September 19, 2011

Important Mobile Analytics Metrics

Mobile traffic is projected to surpass desktop traffic by 2015 and hence it has never become more important to analyse & optimizing your site for mobile. This ofcourse requires to decide which metrics to optimize our mobile site against.
Let us divide the all metrics into 3 buckets : Acquisition metrics, Behavior metrics, & Conversion Metrics:
  • Acquisition: The following three metrics track user acquisition from various sources. These represent the top end of the conversion funnel. Check all metrics across both mobile and desktop use.
    • Visits: How many people visit your website from either mobile or desktop
    • Unique visitors: How many different people visited your website
    • Pageviews: How many times was a page on your website viewed
    • To Remember: When comparing mobile and desktop performance, it’s important to realize that desktop is still the most prominent way to view websites. Therefore, people visiting on a desktop will view slightly more pages.
    • An interested analysis: observe how acquisition metrics change over time. Is mobile traffic growing on your site? Is overall traffic growing on your site? How is the ratio of mobile to desktop traffic changing?
  • Behavior: The next three metrics track user behavior, providing insight into whether a site moves users toward the outcomes it was built to achieve.
    • Pages per visit: How many pages are viewed during a single visit ob mobile vs. desktop
    • Time on site: How much time does each visitor spend on your mobile website Vs On your desktop site
    • Bounce rate: How quickly do mobile/desktop users turn away when they hit the site
    • When we compare behavior metrics on the desktop site vs. mobile site, we see that visitors on desktop tend to delve slightly deeper than visitors on mobile and, consequently, stay longer on the site. Additionally, visitors on mobile are slightly more likely to bounce off the site (a “bouncer” is a visitor that visits only one page and then leaves).
[ Google explains how to understand user modes on mobile. The company classifies mobile users into three categories of interaction.
  • Repetitive now: These people track time-sensitive information on an ongoing basis, like stock quotes or sports scores.
  • Bored now: These people seek distraction or entertainment while waiting in line at the bank or on public transit, for example.
  • Urgent now: These people need location-sensitive information about a specific situation, such as the nearest pizza restaurant or the next available movie showtimes.
Understanding your mobile visitor’s “user mode” sheds more light on your behavior metrics over time. For example, a “bored now” visitor wants to be entertained; therefore, longer time on site indicates a satisfaction of that need. By contrast, a “repetitive now” visitor can have a high bounce rate, short time on site and low number of pages per visit, but it’s still a successful interaction.]
  • Conversion: The last two metrics – conversion rate and average order size – track user conversions and the value of each of those conversions. These numbers show how visitors on both desktop and mobile contribute to an ecommerce site’s bottom line.
    • Conversion rate: How many visitors take the next step, whether to purchase, register or request more information
    • Average order size: For ecommerce conversions, what’s the average dollar amount per order. Most sites typically find that visitors on the desktop convert at a higher rate than mobile visitors. This is to be expected, as mobile web purchasing is relatively new and habits take time to establish.
    • Of course, mobile can still play a large role in the purchase process even if the transaction isn’t actually made on mobile. A recent Google study found that 79% of shoppers use their mobile device to shop, and 70% of them use mobile in-store.
    • Microsoft research found that shoppers who research products on their mobile devices are ready to buy; 70% take action within an hour, but 70% of people on desktop PCs take action within a week.
Impact of the Tablet
  • Any analysis of mobile performance has to factor in the tablet, which has quickly emerged as the third digital screen in consumers’ lives, in between desktops and smartphones. 
  • While smartphones are used on the go, at work and throughout the day and evening, the tablet is a lean back device frequently used at night.
  • What does this mean for your metrics? For starters, don’t consider all mobile devices equal. A shopper or searcher on a smartphone has markedly different needs and motivations than their counterpart who uses a tablet.
  • When you break your mobile metrics down between smartphone and tablet usage, you may notice trends. Perhaps tablet users visit more pages, spend more time on each page, and convert at a higher rate than smartphone users.
Evolution of Web Analytics

Social media Tracking & Analysis Tools
  • Twitter's Analytics Tool For Tweets, Traffic & Buttons
Twitter Analytics, Social Media Analytics, Web Analytics
  • Twitter's Web Analytics Tools will hep webmasters (and Tweeters) see how their content is being shared and how their buttons are being used.  
  • This new platform integrates fully with the new t.co shortener to help see content distribution. 
  • The t.co ‘link wrapper’ is now making up 95% of all tweet and Twitter buttons are on more than 3 million websites.   
  • Until now, only advertisers had any access to analytics on Twitter.
  • Twitter now sends over 100 million clicks to sites across the web everyday, and Twitter Analytics is geared to help analyze these clicks. 
  • Some of the key features that will be available are: 
    • Every tweet that contains a link to your site 
    • A percentage breakdown of how many times the tweet button is used Chronological breakdown of tweet button usage 
    • A “tweet” leaderboard to find out what content is being shared the most and what content is sending the most traffic
    • The product is currently in a private beta and Twitter is planning on launching this to the public  ”as soon as we can.” 
    • An API will also be available for 3rd party applications to harness the analytics information.

