Top 10 Things I Wish I Knew When I Started in Web Analytics

I remember what it was like to walk through the door at my brand new job, my very first job as a web analyst, wondering what I’d gotten myself into. In retrospect, what did I wind up learning the hard way? What would been helpful to know up front? What should I have been prepared to expect? With that in mind, here are 10 things I wish I knew when I started in web analytics:

  1. You will sit between the techies and the marketers. Figuratively, and maybe literally. Make friends on both sides of the fence.
  2. You will learn all about your business. Not just the stats part. Not just the web part. The work you do in web analytics will only make sense once you’ve put it in the general context of your business.
  3. Ahem, what is this thing you call a “Visit”? Know your standard web metric definitions by heart, and be able to recite them concisely for people who ask. They will ask.
  4. Dirty, dirty, dirty. Numbers won’t match, they won’t add up, they won’t make sense, sometimes they won’t even exist. Know how much dirt you’re willing to live with, then accept it and move on.
  5. You will learn to love the query string. You will come to see it as a beautiful haiku. You will know it backwards and forwards. You will repeatedly explain its usage to people who need to append campaign codes to URLs.
  6. CSV stands for “comma-separated value” … it’s a file format, every data analyst’s friend, and – inexplicably – it doesn’t even have to be comma-separated. Huh.
  7. Operators are standing by. Know the support hotline number for your commercial web analytics vendor of choice, and don’t be afraid to call. If you have one sticky note on your monitor it should be that number. Actually two sticky notes. The other one should say, “Patience is a Virtue.”
  8. Don’t fall into the “report monkey” trap. Manually-repetitious activities are not a good use of your time, so automate wherever possible. Strive to spend your cycles doing thinking fellers work, and leave robot work to the robots.
  9. You are not alone. Right now there are other web analysts sitting at their own desks, somewhere between the techies and the marketers, and they’re facing exactly the same issues that you are. You will meet them at Web Analytics Wednesday.
  10. Think long-term. From the very beginning, think about where you want your career to go and make every effort to develop in that direction. Your entry-level position in web analytics can/should/will lead to other things, so know what you’re targeting and go for it.

Originally Posted at: http://june.typepad.com/june/2010/03/index.html

 

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

Individual Visitors Tracking or Aggregate Data – Which One Is The Right Method?

Should web analytics tool track visitors as unique individuals or at the aggregate level? John Squire, Chief Strategy Office of Coremetrics says that tracking at Individual level is the way to go and this is how his company is differentiating itself (from Google analytics). Brian Clifton, former heard of Google Analytics in EMEA, responded by saying that aggregation is the way to go.

In my opinion both of them are right. Which route to go really depends on what you want from the web analytics tool?

Aggregate Data

If you are new to web analytics or you just want to track and analyze the overall health of your website, aggregated data will work for you. If you want to know how your marketing efforts are performing in terms of driving traffic or online conversions than aggregate data will just work fine for you. If you want to know which pages of your site are bleeding and then conduct A/B testing or Multivariate testing to improve them then aggregate data will work for you.
Individual Visitor Tracking

However as companies mature in their use of web analytics data they will need individual level tracking.

A company which is ready to do personalization will need to understand each individual browsing/purchase behavior to put the right offers/products in front of her. That is not possible with aggregated data.

It sounds perfectly ok to know that 75% of visitors abandoned the shopping cart but won’t it be nice to know who those 75% are or a way to convert at least some of those 75%? This is where individual tracking will come in handy. If visitors, who abandoned the shopping cart, leave an email during the process then you can send them a targeted email based on how far along they were in the shopping process, what products they had looked at, what product they had in shopping cart, etc. You don’t need to analyze every single data point but you can have business rules that can trigger those emails. However, to do so you will need to track at individual level. Even if you don’t want to send an email if you know the cookie id of the visitors you can put a personalized offer in front of them when they return back to your site and this will require tracking at individual level.

Individual tracking also comes in handy when the sales people call the lead that they just got from the website. Knowing what the person, who filled the contact us form, did on the website could provide a lot of information to sales person who can then tailor their conversation based on this information.

