Web Analytics, Behavioral Targeting and Optimization by Anil Batra

Analyzing and Optimizing Ad Campaigns – Part 1

2012-01-24T13:02:00.003-08:00

I am going to start this series of post with few questions for you. Here is some data pulled from a Web Analytics tool. This data is for a “Display Ad” campaign:

Most of the web analysts today get the following view of display advertising from their Web Analytics tool. Looking at this data and some publicly available information they will get started on the analysis and recommendation.

Though some other analysts will say, Wait… I need more information. Google Adwords has done such a great job in providing cost data and almost all of the analysts have dealt with some kind of paid search campaign, so they know that cost of campaign plays a role in the analysis of campaign. So they demand it. Well this is where most of the web analytics tools fell short, cost data generally resides in some other tool and it is not easy to get that data. But how said that Analytics was easy. However, I am providing full data with cost so that we can continue with this post. Keep in mind that many analysts will continue without cost data. If you are one of them then stop and look for the campaign cost data.

Now the above view sort of mirrors what you are used to seeing in Google Adwords.

So what do you think? Can we analyze this data and take some actions? This is what many web analysts end up doing. Some will be brave enough to venture into segmenting by repeat v/s new visitors, mobile v/s non-mobile etc. If you are doing some kind of segmentation then you are already moving in the right direction. However there is more…. I will write about that in my next part. Meanwhile, let me hear from you. What do you think? Where should we focus? Is everything looking good? If not then, what is wrong with this campaign? What is your recommendation?

Part II coming soon.

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Web Analytics Jobs

Digital Customer Analytics Sr Consultant at American Cancer Society (Atlanta, GA)
Web/Digital Analytics Auditing at Audit Bureau of Circulations (Arlington Heights, IL)
Senior Web Analyst at Pop (Seattle, WA)
Online Analytics Specialist, Communications, Brookings at Brookings (Washington, DC)
Director, Brand & Multiplatform Research at Turner Broadcasting System (Atlanta, GA)
Web Analytics Analyst - Business Intelligence Group at Cmn.com (Houston, TX)
Senior Manager, Digital Research at NBC (New York, NY)
Senior Analyst, Modeling, Segmentation, and Forecasting at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior Analyst, Digital Measurement | Optimization at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior database developer (Sr. SDE) at Optizent (Redmond, WA)
Associate Games Analyst at Arkadium (New York, NY)
Director of Analytics at Arkadium (New York, NY)
Web Analytics Engineer - Contract (POP) at Pop (Seattle, WA)
Website Analyst at Simplexity (Reston, VA)

Social Media Sentiment: Don’t Get Caught Up In Raw Counts

2012-01-12T12:49:00.001-08:00

Are you obsessing over the total number of mentions, number of positive mentions and negative mentions? If you are then you are not alone.

This same issue came up recently while I was speaking on the subject of Social Media at a local event. One person got very concerned when I said that a lot of social media conversations are marked “Neutral” in most of the social media monitoring tools. The reason is that tools are not yet advanced enough to classify everything and so when in doubt the conversation is marked “Neutral” rather than “Positive” or “Negative” .

So what do you do in this situation, when you know that the sentiment numbers are not right?
Short answer is: Don’t obsess over the raw counts.

Let’s face it; you will never get an exact count of mentions about your brand, products etc. let alone the sentiment counts. Here are few reasons why the number won’t be accurate

Tools - The number of mentions will change with the tool you are using. Different tools have different sources of data and different way of classifying spam, and hence the numbers won’t match between various tools. In other words you will never know exactly how many mentioned about your brand, products etc. are happening in Social Media.
Tool Setup – The way you setup your tool will result in different count of conversations.
Keywords - A generic keyword like “Windows” will bring many more results than “Microsoft Windows” however “MS Windows” will bring a different count and so on. The mention count will change depending on your keywords.
Tool Updates – Tools are changing every day. The count of mentions and sentiment change as tools roll out updates to their algorithm. As for the sentiment, tools are changing the way they assign sentiment to the posts, so if last month something was classified as “Neutral”, similar post this month might be classified as Positive, due to changing algorithm as tools become better each day.

So you can’t really count on the raw numbers, so don’t obsess over them. A better measure of sentiment is the directional movement in sentiment which I calculate using what I call: Sentiment Indicator. I wrote about Sentiment Indicator in my post Sentiment Indicator: Social Media KPI

Sentiment Indicator = (Positive Conversations – Negative Conversations)/(Positive Conversations + Negative Conversations)

Sentiment indicator allows you to see if you making an improvement in positive direction or not. Though it is still dependent on actual count, the impact is minimized or neutralized as tools become better in classifying both positive and negative mentions.

Also, keep in mind that there is a lot more value in the actual conversations than just the counts. Finding value in actual text of the conversation requires manual scanning of the social media conversations. In these conversations is where you will find valuable information to help you optimize your marketing, products, PR etc.

Comments? Questions?

Other Social Media Analytics posts that you might have missed:

Follow Me on Twitter: @anilbatra
Facebook: https://www.facebook.com/TheAnilBatra
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Web Analytics Jobs

Web/Digital Analytics Auditing at Audit Bureau of Circulations (Arlington Heights, IL)
Senior Web Analyst at Pop (Seattle, WA)
Online Analytics Specialist, Communications, Brookings at Brookings (Washington, DC)
Director, Brand & Multiplatform Research at Turner Broadcasting System (Atlanta, GA)
Web Analytics Analyst - Business Intelligence Group at Cmn.com (Houston, TX)
Senior Manager, Digital Research at NBC (New York, NY)
Senior Analyst, Modeling, Segmentation, and Forecasting at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior Analyst, Digital Measurement | Optimization at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior database developer (Sr. SDE) at Optizent (Redmond, WA)
Associate Games Analyst at Arkadium (New York, NY)
Director of Analytics at Arkadium (New York, NY)
Web Analytics Engineer - Contract (POP) at Pop (Seattle, WA)
Website Analyst at Simplexity (Reston, VA)

One Awesome Web Analytics Tip: Think Beyond Web Analytics

2012-01-05T14:46:00.003-08:00

I am sure you have heard of a story about a guy lost his ring in a dark alley. It was really dark and he could not see anything, so he went to a nearby lamppost and started searching for his ring underneath it. When asked why he was looking for ring under the lamppost, he said “because it is bright here”.

That’s what most of the web analyst do. Even when the problem might exist somewhere other than what their web analytics data can show majority of the web analytics folks just look at “Web Data” for the answers. Why? Because that’s all the data they have easy access too. It is brighter there.

