Showing posts with label web analytics. Show all posts
Showing posts with label web analytics. Show all posts

Wednesday, 7 August 2013

One Tip for Enhancing Anonymous Visitor Data

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

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

Also, see 3 Techniques for Expanding your Email Reach

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











 
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Wednesday, 7 March 2012

Finding (Not Provided) Keywords in Google Analytics

I rarely write tool specific posts on this blog but since I have recently been asked by a few people about this issue and it affects every web analytics tool, I decided to post it here.

A few months ago, Google, the search engine, started encrypting searches for user who are logged into their Google account while conducting the search. As a result of this encryption, the keyword that the visitors search to arrive to your site is not passed in the referring URL. Web Analytics tools rely on the keywords passed in the referring URL to build the search engine traffic report and in the absence of the keywords there is nothing to report, though they still see that the visits came from Google search. So Google Analytics now marks those visits that do not have a keyword but come from Google with “(not provided)” keyword instead of the actual keyword.

Finding those keywords

Google still tracks all the keywords search by logged in users but just does not pass it in the referrer to the site that the user clicks through to. These keywords are available in the Google Webmaster Tools. To see the report you will have to register your sites in Google Webmaster Tool. Google Webmaster tools will allows you to see all the keywords that were searched, the number of clicks your site got, the average position of your site for those keywords and the landing pages.

If you are not using Google Analytics on your site then you will have to login to Webmaster Tools anytime you want to see those reports.

If you are using Google Analytics then you can connect Google Analytics reports and Google Webmaster tools to get Webmaster reporting within the Google Analytics interface.
However there are three issues with this report when used with Google Analytics (or any another web analytics tool)
  1. You don’t get other metric (e.g. goal conversion) about the visits that arrived from the keywords.
  2. This list of keywords includes not only the keywords marked with “(not provided)” but also the other keywords that you see in Organic traffic report. So you will have to do extra analysis to see which keywords are hidden under “(not provided)”.
  3. If you look at Google Webmaster tool report then you will notice that there are a lot more impressions and clicks than those displayed in the Webmaster report and the Google Analytics report (see below). I was not able to find a reason why Google is only displaying the partial number of keywords, if you know the reason then please let me know.
To leave a comment please visit my new blog at http://anilbatra.com/analytics/2012/03/finding-not-provided-keywords-in-google-analytics/

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Digital Analytics & Marketing Jobs
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Wednesday, 29 February 2012

Move Web Analytics Data Out Of Silo

Web Analytics tools are great for providing a good view of one channel i.e. your website (ok, maybe slightly more than one channel e.g. some email, some social media, some offline). They worked great in silo for first few years of the internet because the only way for customers to interact with your brand online was on your site and websites were not an integral part of the business. Nowadays the story is different, customers interact with your brand in so many way, your website is just one small part of the whole "web" ecosystem and "web" is just one part of the whole "customer" experience and buying cycle ecosystem. Customer’s don’t think and operate in one channel i.e. your website. However, many "web analytics" tools do not even provide you full view of a customer journey and interactions online let alone the offline journey.

To understand today's customer and performance of your marketing efforts, web analytics data has to move out of it's silo and needs to be integrated with other data sources.

Many of you might be already be using 3rd party solutions to pull data from few sources into a dash boarding tool. That is a great start but it still does not provide you a complete view of customer journeys. For example, just because you have social media mentions on the same dashboard as your on-site analytics data does not tell you if those mentions are from your customers or somebody, who is neither a customer nor is your target customer, just blabbering in social media. But I will give you credit for thinking outside the Web Analytics tool.

To understand complete customer journey (i.e. 360 degree view of customer) and to conduct analysis that take you from marginal improvements in conversions to something that has a huge impact on the business you need much more detailed data than a web analytics report or a dash boarding tool can provide. First, you need to collect individual data for each customer in various channels then warehouse the data in one place where you join various sources via common key such as customer id, email address, phone number etc. Only then you can create and run complex cross channel queries to understand try customer behavior and campaign performance.

Many mature organization are already doing it or are working on it. If you are not then it is about time to start thinking about if you want to stay competitive.