There are several more scenarios where aggregate data just won’t work. You will need individual level tracking.

I agree that tracking individual has privacy implication that need be properly addressed before tracking each person. However privacy issues also exist when you anonymously track visitors at aggregate level and those need to be addressed too.

So should you choose a tool that aggregates the visitor data or the one that tracks them individually? It all depends on what you want to do with that data. If you need help in figuring out what tool will work best for you feel free to email me at batraonline at gmail.com

Comments/Questions?

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Looking to fill your Web Analytics or Online Marketing position? Post your open jobs on http://www.web-analytics-jobs.com/
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Originally Posted at : Individual Visitors Tracking v/s Aggregate Data – Web Analytics, Behavioral Targeting and Optimization by Anil Batra

Web Metrics Pitfalls and Incentives

Website managers operate in a data rich environment. If it happens on your web page, & you decide you care about it, you can track it. And if you can track it, you can set goals around it & hold people responsible for meeting those goals…. The marketing team is responsible for transfers. Repeat visits are the responsibility of the engineering team. John is responsible for new account sign ups. With appropriate instrumentation & tracking (sometimes more difficult than it sounds!!), an organization can evaluate whether individuals & groups are meeting their goals. Evaluation is step one towards compensation, and when compensation is on the line, you can be damn sure people are going to be focused on making. their. numbers.  If you are a boss, YOU better be damn sure you are giving your people the right numbers to focus on.  In large organizations esp., many people end up  managing to a single number.  And throughout large organizations, even when many metrics are consulted, the drive for simplicity & collective understanding (and hopefully the organizational focus that results) will often lead people to a single number. One metric to rule them all, if you will.

One obvious way to go wrong when using this model is by picking the wrong metric(s). Again, focusing on a single number magnifies this danger.  For example… driving transfers to your site is your goal. Single-minded pursuit of THAT number can easily result in driving unqualified, unproductive traffic to your site. All while you comfortably make your goal. Oops. In this case it would be best to balance w/ length of session and/or repeat visits. Admittedly, this introduces complexity.

The more insidious way of going wrong is gaming the system. Metrics are about measurement. And measurement requires a known process. And known processes are gameable. You could change your URL structure to get previously uncounted pages counted; you could split articles into multiple pages to spike page views; you could redirect established traffic funnels.

And let’s not forget about who’s at the wheel… a bunch of type-A achieveaholics.  And that’s life, but if you give a type-A achieveaholic resources or an established traffic funnel and a number to make… suddenly massive amounts of traffic are being redirected to achieve goals. And on the collateral damage side of the equation.. the users.  They end up getting jerked around so people can make their goals & get paid (worthy goals, no doubt!).

And here’s an additional downer, if an independent party is responsible for measurement & you get caught gaming their system, it could sully your relationship w/ them & look bad publicly. Internally, the consequences are potentially worse. You’re going along thinking you are doing fine, all the while you could be undermining yourself.

So what do you do?  Most people say to go simple.  But single-minded focus on achieving a number can blind you to the complexities of what is happening on your website.  Instead, I recommend countering the drive for simplicity with some supplementary complexity.  Single numbers (or small numbers of numbers) are powerful tools for clarity & focus.  This is especially valuable in a large organization where people can easily lose sight of their goals.  But there have to be additional numbers that people watch.  Ideally these would be metrics that can provide contrary evidence to success in the face of growth in the key metric.  To repeat the example from above, if driving trials is your goal, stay focused on that number, but also keep an eye on repeat visits, & length of session.  Ultimately, you want to direct your numbers towards your users.  Of course, in a cookie based tracking system, you can’t really identify the user all that well.  But that’s why the job is fun, or at least, they need someone to do it.

