening services used on twitter also show up as referring domain instead of twitter.
   • 3rd Party Apps – This is a big issue with Twitter URLs. A lot of twitter users use 3rd party apps and any clicks to your URL posted on twitter from these 3rd party apps will show up as direct traffic.
   
   If you are running a campaign or posting links in social media, blogs, forums etc, make sure to tag them with campaign identifiers so that you can use campaign reports instead of relying on referring sites report.
   

Thoughts? Comments?

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image source: ct4me.net

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Looking to fill your Web Analytics or Online Marketing position?  Post your open jobs on Web Analytics Job Board.

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
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• Landing Page Optimization Analyst at Red Ventures Armed Forces - Europe

Compound Metrics in Web Analytics

Should you use a compound metrics in your web analytics reporting? This was a topic of discussion in one of my classes at UBC Web Analytics course.

What is a Compound Metrics?

Before we get into answering the question, let’s look at what a compound metrics is.
Simply stated a compound metrics is when you take two or more simple measures and combine them together to form one metrics.

So should you use it?

Short answer is - why not? Sometimes simple metrics such, such as visits, page views, clicks etc., are not enough to explain a complex concept and that's when you need a compound metrics, e.g. engagement metrics, visit quality measure etc.

But isn't compound metrics hard to explain?

It depends on how you define it but then a lot of people still struggle with
visits, visitors, hits and pageviews. With that in mind, I agree that initially it might be a little hard to grasp the compound metrics. Over long term, compound metrics actually helps simplify the measurement of a complex concept.

Some of the common uses of the compound metrics are

1. Credit Score (Everybody has one and it affects them every day but how many actually know how it is calculated?)
2. Google Page Rank
3. Twitter Resonance (it will use several factors such as retweets, clicks on links etc.)
4. Twitter measurement. Many twitter measurement tools use compound metrics since it is not easy to explain Reach, Impact, Engagement in simple metrics.
5. Facebook's "Likeability Index". Ok, I made this one up but I am sure that's coming soon.

Example

Let's look at an example and see where such a metrics will make sense in your current web analytics reporting.

Lets take an example of a product information site. The products are sold offline via 3rd party retailers and since this company does not want to compete with its retailers it doesn't sell anything online. This site provides information about the various products that this company sells. It provide white papers with pre-purchase information and post purchase information/support. The site has some videos and some stories that are published every now and then. Well there is a sign-up form to allow users to save their product information.

The whole goal of the site is to provide information to current and future customers.

Now your big boss asks "We spent thousands of dollars to build this site, is this site working?".

You reply, well... Visits are down but repeat visits are up so seems like people like it and are coming back. However, page views/visit are down. More white papers are downloaded as compared to last month. However, video views are down and sign ups are also down. Seems like some things are up and some things are down.

Boss goes...."What does that mean? Is it working or is it not? Are customers finding information?"

How do you measure that?

As an analyst you can look at all the metrics and come to a conclusion but you have to be able to convey the end result to the VP of marketing. He needs to know if the site is successful or not.

This is where a compounded metrics comes in handy.

A simple formula for this could be

(% of visits viewing X pages or more + % of visits viewing video + % of visits downloading white papers type 1 + % of visits downloading white papers type 2)/4

we used 4 in the denominator because we are using 4 different metrics with equal weight

Now you can add other metrics that matter to the business and also assign different weight to each, so your formula could be something like:

(1*% of visits viewing X pages or more + 4*% of visits viewing video + 1*% of visits downloading white papers type 1 + 2*% of visits downloading white papers type 2)/8

1,4,1 and 2 are the weights assigned to each metrics based on their importance to the business.

Once you develop a baseline for your metrics, you can confidentially tell you boss if the sites performance is better or worse than the last month. Keep in mind that you are an analysts and you should always get under the hood to analyze each component and find opportunities for improvement.

What do you think?

Questions? Comments?

Other articles on similar topics are

• http://www.juiceanalytics.com/writing/franken-measuresor-how-construct-useful-composite-/
• http://www.usca.edu/polisci/apls301/compound.htm

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Looking to fill your Web Analytics or Online Marketing position?  Post your open jobs on Web Analytics Job Board.

Current Open Positions

• Marketing Strategy Research Analyst at Magnani Caruso Dutton New York
• Digital Strategist at Magnani Caruso Dutton New York
• Sr Data Analyst at Capella University, Minneapolis
  
• Landing Page Optimization Analyst at Red Ventures Armed Forces - Europe