Here are some other things which are in the “dark” areas. It is time for you to shine light on them:

Ad Server – There are several factors that impact a performance of a campaign, many of them don’t show up in your web analytics tools, they reside within ad servers or with 3rd parties. Example: Which pages the ads was shown, what time was the ad shown etc. I will write more on this in a future post.
Conversions – Conversions can happen offline in-stores or via phone. Most of the time these won’t show up in your web analytics tool. I wrote about this in my post Are you Optimizing the Wrong Steps of the Conversion Process?
Social Media Conversations – Conversations about your brand, products, offers happen outside your domain and impact how people react to your campaigns, engage with your site and ultimately impact the conversions and bottom line. Many companies have started to collect the conversation data but they might sit within a different system owned by a different department.
Mobile – Mobile usage is growing every day. More users spend their time on Mobile. If you don’t have an integrated view of the mobile data with other data sources then you will end up barking the wrong tree.
Third Parties– Some companies do not sell any products on their site. Their sites are mainly there to provide information. They sell their products via 3rd parties. However these 3rd party sites also provide information on products, provide reviews, have user communities etc. You don’t need to visit the official company site to make a decision to purchase something. For example, you might never visit Samsung’s site to buy a Samsung TV. All the research you need is already available on Amazon or Best Buy. Similarly, many insurance providers sell their insurance through 3rd party agents. Game companies sell their games via 3rd parties. What does web analytics data show in this case?

What you need is integrated data sources that provide you data other than just web analytics. I am not saying that it is going to be an easy task to get all this data but at least start thinking about those and see how you can bring them all together.

Comments? Questions?

Follow Me on Twitter: @anilbatra
Facebook: https://www.facebook.com/TheAnilBatra
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Web Analytics Jobs

Web/Digital Analytics Auditing at Audit Bureau of Circulations (Arlington Heights, IL)
Senior Web Analyst at Pop (Seattle, WA)
Online Analytics Specialist, Communications, Brookings at Brookings (Washington, DC)
Director, Brand & Multiplatform Research at Turner Broadcasting System (Atlanta, GA)
Web Analytics Analyst - Business Intelligence Group at Cmn.com (Houston, TX)
Senior Manager, Digital Research at NBC (New York, NY)
Senior Analyst, Modeling, Segmentation, and Forecasting at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior Analyst, Digital Measurement | Optimization at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior database developer (Sr. SDE) at Optizent (Redmond, WA)
Associate Games Analyst at Arkadium (New York, NY)
Director of Analytics at Arkadium (New York, NY)
Web Analytics Engineer - Contract (POP) at Pop (Seattle, WA)
Website Analyst at Simplexity (Reston, VA)

Cost of Advertising: CPM, CPC and eCPM Demystified

2012-01-03T20:30:00.001-08:00

The purpose of this post is to clarify the terms CPM and CPC and also show how to convert from one model to the other.

CPM

CPM stands for Cost per 1000 Impressions (number of times the ad is shown) (M is Roman numeral for 1000). Generally display advertising (e.g. banners) is sold in CPM. If the ad is shown 1000 times the cost will be equal to 1 CPM price. For example, if a publisher charges $10 CPM, that means your ad will be shown 1000 times for $10. If your budget is say $10,000 then mean your ad will be shown 1,000,000 times ($10,000 *(1000/$10) ).

Total Impressions = (Total Cost or Budget) * (1000/CPM)

If you are trying to find out how much you will pay for a given number of impressions then you can use the following formula

Total Cost = (Total Impressions * CPM)/1000

If you notice in the above calculations, there are no mentions of how many people the ad will be shown to or how many clicks will be generated. CPM advertising is solely based on impressions. In theory if you don’t set a frequency cap (i.e. the maximum number of times one person will see your ad) then you could end up serving all the impression to one person only. (If you would like to know more about frequency cap then drop me a line and we can talk further).

CPC

CPC stands for Cost Per Click. Google Adwords made this model popular. Generally search and text advertising is sold by CPC model. In this kind of advertising model you just pay for number of clicks you get on your ads irrespective of number of impressions it takes to generate those clicks. For example, if the CPC is $1.00 and your ad is shown 12,000 times but gets no clicks then you pay nothing. If you get 10 clicks on your ad then you pay $1.00X10 = $10.00.

CPC = Total Cost/Total Clicks

Total Cost = CPC * Total Clicks

Comparing CPM to CPC and vice versa

The goal of advertising using one model versus the other is really dependent on what you are trying to achieve. If your objective is to generate Brand awareness then you might engage in display advertising which will most likely be sold in CPM model. While search ads on Google or text or display advertising on Google Ad Network are sold in CPC model.

Often you will end up comparing two models to figure out where and how to spend your money effectively. To do direct cost comparison you will need to convert CPM to CPC or CPC to CPM pricing.

CPM to CPC conversion

Below is a formula that you can use to calculate a CPC equivalent of a CPM model

CPC = ((Total Impression *CPM)/(1000 *Clicks)

Below is a spreadsheet to show you the same calculation. Let’s take an example of a campaign that costs you $10 CPM and generates 50 clicks in 50,000 impressions.

		Formula
CPM	$10	Know value
Impressions	50,000	Know value
Click	100	Expected or Known
Total Cost	$500	Impressions * (CPM/1000)
Cost Per Click	$5	Total Cost/Clicks

The above $10 CPM campaign is equivalent to a $5 CPC campaign.

CPC to CPM conversion

Below is a formula that you can use to calculate a CPM equivalent of a CPC model

CPM = (CPC*clicks*1000)/Total Impressions

Let’s take an example of a campaign that costs $4 per click and generates 100 clicks, resulting in a total spend of $400. Let’s say it took 50,000 impressions to generate those 100 clicks.

		Formula
CPC	$4	Known value
Clicks	100	Know values
Total Cost	$400	CPC*Clicks
Impressions	50,000	Impressions * CPM/1000
Cost per 1000 Impressions	8	Total Cost/(Total Impressions/1000)
CPM	$8	Cost per 1000 Impressions

eCPM

The CPM value you get when you convert CPC into CPM is also known as eCPM (effective CPM).

Note: eCPM is also shown in Adsense reports, in that case it is

Total Adsense Revenue /(Impressions/1000)

I have developed few calculators to calculate CPM and CPC, feel free to use them.

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Web Analytics Jobs

Web/Digital Analytics Auditing at Audit Bureau of Circulations (Arlington Heights, IL)
Senior Web Analyst at Pop (Seattle, WA)
Online Analytics Specialist, Communications, Brookings at Brookings (Washington, DC)
Director, Brand & Multiplatform Research at Turner Broadcasting System (Atlanta, GA)
Web Analytics Analyst - Business Intelligence Group at Cmn.com (Houston, TX)
Senior Manager, Digital Research at NBC (New York, NY)
Senior Analyst, Modeling, Segmentation, and Forecasting at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior Analyst, Digital Measurement | Optimization at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior database developer (Sr. SDE) at Optizent (Redmond, WA)
Associate Games Analyst at Arkadium (New York, NY)
Director of Analytics at Arkadium (New York, NY)
Web Analytics Engineer - Contract (POP) at Pop (Seattle, WA)
Website Analyst at Simplexity (Reston, VA)

10 Conversion Optimization Posts You Must Read

2011-12-28T14:12:00.000-08:00

You will find many examples of how various headlines, call to actions etc. can be tested to drive more conversions and how many companies have successfully done so. Maybe you have done it too. However deep inside you know that moving the needle from 3% to 4% is huge but still there are 96% of your visitors/visits that did not convert. I have compiled a list of some of my blog posts that show you how can move the needle further up by taking action on things that are generally not found in tips and tricks books and articles.