Originally Posted at: http://www.menggoh.com/63/web-analytics/web-metrics-pitfalls-and-incentives/

Analytics Mission Statement and Team Structure

Analytics Mission Statement: “Bring data to the masses and make data-driven decision making a reality”


How do you build an analytics team? Tell your manager you need money to measure social media! No seriously, I heard it’s easy to hire people, everyone on the “interweb” is “social media experts”. For some of us, we have multi-channels analytics need, SEM, Display Advertising, good ole fashion Direct Marketing and a whole bunch of other internal data we need to deal with. Building a team could be quite daunting.

Before I starts the usual blah blah on how to do hiring, I want to share a story.  In the not so distanced past, I had my career review(here at the mother ship we take it seriously), the memorable feedback I received stand in my way of promotion is leadership. “You have excellent management skill, Meng; but you need to improve you leadership” said my manager.

What is Leadership? For me, leadership is to have vision, to anticipate future growth and direction of the company, have the courage to take calculated risk and execute. So…do you have the vision, courage and patience to bring ass-kicking analytics practices, insights and in turn “mucho mullah $$$” to your company? Do you have the courage to take calculated risk? Be the Hokage of your clan, leads your ninjas to bring insights to your organization against the corporate hacks, bureaucrats and simple-minded marketers (I kid, I kid, I am a marketer at heart). Have you been wrong many times? If you haven’t, it’s time you try something new because you haven’t been “A/B testing” everyday and doing your “MVT”. In fact, My A and B both sucks many times!

Our team has very rigorous process of setting yearly commitment tied to precise deliverable. Having a analytics mission statement help guides me to focus on the right thing and not waste resources. I know mission statement is corny, I don’t care, I am writing it anyway. My team’s mission statement is “Bring data to the masses and make data-driven decision making a reality”. Here are a few sub-objectives to bring more clarity to that mission statement:

  1. Build a sustainable data infrastructure (must..resist..the urge..to knock..Google Analytics) to measure multi/cross-channels digital marketing ROI. I have two types of audiences: a. the big bosses, you know, the gazillions Directors, GMs, VPs around here. b. the marketers and agencies. For the big bosses, we deliver “BI” and KPI, for the marketers, we delivers data (see #2). We build platforms and tools to enable marketing operation, reporting and analytics, share best practices and improve Go-To-Market efficiency. For example, we build our own data warehouse and segmentation tools, our own marketing process management workflow tool and execute our direct marketing, all in-house because scale is the challenge with everything we do here. Our scale is enormous in comparison to other companies, we collect petabyte of data, from which I need only a few drops of marketing traffic, a strict qualitative ROI model would’ve #failed as our primary objective is still mainly to build brand. We have our internal awareness and perception tracking system to measure traditional media such as TV ads and brand improvement. We use comScore and Compete for research, out of those insights we then have to build targeting capabilities, it’s useless if we can act on these finding.
  2. Knows where my team fit in and build efficient organization structure. I am part of centralized Business Intelligence and Customer Intelligence team, we serve both product management and marketing and I am on the marketing side.  On the marketing side, each marketing department from different business groups have their own marketing analytics people, they are our partners. The reason behind this structure is ..well, it’s your money, if you wasted it buying $20 CPC keyword because your relevancy and quality score sucks, well it’s your fault. Simple as that.
  3. Review and improve our processes, conduct researches on various marketing campaigns and channels, share best practices across different business groups. Publish training and information so that marketers worldwide can efficiently leverage our capabilities.

Now I have a better idea on what type of resources I need to deliver my commitment. I have databases to maintain so I need a SQL expert. I have campaign sites to tag so I need an instrumentation consultant. I need to pull data regardless of what all the expert say, so I need reporting robot. Lastly I need “Analyst”, my ninjas, the one who dig into the data and find the golden nuggets. I am ready to build a team. As you can see, my needs are very different from yours, so my team would be very different from yours even though we are in the same analytics field of work.

If you have a mission statement for your team, I would love to hear it. If not, maybe it’s time to create one.