Don’t think that just because you are using Google Analytics you can’t have this level of data because you can. You just have to push yourself and start thinking outside what your web analytics tool can provide.

How Can You Do it

Web Analytics tools already anticipated this needs so they have built a way for you to get the data out easily. You can use either of the two methods listed below to get the required data
  1. APIs – Many tools like Google Analytics provide data via APIs. Use those APIs to pull appropriate data into your datamart/datawarehouse.
  2. Data Feeds – Many tools provide data in a flat file that you can use to populate your datamart.
Here are few things to keep in mind before you start putting this data in your datamart
  1. Make sure your tools are configured properly to collect the data in the right format and
  2. Your data transformation process should be able to understand the difference between various custom variables that you have used in the data collection
  3. Various data sources also need proper identifiers (keys) to match them together.
This is not going to be an easy project but this is a critical step in using your web analytics data to stay competitive.

There are few 3rd companies who are already providing tools and service to help you with it. I recommend looking at iJento Datamart solution (Note: I work for iJento). You should also check out Gary Angel’s Blog. Gary has worked and written extensively on this topic.
If you have any question, I will be happy to chat. Email me.

Questions/Comments?

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Web Analytics Jobs
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Wednesday, 1 February 2012

Bounce Rate Optimization Is Not Always The Cure: Analyzing and Optimizing Campaigns

This is part II of the series on Analyzing and Optimizing Campaigns. I wrote in my previous post that when analyzing campaigns many web analysts just focus on the web analytics data. Some venture to include the cost and impression data of the campaign but they still don’t have a complete view.

In this post I will show you how their lack of complete view results in wrong analysis and wrong conclusions.

Below is the data I used in my last post. This is the type of data most Web Analytics tools provide and hence “Web Analysts” tend to use.



What is missing?

Where is the cost of products and profit margin data? Without that information, you don’t know if this campaign is successful or not. Right?

The sad reality is that many web analysts don’t have access to profit margin data and hence they look at what is available to them and start recommending A/B testing (see my post One Awesome Web Analytics Tip: Think Beyond Web Analytics). And their first target generally is Bounce Rate. Oh… look bounce rate is 50% it is too high, we need to reduce it. Right?

Wait...There is More...

Let’s assume that you are able to get hold of additional data. Now let’s see how the campaign looks if we add that data. Below I have added cost of Goods Sold data (keep in mind there are additional costs in real life).


It is evident now that the campaign is bleeding money. If your business goal is to increase conversions at any cost then you might be ok but if you goal is to increase conversions without losing money then this campaign sucks.

Ok, so what should we do now? If your answer is still bounce rate then you are wrong. Look at the data below, even with a bounce rate of 0% you will never make this a profitable campaign.



So next time get all the data before you jump to the conclusion that all you need to do is reduce “Bounce Rate”. Bounce Rate Optimization looks tempting to tackle but it is not always the cure.

Stay tuned, more coming soon on this subject.

Follow Me on Twitter: @anilbatra
Facebook: https://www.facebook.com/TheAnilBatra
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Tuesday, 24 January 2012

Analyzing and Optimizing Ad Campaigns – Part 1

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

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Thursday, 5 January 2012

One Awesome Web Analytics Tip: Think Beyond Web Analytics

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:

  1. 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.
  2. 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?
  3. 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.
  4. 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.
  5. 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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Wednesday, 7 December 2011

Do you need Real-Time Web Analytics?


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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Wednesday, 30 March 2011

QR Code Analytics

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

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Friday, 4 March 2011

Context is Critical: Creating a Culture of Web Analytics

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

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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

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Tuesday, 15 February 2011

The Curse of Knowledge: Creating a Culture of Web Analytics

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

  1. The amount that I wanted to refinance
  2. The interest rate range that I was comfortable with
  3. $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
  1. Understand your audience and their goals
  2. Understand their level of understanding of the subject matter
  3. 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)

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    Friday, 7 January 2011

    Creating a Culture of Web Analytics

    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?



    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 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)

  • Web Analytics Manager at Tig Global (Chevy Chase, MD)


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    Monday, 13 December 2010

    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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    Monday, 12 July 2010

    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?
    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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    Thursday, 10 June 2010

    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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    Wednesday, 2 June 2010

    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

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