5 Things That Could Be Hindering Your Conversions
In this post I have listed 5 fundamental things that are part of most of the online forms but could be preventing the visitors from converting.
Underline the Clickable Text and Link the Pictures
Sometimes you just have to do it without doing testing. Underlining the clickable text and linking the picture to a page are few of those things that really do not require testing.
Are Form Validations Invalidating Your Conversions?
Are the data validations on your sites form hindering your conversions? This posts gives you something to think about.
Is CAPTCHA Eating Up Your Conversions?
Though CAPTCHA is a great tool for blocking spam it could be coming in the way of user experience and resulting in a lower conversion than you would have had without it.
7 Ways Of Handling 404 Error Messages - 404s are hard to avoid. Even if you have done everything correctly users might mistype the URLs and get a 404 on your site. This post shows you how various companies are handling them effectively to drive engagement and conversions.
Conversion Optimization: Go Beyond A/B Testing and MVT
A/B testing and MVT are a great way to help you drive more conversion on your website. A/B testing and MVT help you decide the best layout, headlines, images, message copy etc. that motivates the visitors to complete a transaction.
However, A/B testing and MVT will only get you so far. If a visitor does not complete a transaction during later steps of the funnel then there are generally other reasons than those that can be simply fixed by changing the page layout, copy, images etc. .
Is Your Conversion Rate Wrong? – This post explains how your conversion rate calculations are wrong.
Conversion Tip: Making the Most of the Email Confirmation Thank you Page -
Thank you and confirmation pages are the most ignored pages. This post shows how to effectively use those pages to drive further engagement and conversions.
Are you Optimizing the Wrong Steps of the Conversion Process?
Due to organizational structure, many marketers/analysts get a partial view of the customers’ conversion process data. This results in optimizing the wrong steps of the conversion funnel /channel. I describe my recent experience while purchasing a laptop to show how focusing on one channel only can lead to wrong
results.
Most likely your Conversion Rate is Wrong
Most of the web analytics tools just allow you to see a view of single channel conversion rate i.e. web conversion rate. However, as I discussed in my post "Are you Optimizing the Wrong Steps of the Conversion Process?", customers don’t care how your channels are divided or who is responsible for what channel at your organization. They care about their money and will use whatever channel they feel most comfortable with. Are you considering other channels when calculating your conversion rates?

And a bonus:
Significance of Statistically Significant Results in A/B Testing
Do not make the mistake of jumping the conclusions too quickly when running A/B tests, wait for statistically significant results.

I hope 2012 will bring you lot more conversions. Happy New Year!!!

Comments? Questions?

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Web Analytics Jobs

Web/Digital Analytics Auditing at Audit Bureau of Circulations (Arlington Heights, IL)
Senior Web Analyst at Pop (Seattle, WA)
Online Analytics Specialist, Communications, Brookings at Brookings (Washington, DC)
Director, Brand & Multiplatform Research at Turner Broadcasting System (Atlanta, GA)
Web Analytics Analyst - Business Intelligence Group at Cmn.com (Houston, TX)
Senior Manager, Digital Research at NBC (New York, NY)
Senior Analyst, Modeling, Segmentation, and Forecasting at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior Analyst, Digital Measurement | Optimization at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior database developer (Sr. SDE) at Optizent (Redmond, WA)
Associate Games Analyst at Arkadium (New York, NY)
Director of Analytics at Arkadium (New York, NY)
Web Analytics Engineer - Contract (POP) at Pop (Seattle, WA)
Website Analyst at Simplexity (Reston, VA)

One Prediction and Five Web Analytics Tips for 2012

2011-12-19T00:23:00.000-08:00

For past few years I have made several predictions about Web Analytics. This year I am going to make only one prediction but will provide five tips for 2012.

Prediction

This year the push will be towards “Multichannel Analytics”. Integration of various data sources, e.g. email, CRM, social media, call center etc. , with Web Analytics will take center stage.

Five Tips for Web Analytics

Expand your web analytics to consider other data sources
We all know by now that no one channel exists in isolation. Web, email, mobile, social media, catalog, stores, call centers etc. all impact each other. Web is a just one part of the customer’s experience and journey towards purchase. To fully understand customer behavior and optimize your marketing you have to go beyond web analytics and look at data from other channels.
Move from “How Many” to “Who”
Majority of the web analyst today analyze “How Many” e.g. how many people landed, how many bounced, how many converted etc. “How many” is a great start but it is time for you move to “Who”, e.g. who bounced, who did not convert etc. and then think about how to engage with those “Who” did or did not do something. (if you need help with this then ping me)
Understand the data structure behind your web analytics data
I am surprised that many web analysts today don’t understand how the web data is structured, how it is collected, where all the variables that are passed in your JavaScript end up at and how various data elements are related to each other. If you are one of those analysts, take some time to understand the data structure. Open a raw web server log file and start from there. If you company is porting the web analytics data into a database then open up that database and look under the hood.
Learn SQL
This is going to be critical. You can only do limited segmentation and optimization with aggregated data that is provided in the web analytics tools interface. To really understand customer behavior and capitalize on that you should be able to extract the data from the backend. Even if you are not going extract the data yourself, having an understanding of SQL will give you tons of ideas on segmentation, optimization and targeting.
Make friends with “HiPP” (Highest Paid Person) and say goodbye to “HiPPO”
HiPP is your friend, not foe. If you really want to create a culture of analytics in your organization then make friends with HiPP, get them on your side. You need their support. Stop using the term “HiPPO”.

Comments? Questions?

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Web Analytics Jobs

Web/Digital Analytics Auditing at Audit Bureau of Circulations (Arlington Heights, IL)
Senior Web Analyst at Pop (Seattle, WA)
Online Analytics Specialist, Communications, Brookings at Brookings (Washington, DC)
Director, Brand & Multiplatform Research at Turner Broadcasting System (Atlanta, GA)
Web Analytics Analyst - Business Intelligence Group at Cmn.com (Houston, TX)
Senior Manager, Digital Research at NBC (New York, NY)
Senior Analyst, Modeling, Segmentation, and Forecasting at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior Analyst, Digital Measurement | Optimization at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior database developer (Sr. SDE) at Optizent (Redmond, WA)
Associate Games Analyst at Arkadium (New York, NY)
Director of Analytics at Arkadium (New York, NY)
Web Analytics Engineer - Contract (POP) at Pop (Seattle, WA)
Website Analyst at Simplexity (Reston, VA)

Do you need Real-Time Web Analytics?

2011-12-07T11:40:00.000-08:00

Real-time web analytics provides you a view into what is happening on your site at that very moment. It is really interesting to see where visitors are coming from, what keywords they are searching, what pages they are viewing etc. Though most of the time that’s where it ends i.e. it is interesting but not very valuable. As many web analysts have stated time and again, the value of the analytics comes from the action you take on that data. So, unless you are going to take actions in real time you really don’t need real-time analytics. However, I can understand the temptation to use Real Time Analytics for instant gratification.

Side Bar:

Recently Google Analytics joined the bandwagon of providing Real-Time analytics. Other notable real time web analytics vendors include Chartbeat, Woopra. As of now, Google analytics only provides a very limited view of real time stats at this point, though I am assuming that it is just the beginning and Google will roll out more stats in its real time reports.