Originally Posted at: http://www.menggoh.com/72/management/analytics-mission-statement-and-team-structure/

Web Analytics – Tool For Measuring Off Line Efforts

Web Analytics, as the name suggests, is used for measuring and analyzing the web traffic. Online campaigns can be effectively measured by almost all of the web analytics tool in the market.
To measure online campaigns you assign a unique campaign identifier at the end of the landing url and then use your analytics tool to see how many people responded to the end and then track them all the way to end conversion. It is easy (sort of) to calculate your Return on Investment on online campaigns.

You can use the same method to track offline campaigns, print, in-store display ads, billboards etc.

Here is how it works

  1. Create a campaign tracking code(s) to track this campaign just like you do in online campaign
  2. Create a easy to remember unique URL e.g. http://www.SeattleIndian.com/saveondining
  3. The URL created in step 2 above redirect the users to actual landing page passing the campaign variables.
  4. When a user arrives on page created in step 2, the user will be redirect as in step 3 and it will appear in the web analytics tool as the user is coming from a campaign.
  5. Add the URL created in step 2 to your print advertising and you are done.

Example:
I will be using Google analytics (http://www.google.com/analytics) for this example

  1. You have a campaign called “Save on Dining” running as a Half page color in local newspaper
  2. Your campaign variables are
    utm_source=Newspaper
    utm_medium=Print
    utm_content=HalfPageColorAd
    utm_campaign=SaveOnDining

  3. Create a easy to remember unique Vanity URL e.g. http://www.SeattleIndian.com/saveondining
  4. The URL created in step 2 above redirect the users to actual landing page passing the campaign variables.
    http://www.seattleIndian.com/dining.asp?utm_source=Newspaper&utm_medium=Print
    &utm_content=HalfPageColorAd&utm_campaign=SaveOnDining
  5. When a user arrives on http://www.SeattleIndian.com/saveondining will be redirect to http://www.seattleIndian.com/dining.asp?utm_source=Newspaper&utm_medium=Print
    &utm_content=HalfPageColorAd&utm_campaign=SaveOnDining

Note: You can also set some variables on the Vanity URL web analytics tracking code instead of redirecting to a new URL.

Add the URL created in step 2 to your print advertising and you are done.

So why did I write this article? Well, there are two reasons why I decided to write this article today.

  1. I have been involved with tracking campaigns for a fortune 50 company and this topic has come several times. So I had to write this one day.
  2. I just read an article by Kevin Newcomb (http://www.clickz.com/showPage.html?page=3623461) about how one company successfully tracked offline campaigns so I thought this is a good time to write it so that users not only know that it can be done but how it can be done.

As always, I would like to hear your experiences with offline campaign tracking.

Originally Posted at : Web Analytics – Tool For Measuring Off Line Efforts – Web Analytics, Behavioral Targeting and Optimization by Anil Batra

3 Tools for Measuring the Virality of Your Content

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

  1. Inbound keywords – keywords that visitors searched to get to your site (AddThis has a different variation of keyword report)
  2. 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.

Originally Posted at : Web Analytics, Behavioral Targeting and Optimization by Anil Batra

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Looking to fill your Web Analytics or Online Marketing position? Post your open jobs on http://www.web-analytics-jobs.com/
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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 siteMeasuring 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 pageSince 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?

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
    1. 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.
    2. 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.

Read more: 5 Web Analytics Misconceptions – Web Analytics, Behavioral Targeting and Optimization by Anil Batra http://webanalysis.blogspot.com/2010/06/5-web-analytics-misconceptions.html

What is Bounce Rate?

Time and again my clients ask me about Bounce Rate. This made me think that there is still confusion about what is bounce rate and exit ratio. The three main questions that have come up are

  1. What is bounce rate?
  2. What is the industry standard for bounce rate?
  3. What causes high or low bounce rates?

I am going to answer these questions in this post.

What is bounce rate?

Bounce rate is the percentage of visitors who enter a site (or a page) and then leave immediately. Think of a ball (visitor) that is thrown (visits) towards a table (site). It hits the table and bounces back without rolling (visiting any other pages).
Generally, “leave immediately” in the above definition means without going to any other page. However it could also be expressed in terms of time spent on site, say users who spend 5 seconds or less on the site irrespective of the number of pages they view.