Few cases where you might want to (or be tempted to) use Real-Time Analytics

You launched a new campaign e.g. paid search, email newsletter, TV ad , and would like to see how people are reacting to those campaigns.
You added new promotions on your site and want to see how visitors are reacting to those promotions, so that you can tweak those promotions in real time.
You added new stories, links etc. and want to see if anybody is clicking on them so that you can make some changes based on instant feedback. I can see the usefulness of this feature for news and media sites.
You made some technical changes e.g. changed tracking code and want to see if those pages are being recorded in Google Analytics. Real time reports can serve as QA tools.
You launched a new feature on your site, launched a video, deployed a new game and would like to know if your visitors are using it or not.

Keep in mind that even if you are ready to make changes in real time, you might not have statistically significant results based on few data points that you get in real time reports. If you have nothing better to do then you can for sure kill your time with some real time view into your site traffic.

Views from Twitter

What do you think? Have you found Real time analytics to be useful? How are you using it? Please share your views.

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Web Analytics Jobs

Director, Brand & Multiplatform Research
at Turner Broadcasting System (Atlanta, GA)
Web Analytics Analyst - Business Intelligence Group
at Cmn.com (Houston, TX)
Senior Manager, Digital Research
at NBC (New York, NY)
Senior Analyst, Modeling, Segmentation, and Forecasting
at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior Analyst, Digital Measurement | Optimization
at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior database developer (Sr. SDE)
at Optizent (Redmond, WA)
Associate Games Analyst
at Arkadium (New York, NY)
Director of Analytics
at Arkadium (New York, NY)
Web Analytics Engineer - Contract (POP)
at Pop (Seattle, WA)
Website Analyst
at Simplexity (Reston, VA)

Most likely your Conversion Rate is Wrong

2011-11-28T00:21:00.001-08:00

I am sorry to break this news to you but chances are that your conversion numbers are all messed up. Let me demonstrate it with an example.

Let’s take a simple conversion process, see the figure below. Let’s assume that you get 100,000 visitors on your site, and 20,000 start the checkout process, 15,000 make it the next step and finally 5,000 end up converting.

Based on your web analytics tool your conversion rate will be 5,000/100,000 = 5% . So far everything looks good.

But what if your checkout path looks something like this?

Do you see the phone number? I bet many customers are using that phone number to complete the purchase. Are you taking those, who call and convert, into consideration when calculating the conversion rate? Do you know that when someone picks up the phone to call he/she has a higher likelihood of converting?

Taking the example above, here is how your conversion funnel looks like:

Most of the web analytics tools just allow you to see a view of single channel conversion rate i.e. web conversion rate. However, as I discussed in my post "Are you Optimizing the Wrong Steps of the Conversion Process?", customers don’t care how your channels are divided or who is responsible for what channel at your organization. They care about their money and will use whatever channel they feel most comfortable with.

Are you going beyond single channel when calculating your conversion rate? If your answer is no then your conversion rate is wrong.

Thoughts? Comments?

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Web Analytics Jobs

Senior Manager, Digital Research at NBC (New York, NY)
Senior Analyst, Digital Measurement | Optimization at ARC Worldwide, An Affiliate of Leo Burnett (Chicago, IL)
Senior database developer (Sr. SDE) at Optizent (Redmond, WA)
Associate Games Analyst at Arkadium (New York, NY)
Director of Analytics at Arkadium (New York, NY)
Web Analytics Engineer - Contract (POP) at Pop (Seattle, WA)
Website Analyst at Simplexity (Reston, VA)
Web Analytics Manager at Gilt Groupe (New York, NY)
Principal Web Analyst at AOL (Dulles, VA)
Senior Web Analyst at Vml (New York, NY)

Conversion Optimization: Go Beyond A/B Testing and MVT

2011-11-04T15:05:00.000-07:00

A/B testing and MVT are a great way to help you drive more conversion on your website. A/B testing and MVT help you decide the best layout, headlines, images, message copy etc. that motivates the visitors to complete a transaction.

However, A/B testing and MVT will only get you so far. If a visitor does not complete a transaction during later steps of the funnel then there are generally other reasons than those that can be simply fixed by changing the page layout, copy, images etc. . Don’t get me wrong, I am not saying that you can’t improve conversions by optimizing later steps of the funnel. You can, but you will get to a point of diminishing return and you will need something else to drive more conversions. Moreover, the learning from A/B and MVT will only help you going forward but you will lose many customers while you are doing the tests.

Keep in mind that as a visitor moves down the conversion funnel his/her commitment to complete the transaction (convert) increases. If you are able to capitalize on that motivation in time, you will drive higher conversions.

Here are some of the ways to help you drive conversions from those visitors who walked away without converting (sales, download etc.):

On-Site Targeting – This is very effective technique to drive user to take desired actions. You can target visitors with personalized message/offer, prompting them to complete a transaction, when they come back to your site at a later time.
Remarketing or Retargeting via Ads– This works great to bring the potential customers, who have wandered away on the internet, back to your site. Using a service like Google Adwords you can reach your visitors on various sites which use Google Adsense. There are several remarketing services that you can use but Google Adwords, though not very sophisticated, is a good way to get started. Read my post on Google Adwords Remarketing before moving forward.
Online Chat – Online chats are a great way to make a human connection with the visitors while he/she is still on the site and in the buying mode. Some products/people need human interaction to persuade and a triggered online chat might just do the trick.
SMS - Everybody seems to own a cell phone these day, follow-up the shopping cart abandoners with an SMS message, hit the iron while it is still hot. SMS marketing is not very prevalent in US but is heavily used in many other countries.
Email Follow-up – Following up with an email is another excellent and widely used way to drive conversions from those unfinished conversions.
Phone Calls – Similar to online chat, phone calls have a human element to them. Phone calls work very effectively even in converting a person who might have decided otherwise. Phone conversion rate is generally a lot higher than web conversion rates and phone salesperson can even do upsell to drive more revenue/visitors, though the cost also goes up. Striking a right balance is critical and needs proper assessment and strategy.
Direct Mail - Yes it still does work in many cases.

Keep in mind that timing and right follow up strategy is very critical when contacting those that did not convert. If you do need help in this area send me a note.

Questions/Comments?

Are you Optimizing the Wrong Steps of the Conversion Process?

2011-10-31T15:48:00.000-07:00

Due to organizational structure, many marketers/analysts get a partial view of the customers’ conversion process data. This result in them optimizing the wrong steps of the conversion funnel /channel.

Read below about a shopping experience I recently had, it will make it clear how this narrow view can come in the way of an organization's ability to effectively optimize the right step/channel in the conversion path.

I was recently in the market to buy a laptop. I had a Lenovo laptop in past, which I really liked, so I decided to buy another Lenovo laptop.

I went to their site, configured the laptop and chose various options. When I got to the last step, I decided to contact a live person because I was not sure of all the options that I had picked. I clicked on the little chat button on their site and connected with a sales guy. The person asked me to save my order (create an account etc.) so that he can find the order and help me with it.

I did what he told me to but to my disappointment, the sales guy (online chat) was not able to find my order even when I gave him the email address I used to create the account.

I had my credit card ready and was willing to make a purchase but they just could not close the deal.

Where do think the problem is in this conversion process? Which steps are you going to optimizing?

Someone just focusing and looking at online channel data will not know the complete pictures. They will see a drop-off at the last step of the funnel and if there are a significant number of visitors like me, they will most likely focus their attention on optimizing (A/B testing, MVT etc.) the last step. Right? This is where the problem lies. You may live in your little silo of online optimization but customers don’t follow your organizational boundaries. They will flow from one channel to other and convert from the channel that they are most comfortable with. You can go ahead and A/B test all you want to the last step of the funnel but if the issue is not with the page layout, heading, fonts, colors etc. then you A/B test are not going to help.

As an analyst you should go beyond your designated channel. If there are other channels (e.g. contact center) that the visitors can use to complete the process then don’t ignore them. Get a complete view of the data so that you don’t end up optimizing the wrong steps in the conversion process.

Sentiment Indicator: Social Media KPI

2011-09-20T21:01:00.000-07:00

People talk, they say good things about a brand, they say bad things about a brand or they just talk. Social media has become a place for people to make sure whatever they are saying is heard loud and clear by their friend and followers on Facebook, twitter, blogs etc.

Going through all this social media chatter to understand and figure out what is going on about your brand is a very labor and time intensive work. Even though many Social Media Monitoring tools have done a great job in aggregating the data from various sources, but to understand the context of those conversation and provide that to marketers in a meaningful way still needs a lot of work. Currently it really needs a human to understand the full context of the conversations and understand the sentiments of consumers.

However there are some metrics that can provide you a measure of the sentiments (positive or negative) of these conversations and indicate which direction they are going.

Social Media Sentiment Metrics

Almost all of the social media monitoring (listening) tools provide following metrics to help you understand the sentiment of the conversations about your brand in social media.

Total number of conversation or mentions about a brand, product or topic
Number of positive conversations or mentions about a brand, product or topic e.g. a tweet saying: I love brand ABC
Number of negative conversations or mentions about a brand, product or topic e.g. a tweet saying I hate brand ABC

Many social media analysts use these raw number of positive and negative conversation to monitor the health of their brand, competitor or industry in social media (positive is good and negative is bad, unless that conversation is about your competitor).

However,these numbers are not KPIs. For example, if one day there are 100 negative conversation about your brand and the next day you have 50 negative conversations then what does it really mean? On the surface it looks like you have done something good to bring down the negative conversations by 50%. Is it really true though?

To fully understand those numbers we need a little more context. Looking at the total number of conversations about your brand might provide some context. Say, there were total 200 conversations about our brand on day1 and 100 on day two. If we take percentage or ratio of positive conversation to total conversations and ratio of negative conversation to total conversation we find that we did exactly the same on both the day.

On Day 1: Negative Conversations/Total Conversation Ratio = 100/200 = 50%

On Day 2: Negative Conversations/Total Conversation is 50/100 = 50%

As you can see these ratios or percentages provide much more information than the raw number did. Even though raw negative mentions were down, as a percentage your negative conversation were about the same on both the days. This is where many social media analysts and marketers stop and use the above 5 metrics as KPIs. Let’s relist the 5 KPIs discussed so far

Total Conversation about a brand, product or topic
Number of Positive Conversations about a brand, product or topic
Number of Negative Conversations about a brand, product or topic
Ratio or Percentage of Negative Conversations/Total Conversation
Ratio or Percentage of Positive Conversations/Total Conversations

But something is still missing in these metrics. Those who have analyzed social media conversation know that majority of the conversations are classified as “Neutral”. Neutral means that there is no positive or negative sentiment in the sentence or the conversation in which that brand, product or topic is mentioned. In my experiences, over 90% of the conversations are neutral. So let’s take another example to show how that messes up the above KPIs.

Day 1
Total Conversations: 1000
Negative Conversation: 5
Positive Conversations: 10
Negative/Total Conversation = 5/1000 = 0.5%
Positive/Total Conversation = 10/1000 = 1%
Day 2
Total Conversations: 1500
Negative Conversation: 5
Positive Conversations: 10
Negative/Total Conversation = 5/1500 = 0.33%
Positive/Total Conversation = 10/1500 = 0.67%

In the example above, it looks like our positive and negative conversation both dropped on day 2. Though in reality, looking at the raw numbers there was no difference in the volume of positive or negative conversations. It just happened that “neutral” conversations went up on day 2 causing the percent of positive and negative conversations to go down.
So as you can see, in this case raw numbers are a better indicator than the percentages or ratios. So you can see how none of the above 5 KPIs provide an accurate view of sentiments of conversations in the social media. We need a better KPI.

Sentiment Indicator

I use another KPI, that I call "Sentiment Indicator" or "Sentiment Index", which in my opinion, is a better indicator of sentiment then other metrics that we discussed. Here is how I calculate “Sentiment Indicator”:

Sentiment Indicator = (Positive Conversations – Negative Conversations)/(Positive Conversations + Negative Conversations)

(Note: Even though neutral comments are still good for analysis, I do not use them in my calculations of Sentiment Indicator.)

Using our example above Day 1, The Sentiment Index will be 10-5/(10+5) = 33%, which is exactly the same as that on the Day 2.

This metrics is more actionable than other metrics. If it goes in negative direction that means we are getting higher number of negatives as compared to positives and it is time to get into action. If it goes in the positive direction then we must be doing something good and time to find out what that is. Also, many times I will use the volume of conversation along with it to make sure that while we are maximizing the positive conversation we are also enabling the total conversation volume to go up.

Note: You should still dig deeper into those conversation, particularly the negative ones and see what is going on. Sometimes even one negative comment can quickly go viral and ruin your reputation.

Your turn now. How do you measure sentiment?

If you are not sure and need help, don't hesitate to email me at batraonline (at) gmail (dot) com or leave a comment on this blog post.

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Web Analytics Jobs:

Senior database developer (Sr. SDE) Optizent Redmond, Washington
Associate Games Analyst Arkadium New York, New York
Director of Analytics Arkadium New York, New York
Web Analytics Engineer - Contract (POP) POP Seattle, Washington
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Website Analyst Simplexity Reston, Virginia
Principal Web Analyst AOL Virginia
Senior Web Analyst VML New York, New York
Director, Analytics VIMEO New York, New York
Web Marketing Analyst (International) j2 Global Communications Los Angeles, California
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Digital Marketing Analyst Makeover Solutions Inc. New York, New York
Senior Web Analyst VML Kansas City, Missouri

To add open positions, visit Web Analytics Jobs Board

WAA Board, Symposium and iJento

2011-09-18T15:47:00.001-07:00

It has been quite some time since I wrote a blog post and you must be wondering if I am going to get back to writing or not. Short answer is: Yes, I will. Before I get back to my regular writing scheduled I would like to tell you about two major changes that have happened since my last blog post.

WAA Board
My term as a Director of WAA Board came to an end earlier this year. I decided not to rerun for another team at this time. I would like to thank all of you who voted for me and gave me an opportunity to serve on the Board of Web Analytics from 2009-2011. It was a very exciting time and we achieved a lot of thing during that time. Personally, the biggest achievement for me was the start of local symposiums and local chapters.