Bounce rates are calculated both at the individual page level and at the site level. For an individual page, bounce rate is the ratio of visitors who enter the site from that page and leave without going any deeper, to the total number of visitors who enter the site through that page. In other words it is single page visits/ total entries to the site through that page.
At the site level, bounce rate is simply single page visits/total site visits.

Note: If a visitor enters though a page, refreshes it (manually or via auto refresh such as ESPN score page or MSN money page) but never goes beyond the first page the visit is not counted in the bounce rate.

  • Bounce rate is often confused with Exit Ratio. Exit ratio is usually expressed as the percentage of exits from a page to the total number of visits to that page. As a side note: A lot of times exit ratio expressed as % of visits can be misleading. In most cases, page views are actually more appropriate than visits for this ratio. Why page views and not visits? If I view the same page twice during the same visit, and after one of those page views I exit, shouldn’t my exit ratio be 50% rather than 100%? The first view of this page was compelling enough for me to further engage. A 100% exit ratio would indicate a problem that may not be there.
  • Bounce rate is confused with Single Page Visit Ratio: Single page visit ratio is calculated as a percentage of single page visits over total visits to a page.
  • Here are two examples that will help you clarify

    1. A visitor who enters site at home page and then goes to contact us page and leaves from contact us will be counted in the exit ratio from the contact us page but won’t be counted in the bounce rate of contact us page.
    2. A visitor who enter the site from contact us page and then leaves without going any further counts in all three, exit ratio, single page visit ratio and bounce rate.

    So to Recap:

    Single Page Visit Ratio= Single Page Visits to the page/ Total Visits to the page
    Exit Ratio= Total Exists from the page/Total Visits on the page or Total Exits from the page/Total Page Views of the page (see explanation above)
    Bounce Rate= Single Page Visits to the page/Total Entries to the site through that page.
    Note: All of the above three are generally expressed as percentages.

    What is the industry standard for bounce rate?

    The simple and short answer is that there is no industry standard. I know you don’t want to hear that, but it is true. There is no industry standard. There are some ranges that I will share shortly but we can’t call them industry standards. There are a lot of factors that influence the bounce rate, so you really can’t compare bounce rates of one site (or page) to another. I have listed those in the next section.

    The goal of the site should generally be to reduce the bounce rate to as low as possible. The lower the bounce rate the better job the site is doing to keep users engaged. One exception may be a site that is intended to accomplish all relevant user engagement on it’s landing page. This is more common on say, a campaign landing page intended to sign up users for direct marketing emails.

    Bounce rate is very unique to your site and page. The best way to know if you are doing better or worse is to set your own baseline and compare your performance over time.

    I have seen most bounce rates fall between 18 – 30% on home page and the site overall. Any page with a bounce rate higher than 30% should be looked at closely. I am not saying that you should not analyze the pages below 30% bounce rate. Remember there is always room for incremental improvement.

    There are several factors that determine the actual bounce rate of any page.
    Here are some of the numbers that were listed by Steve Jackson based on his experience with various sites.

    Source: http://tech.groups.yahoo.com/group/webanalytics/message/6116

    Retail sites driving well targeted traffic 20-40% bounce.

    Simple landing pages (with one call to action such as add to cart) I’ve seen bounce at a much higher rate, anywhere from 70-90%.

    Content websites with high search visibility (often for irrelevant terms) can bounce at 40-60%.

    Portals (MSN, Yahoo groups etc) have much lower bounce rates in our experience 10-30%.

    Service sites (self service or FAQ sites) again usually lower 10-30%.

    Lead generation (services for sale) 30-50%.

    Per Steve,
    “I must stress that all the above figures are based purely on our own
    experience after working with clients. I wouldn’t advise you base an
    optimization model around these numbers. We advise that when forming a
    benchmark, that you do it internally. Take the average bounce rate over a
    given period on your current site. You need to have at least 1000 entries
    coming from normal sources to get reasonably actionable data.
    Measure what the average bounce rate is and then work to get that down.”