As I thought about WAA, before I was on the Board, I felt that there was very little (almost no) value for the members in joining the association. Members felt disconnected from WAA. Something needed to be done to bring WAA and its values down to individual members. Local events such as Symposium felt like a great way to connect individual members around the world with WAA and also provide an opportunity for members to learn from experts as well as other fellow WAA members.

I think it was March 2010, when I discussed the idea of local events with Peter Sanborn, President Board of Directors Web Analytics Association, while sipping coffee at a Microsoft cafeteria. Peter liked the idea and we agreed to bring “Web Analytics Associations” to local levels and the "Seattle Web Analytics Symposium" was born. Next year we took the Symposium to Austin and just like Seattle it was a huge success. Thanks to many volunteers around the world, since then Web Analytics Symposiums have been organized in many cities and has proven to be very successful in driving both sponsorship and memberships. Last I heard was the next WAA Symposium in Seattle will draw close to 400 attendees. Wow!!! That is huge. Unfortunately I will miss it because I will be on vacation at that time but I am sure there will be many more organized in Seattle in coming years and I will be a part of them.

I am proud of my contribution to the Web Analytics community. I wish I could have continued as a WAA Board member but given that my full time job, a 3 yr. old son, blogging, speaking, teaching etc. take a lot of time, I felt that I cannot continue to spend the time required to do justice to WAA Board position so I decided not to rerun for the board this year. I might run for the board again in future but for now I will support WAA and its effort by participating at the local levels.
iJento
Moving along the curve of Web Analytics Maturity, I have joined iJento,a multichannel analytics company, as the Vice President of Business Consulting. It is a very exciting opportunity. I will write more about iJento in future but if you are curious to know more about iJento then send me a note or visit http://www.ijento.com. I also encourage you to read Barry Parshall’s , SVP of Product Management, interview at IQWorkforce to give you an idea about what iJento is up to. iJento will also be at eMetrics in New York.

QR Code Analytics

2011-03-30T14:24:00.001-07:00

QR codes have started to pop-up in lot of places such as store display, business cards, online ads, postcards etc. Whether QR codes are here to stay or not but from the measurement perspective they do present a huge opportunity in measuring advertising's (particularly offline) effectiveness.

If you are one of those marketers who have embraced QR code or are thinking about it or just curious to know how QR code measurement works then this post is for you.

Measuring URLs in QR Codes

You won’t be able to measure the number of impressions of the QR codes if they are distributed offline. What you can measure is how much traffic those QR codes are driving to your site or to your pages on 3rd party sites like facebook page, twitter account etc.

Measuring QR code links to your site

Measuring QR codes that sends user to your site is as simple as campaign tracking. Just add the campaign tracking variable to the URLs that you have in your QR Codes and treat it like any other campaign. Then you can use your campaign reports to see how much traffic QR codes are bringing and how valuable that traffic is.

(Note: The tracking code, that you should append, depends on your Web Analytics tool.

For Google Analytics, you need to append add at least 3 variables, Source, Medium and Campaign Name. to the URL for it to be tracked in the Google Analytics (Check out URL Shortner, http://clop.in as it’s URL builder let’s you append the variables for tracking in Google Analytics, Omniture, WebTrend and Unica NetInsights )

Example
Say I want to create a QR code to send people to
http://webanalyis.blogspot.com

Instead of simply creating a QR code to http://webanalyis.blogspot.com I appended Google Analytic campaign tracking code so my URL looks like the following http://webanalysis.blogspot.com?utm_source=qrcode&utm_medium=blog&utm_campaign=qrcodeblogpost

Now I can use the campaign tracking in Google Analytics to see the stats on my QR code advertising.
Measuring QR links to offfsite URLs such as Facebook page

Since you won’t have your own web analytics tool running on a Facebook page you can use a URL shortener like http://clop.in or http://bit.ly (or better yet get a URL Shortener for your own domain with built in analytics from http://clop.in) to shorten the destination URL and then build a QR code using the shortened URL. This way you can use the built in analytics functionality of the URL shortener.

Example:
Say I want to send user to my facebook page http://www.facebook.com/TheAnilBatra

Rather than sending user to the facebook page, via my QR code, I created a short URL using http://clop.in, http://clop.in/PByJfv and then used this shortened URL to build my QR Code.

Now I can use the analytics reporting of http://clop.in/short-url-clopin.aspx?utm_source=qrcode&utm_medium=blog&utm_campaign=qrcodeblogpost to see the stats on my QR code advertising.

Tracking Phone Numbers in QR Code

To Track phone numbers, that get dialed when someone scans a QR code, use a unique phone number that you have tracking for. If you don't have unique phone number then you can use 3rd party services likes Marchex to get a unique phone number for each QR code that you publish.

Note: To create a QR code use a service like http://qrcode.kaywa.com/

Questions? Comments?

Current Open Positions

Web Analytics Senior Implementation Consultants (Contractor) at Acceleration Emarketing (New York, NY)
Web Analytics Analyst at Designory. (formerly Agency.com) (Chicago, IL)
Web Games Analyst at Arkadium (New York, NY)
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)

Underline the Clickable Text and Link the Pictures

2011-03-10T15:02:00.000-08:00

Sometimes there are things that you know are not right and need to be fixed immediately rather than testing and waiting for the result. Such was a case that I recently encountered and the results were amazing.

Recently, I was working with a client who sells people expertise (I am purposely vague here because I don’t want to reveal the name of the client). The “Expert” search is the start of the process and then “Expert Search result” page is a second step in the process.

On the expert search page, each expert is listed with a small blurb and the name of the expert was linked to the next step of the “checkout process”.

When analyzing the “checkout” process we noticed that there were 2 things missing

The name of Expert was not underlined – it was linked to the next step in the “checkout” funnel but not underlined. Also, that was the only call to action on that page i.e. to click on the experts name to go to the next step.
The picture of the Expert was static and had no link whatsoever.

Recommendation

Usually I recommend doing A/B testing before making any changes to a page/process but I also do rely on best practices from time to time. In this case underlining the Expert’s name (“product name”) to get more information and to link the image to either next step or the enlarged version of the image with more info made total sense. I was confident that I did not need any test (I sound like a HiPPO, right?). So
So rather than waiting to conduct an A/B test we went ahead and made those changes.
(of couse a clear to call to action link or button might have worked too but that was not an option)

Result

Exits from that page dropped from 38% to 33%
Funnel conversion rate went up from 40% to 47% (Though 40% conversion was amazing considering there was no highly visible way to get to the next step of the process).

I am sure if you look at your own site you will find plenty of such opportunities for improvement.
Thoughts? Comments?

Context is Critical: Creating a Culture of Web Analytics

2011-03-04T09:14:00.001-08:00

Continuing my series on Creating a Culture of Analytics I would like to touch on a very critical aspect of creating a culture of Web Analytics and that is Context.

What is Context

According to Princeton.edu context is

Discourse that surrounds a language unit and helps to determine its interpretation
the set of facts or circumstances that surround a situation or event

Context takes the ambiguity out of the equation. As an Analyst it is very important that you provide full context when reporting your web analytics data. Context gets everybody on the same page. Do not leave anything for interpretation by the end users of your reports, give them the insights in a simple and easy to understand format.

Let’s look at an example to understand critical context is.

60 Degrees

If I say it is going to be 60 degrees tomorrow. What will be you reaction?
If you are in Minnesota – You will yell “Summer”
If you are in Seattle, you will think – ““Spring”
If you are in Florida, you will say “ Damn… Cold”
If you are in India, you will say “WTF….” (Indians measures temperature in Celsius and 60 degrees Celsius is 140 F)

Some other question that might pop in people’s mind are:

What is the temperature today?
Is it normal to have 60 degrees this time of the year

Without context 60 degrees does not mean much. Right.
Similarly when you report your numbers and tell report on visits, page views, time on site etc. it does not mean much unless you provide the full context.

Web Analytics & Context

Just saying that Visits are down by 10% from last week is not enough. You have to put that 10% decline in full context. Tell your end users what happened and why they should or should not worry.

So add something like : Visits are down 10% from last week and also 10% lower compared to the same time last year. Prior to this week we saw a 10% year over year growth but last week was abnormally down. Isn’t that betting better now?

You should go even further: Last year we got some free advertising from local newspaper sites that drove 20% additional traffic same time last year. Since we did not have the advertising deal this year, it impacted our visits this year. We noted the potential impact of newspaper site advertising in our last year’s annual recap (here is the link to last year report – people forget so remind them). If we take out the impact of spike from newspaper sites then we have a consistent pattern of 10% year over year increase. As noted in last few reports, that increase is due to our social media efforts this year. Now the picture is much clearer. Of course you should look into the full impact e.g. conversion, bounces, sales etc. (Note: How you present this story will depend on what format you chose to present your report)

Now everybody is on the same page and knows exactly what those numbers mean. Without that context, everybody would have had their own interpretations of the data. Misinterpretations lead to wrong action and/or mistrust in the data and the analytics team.

Final Words

Do not provide any reports without providing full context. Keep in mind that most of the canned and automatic reports do more harm than good because they do not provide context.

Other posts in the series

Follow me on twitter @anilbatra

Facebook Page http://www.facebook.com/pages/Anil-Batra-Page/130050670343547

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

Current Open Positions

Web Analytics Senior Implementation Consultants (Contractor) at Acceleration Emarketing (New York, NY)
Web Analytics Analyst at Designory. (formerly Agency.com) (Chicago, IL)
Web Games Analyst at Arkadium (New York, NY)
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)
Web Metrics Analyst at Omnitec Solutions (Alexandria, VA)

Value of Social Shares

2011-02-28T16:02:00.000-08:00

Adding a widget such as AddThis , ShareThis and Facebook Like button on your site makes it very easy for your site visitors to share your site and content with their friends and followers via email or social media. Even though these are small widgets, that your developers/designers might not have paid much attention to, they add a tremendous value to your business.

According to a recent report by eMarketer 47.5% of the people trust the recommendations of their social media contacts. In order to leverage social sharers you have to make it easy for them to share you content and widgets like these do a good job in making your site shareable.

A small widget like this can save you thousands of dollars in customer acquisition and even retaining the customers via either direct conversions from the traffic driven by shared links or by the brand awareness that those links create.

Monetary value of Social Shares

Most of the sharing widgets have built in analytics to measure the virality of your site/content. Use the analytics report to understand how valuable those shares are. Make share analytics reporting part of your web analytics reporting so that other stakeholders can see the value too. If you need to convince your boss on why they should pay attention to these social shares, tie the value of shares to something more tangible i.e. Dollars/Pound/Euro/Rupee. Here are some of the ways you can tie the value of social shares to money:

Direct revenue
Life-time value of customer gained via social share
Advertising cost savings from the shares

Let’s do a simple calculation to see the value of social shares. In this example I tied the value of “Social Share” to the amount saved in paid search advertising

Example Calculation

Data that you will need:

Clicks Generated– The number of click/visit/visitors generated from Social shares shares. (You might only get clicks/share from the widget analytics but you can easily estimate visits or visitors based on the data from your web analytics tool)
Cost of a visit – You can estimate this from either a blended cost of all your online advertising or simply from paid search.

That’s all. Using the above information you will be able to calculate the “Cost Savings”, the cost you would have paid to drive those visits that you got for free from social shares.
Note: If you are able to tie the social sharing with your web analytics tool then you can not only get accurate count of visits (or visitors) instead of just clicks but also can get the conversions and revenue generated from those shares.

A/B Testing & Optimization
The location of you share widget will have an impact on the number of social shares you get. Social shares present a great opportunity to drive lots of valuable traffic. A/B test different locations of share widget to see how it impacts your bottom line and find the best location for those widgets.

I have attached a spreadsheet that will allow you to calculate the value of those shares and the opportunities optimization present. Just plug in some basic numbers and see the results. Download the spreadsheet from http://anilbatra.com/digitalmarketing/downloads/socialshares.xlsx

Related post: 3 Tools for Measuring the Virality of Your Content

Follow me on twitter @anilbatra

Facebook Page http://www.facebook.com/pages/Anil-Batra-Page/130050670343547

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

Current Open Positions

Web Analytics Senior Implementation Consultants (Contractor) at Acceleration Emarketing (New York, NY)

Web Analytics Analyst at Designory. (formerly Agency.com) (Chicago, IL)

Web Games Analyst at Arkadium (New York, NY)

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)

Web Metrics Analyst at Omnitec Solutions (Alexandria, VA)

3 Tools for Measuring the Virality of Your Content

2011-02-24T16:41:00.002-08:00

Several studies have shown that people trust the link and site recommendation they receive from their friends or experts in the field. To capitalize on this opportunity websites have long used features like “Recommend to a Friend” or “Email this” kind of functionality. Recently we have seen a rise in usage of tools/widgets that make it easy for the visitors to share links via email and social media.

Measuring Virality
Many of the tools/widget that allow you to add easy sharing now also have built in analytics to help you track things such as which content is getting shared, how many people like to share etc, what methods do they use to share etc.

3 tools that you should look into are:

Tool Comparison

ShareThis and AddThis

ShareThis and AddThis are very similar in functionality with some minor differences but they look more like each other.

Both this widgets have very similar reporting and tell you

How many links were shared
How many people shared them
What content was shared
Number of clicks back to you site from those shares
Sharer’s interest
Geo locations of the sharers

AddThis and ShareThis only capture the information if a user uses the widget provided by these companies. However, these widgets won’t’ track the content shared by old fashioned copy and paste of either the URL or the actual content of the page. This is where Tynt comes into picture.

Tynt

Unlike AddThis and ShareThis Tyne does not have any share widget. Instead it works by automatically appending a unique hash value (a number folder by #) to each URL and the copied content. It uses that hash value (sort of like unique cookie) to determine metrics such as how many times the links/content was copied from your site, the number of visits it brought back and various other metrics.

Most of the reporting is very similar to AddThis and ShareThis widgets. Here is a list of some of the data that Tynt reports on:

How many times your content was shared
How many visitors you got back from those shares
What content was shared and how much
It even tells you how your sharing compares to others
Geo locations of the sharers and clickers

However, There is one report that only Tynt provides and that is the keyword report. It shows you

Inbound keywords - keywords that visitors searched to get to your site (AddThis has a different variation of keyword report)
Outbound keyword - the keywords that visitors found on your sites but left your site to find out more about them. This is a really cool report because it tells me what else I can write more about on my site so that my visitors don’t have to leave the site to find out more about them. I will be using that report to add more content to my blog/site.