    What are the factors that affect the bounce rate?

    Below are some of the factors that determine the bounce rates. You can use this as a checklist to diagnose a high bounce rate issue.

    1. Source of your traffic – Each source results in a different bounce rate. When setting your baseline create overall baseline and baselines for each traffic source e.g. display advertising, organic traffic. With one client I found out that the traffic driven by searches (paid and organic) and sources other than campaigns had a much lower bounce rate than traffic that was driven via display ads. Their display ad had 90% bounce rate while other traffic only had 35% bounce rate. Their overall bounce rate was around 55%, way lower than 90% and giving them a misleading picture.
    2. Search engine ranking of the page – A page which ranks higher on irrelevant keyword will get a higher bounce rate. I have seen this to be an issue a lot of times. I wrote an article on how to follow the search and reduce your bounce rate.
    3. Type of Audience – If you are advertising and reaching the wrong audience you will see higher bounce rate. Bounce rate will tell you if you need to better target your ads.
    4. Landing Page Design – Landing page design affects the bounce rate. I suggest A/B testing to improve after you have set your baseline. No matter how low you go there is always an opportunity for improvement unless you somehow achieved 0% bounce rate.
    5. Ad and Landing Page Messages – If the messages on your banner or search ads are not aligned with the messages on the landing page then the chances are you will have one of those 50% + bounce rates. Make sure messages are aligned and give visitors a clear call to action. Many a times I have seen marketers sending users to a generic page instead of an appropriate landing page. This can (and will) result in higher bounce rates. Again A/B or multivariate testing should be used to reduce the bounce rate.
    6. Emails and Newsletters – Subject lines, to and from, links, banners, the layout of email and the landing pages all work in tandem. They can either result in a great user experience and hence lower bounce rate or can result in a disaster. Do testing (More on this later in another post) to reduce bounce rate.
    7. Load time of your page(s) – A longer load time can result in visitor bailing out of the site causing higher bounce rates. Conversely, users can hit the refresh button, thinking there was a problem with the page load. This will incorrectly reduce bounce rate.
    8. Links to external sites – A page that has links to external sites (or sub domains/ pages that are not tracked in the same data warehouse) will show higher bounce rates.
    9. Purpose of the page – Some pages’ purpose is to drive users inside the site while other pages provide the information that user is looking for. A page that provides the end result can show higher bounce rate. One example is the support page on my bank’s web site, I have this page bookmarked. Whenever I need my bank’s phone number, I go to my favorites, pull this page, get the number and leave.
    10. Other factors – Pop-up ads, pop-up survey requests, music, streaming video, all can have an adverse effect on bounce rates if users become annoyed.

    Hope this clarifies the confusion around Bounce Rate. I would like to thanks Brad Gagne, who challenged my thinking on this subject, provided his valuable insight and proof read this article.

    Contributed By : Bounce Rate Demystified – Web Analytics, Behavioral Targeting and Optimization by Anil Batra

    Real Time Analytics Tools

    Below is a list of Real time Web Analytics tools that you can you to optimize your landing page and conversion paths. We will continue to update this page so that you have the latest information. If you find something that we should include then please email us.

    Tools

    Tool Price Site
    Clicky Free Trial http://getclicky.com/
    Clicktale Free Trial http://www.clicktale.com
    ShinyStat Free Trial http://www.shinystat.com/
    Reinvigorate Free Trial http://www.reinvigorate.net/
    StatCounter Free http://statcounter.com/
    Woopra Free http://www.woopra.com/
    Performancing Free Trial http://pmetrics.performancing.com/
    Piwik Free http://piwik.org/
    SiteMeter $6.95 and up http://www.sitemeter.com/
    TraceWatch Free http://www.tracewatch.com/
    Chartbeat $9.95 and up http://chartbeat.com/
    W3Counter Free Trial http://www.w3counter.com/
    Histats Free http://www.histats.com/
    GoSquared Free Trial http://www.gosquared.com/
    DaCounter Free http://www.dacounter.com/

    Source: http://www.Optizent.com

    Books