I will cover some more details on these tools and how we use them for our clients in future but for now I suggest you look at these tools and let me know what you like or don’t like about them.

Do you know of or use any other service? Send me the details.

Note: In addition to above three there is “Facebook Like” button too.

The Curse of Knowledge: Creating a Culture of Web Analytics

2011-02-15T17:14:00.000-08:00

Presenting the data is what Web Analysts do majority of the time. It is critical for Web Analysts to present the data in a way that is easily understood by their intended audience. However, I have seen time and again that this simple rule is missed. Why? Because we all suffer from what is known as "The Curse of Knowledge".

What is The Curse of Knowledge?

Here is what 37Signals.com write on this subject:
Lots of research in economics and psychology shows that when we know something, it becomes hard for us to imagine not knowing it. As a result, we become lousy communicators. Think of a lawyer who can’t give you a straight, comprehensible answer to a legal question. His vast knowledge and experience renders him unable to fathom how little you know. So when he talks to you, he talks in abstractions that you can’t follow. And we’re all like the lawyer in our own domain of expertise.

"Curse of Knowledge" becomes a big issue for Web Analysts and Managers who are trying to create a Culture of Web Analytics. We assume that people know what we know because it seems so simple, right? Think again. Even simple metrics such as Visits, Visitors and Page views that seem so simple and no-brainer to you are difficult for others to understand.

If the numbers/data/reports that you present to the stakeholders do not provide them what they need in a simple and easy to understand format then you are in for a very though journey to building a Culture of Web Analytics.
To further illustrate my point, let me tell you about a situation that I personally had to go through.

I was approached by a mortgage agent who wanted me to refinance my mortgage and claimed that he had better rates than any other lender in the area. So I thought, sure let me see what this guy has to offer. So we met and I gave him my goals

The amount that I wanted to refinance
The interest rate range that I was comfortable with
$0 closing fee

I also asked him to tell me how much my monthly payment was going to be for those interest rates. We decided to watch the interest rates to see when they fall in my range and he promised to send me the daily interest rates.

That’s all.

Next day he sends me the following table with some explanation of the two columns. All this did not make sense to me, and I deal with numbers all day long. He also wrote that he will explain this to me over the phone.

So he called and tried to explain me the above chart but he still did not answer my earlier questions. See the problem?

If you have to call someone to explain your data that mean you have not done a good job of understanding him and his needs.

You see how easily you can alienate someone by not presenting the information in the right way. That’s the issue you face when you are trying to sell value of analytics within your organization. People look at your reports few times, find it too complex to understand and move over to other things. If that happens then you are done.

So do not fall a victim to “Curse of Knowledge”, step in your audiences’ shoes and make your reports really simple and actionable. Three key points to remember when presenting the data are

Understand your audience and their goals
Understand their level of understanding of the subject matter
Customize the data presentation to meet your audience level of understanding of web analytics and needs. Make it a no-brainer to understand and tie everything back to the business goals

Questions? Comments?

Follow me on twitter @anilbatra

Facebook Page http://www.facebook.com/pages/Anil-Batra-Page/130050670343547

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

Current Open Positions

Web Analytics Analyst at Designory. (formerly Agency.com) (Chicago, IL)

Web Games Analyst at Arkadium (New York, NY)

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)

Web Metrics Analyst at Omnitec Solutions (Alexandria, VA)

Web Data Analyst at Alzheimer's Association (Chicago, IL)

Creating a Culture of Web Analytics

2011-01-07T10:32:00.000-08:00

All those who have worked at companies which never used or do not use web analytics to make decisions about site changes, know how difficult it is to create a culture of web analytics. It is very hard. Building a culture of web analytics is a grueling uphill task.
After working with various client I have found that reasons for not using web analytics vary from company to company, some of the common ones are:

Gut feel has always worked or at least it seems like it has worked
It is an additional step in the process
New skills are required to use web analytics. They feel they don’t have the required skills for using web analytics
Fear of accountability i.e. now I will be measured and I don’t like that
The reports that they got in past were pretty useless
They didn’t believe in web analytics data because they have no clue on how the data was collected
They don’t understand how web analytics can help them
They don’t understand what web analytics is

The first reaction of many newly hired analyst/analytics manager is to start talking about KPIs, reports, what web analytics can do etc. But before you start digging into the data and analysis and start to talk about KPIs, dashboards etc. you need to understand the root cause of why analytics has not been used in the past. Understanding and tacking those issues will give you a better platform to build the culture of analytics on.

Here are few things you need to do before jumping into KPIs

Identify various stakeholders, who could benefit from web analytics, in the company. You don’t have to have a comprehensive list of every person but some that you think could immediately benefit and you can immediately help is also a good list to start with
Get a meeting with them, individually or grouped together in groups based on their roles/departments etc.
Agenda of the first meeting should be to understand why they have not used web analytics in the past and what they would like to see from web analytics group. Don’t talk about KPIs yet. This meeting is about hearing them, if they talk about goals, metrics etc. then fine but don’t jump to discussing KPIs
Make sure they understand that there will be a follow-up and you are there to help them not to use numbers to find faults. You need collaboration. Don’t let other people’s opinion about HiPPOs put you in an offensive or defensive position
Schedule a follow-up meeting to go over you analysis of the past meeting, address any concerns/issues that are preventing them to use analytics

The goal of this exercise is to make people feel confident that you can truly help them make data driven decisions without jeopardizing their job. You understand their concerns and are willing to address them.

During this process you will also find out who all (groups/individual) are more willing than others to help you build your case and will provide you small wins that you can use to garner more support. If you have an executive support e.g. your bosses boss then leverage that to help you.

At the end,remember, every company is different. The culture is different, challenges are different, political structure is different so it is critical you understand all those elements. It is not going to happen overnight so be prepared for a long rocky journey.

Comments/Questions?

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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)

Online Personalization: Issue Is With People Not Technology

2010-12-22T16:49:00.001-08:00

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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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

2010-12-13T15:06:00.001-08:00

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
at Conde Nast (New York, NY)
Web Analytics Manager
at Juggle (Swansea, IL)
Sr. Analyst Web Analytics
at Williams-Sonoma (San Francisco, CA)

FTC’s Proposed Privacy Framework

2010-12-09T12:15:00.000-08:00

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

----------------------------------------------------------------------------------------------------
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...

2010-08-24T22:16:00.002-07:00

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?

Do you like to be targeted?
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:

Do you like to save you money on things you buy online? I am sure the answer will change from Hell No, to Yes.
Will it be ok if we understand your online behavior so that we provide you better offers?.... Sure
Understanding your behavior will require us to keep track of stuff you are buying and browsing. Are you ok with that?…. Sure or Maybe
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

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

What do you think?

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5 Things That Could Be Hindering Your Conversions

2010-08-16T15:17:00.001-07:00

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.

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).
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.
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.
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.
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

2010-08-12T09:13:00.002-07:00

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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