ConversionBuddy: An Intelligent Facebook Data & Analytics Platform for Social Media Marketers
ConversionBuddy, a data and analytics platform for brand marketers has been launched by Buddymedia
  • ConversionBuddy allows brands to track connections to boost conversions by gaining insight into the number of shares, tweets, conversions and more. 
  • Brands can segment data by demographic and even determine which audience segment shares social content most frequently and which audience generates the most traffic and revenue per share. 
  • The new product will also show marketers which content and features are most popular and how they travel across multiple social networks, which social networks and emails generate the highest revenue per share and more. 
  • ConversionBuddy is actually a result of Buddy Media’s acquisition of social commerce and analytics startup Spinback earlier this year. The company raised $54 million in Series D funding led by GGV Capital with Institutional Venture Partners, Bay Partners and Insight Venture Partners. And Buddy Media’s revenue has more than doubled since the end of 2010, and could be as high as $40 million. Buddy Media provides an all-in-one social media management system to help create, manage and track social campaigns on Facebook. The platform lets brand managers agencies create, manage and track Facebook pages in a variety of languages to drive and increase user and brand engagement. Users don’t need to have any prior FBML knowledge to create pages on Facebook and can create sleek and interactive pages fairly easily. 
ConversionBuddy Social Media Analytics tool

Use of Multiple Web Analytics tracking tools
  • No analytics provider seems to have invented the perfect system to meet every need
  • Increasing number of advertisers using multiple systems together in order capture a wider set of data for reporting and optimization purposes. 
  • This is generally some combination of a search/display/Facebook technology provider and one or more analytics systems such as Google Analytics, Omniture, Web Trends, or Doubleclick. 
  • Each system requires some combination of dynamic parameters or URL redirects to capture the necessary data about a click and/or conversion, so there’s a science behind getting all the systems involved to work harmoniously. 
  • Multiple systems can function together if the following criteria are met: 
    • Custom parameters can flow through one system either onto the landing page or reports can be generated including custom parameters and imported into another system. 
    • URLs do not require redirects; or if a URL requires redirects, it does not have to be the first redirect. 
Relationship between Analytics & Redirects
  • Below is an example URL using multiple redirects. The first redirect is in normal font, and the second redirect is italicized at the end. Note that the second redirect is URL encoded within the first: http://akatracking.esearchvision.com/esi/redirect2.html?esvstue=13133462492&esvt=4-GOUS{ifsearch:E}{ifcontent:C}543&esvq={keyword}&esvadt=939929-1-10-1&esvcrea={creative}&esvplace={placement}&transferparams=1&esvaid=41662&useesvcid=1&esvcid_fwdsize=L&url= http%3A%2F%2Fclickserve.us2.dartsearch.net%2Flink%2Fclick%3Flid%3D430000048238949 
  • Information from the original source of traffic can only be associated with the first redirect in a string of redirects. This is because once a URL has been redirected, the URL itself changes and the information from the referring domain (ex: google.com after a search has been executed – http://www.google.com/search?sourceid=chrome&ie=UTF-8&q=mens+shoes&utm_source=google&utm_medium=cpc) is no longer there. If an advertiser is using multiple redirects (one redirect wraps another as in the example above) the second redirect cannot capture any information from the original traffic source. This greatly limits the capabilities of the second redirect. 
Doubleclick Search V3 Analytics Problems
  • Historically, analytics systems have not attempted to block an advertiser from using other systems by requiring their redirect to be first. 
  • This works because an analytics system use URL parameters to capture their data and do not require a redirect. 
  • Google, with the release of Doubleclick Search 3, is preparing to do just that. Doubleclick team, they indicated that DS3 must be the first redirect. 
  • This is because DS3 utilizes a bi-directional synchronization system which overwrites unrecognized URLs in the search engine platforms. 
  • This is a very useful feature used to ensure tracking is correct for their system
  • However, by requiring it to be used, Doubleclick is forcibly limiting an advertisers ability to utilize other tools in conjunction with Doubleclick Search. 
  • In some cases, the advertiser will have to choose between using Doubleclick Search and the other technology providers if the other provider requires a URL redirect.  
  • It’s an aggressive move and will force more nimble startups to get crafty and utilize URL parameters to capture all the data previously only generated using a redirect. 
DoubleClick analytics tool for advertiser
  • Advertisers use Doubleclick because it is an ad server tied into an analytics package. 
  • Running multiple advertising channels through one system allows an advertiser to mitigate double counting conversions: a common phenomenon when using multiple tracking systems (technology provider with proprietary tracking and an analytics system). 
  • From a functionality standpoint, Doubleclick Search and DART for Advertisers (DFA) are definitely not the most advanced systems available save for specific features, such as the universal floodlight tag.
Data Analysis Tools / Softwares
Business Objects for Data Analysis
The following video demonstrates features / functions of business objects for data analysis

For Excel Analytics Tips please go through my post on Excel Analysis tips & tricks

Emerging Analytics Trends
  • Increasing sophistication of analytics software and the need for a simplified approach to presenting the results of complex analysis. 
    • Analytics tool vendors have realized over the past couple of years that to be effective and reach the widest audience, analytics software should present the results of sophisticated analysis on large and complex data sets in an easy to read, actionable format. 
    • Most tools today have advanced visualization capabilities – so much so that sophisticated visual presentation has become an absolute requirement for analytics tools.
  • Transition of analytics out of the office and onto the mobile devices of executives. 
    • For some years now, sales reps and field technicians have been able to perform simplified analytics on handheld units. However, true analytics functionality has been lacking – especially the further up the management chain you are. 
    • With the advent of improved mobile operating systems and widespread adoption of standardized mobile platforms, mobility has moved from the wish list to the must-have list. 
    • It helps executives achieve true collaboration – no matter the location or the time – with analytics delivered via mobile technology. 
    • With mobile analytics, whether you’re in Budapest, Bangkok or Baltimore, you can have the information you need to make decisions when you need to make them.
  • Companies are starting to realize that analytics gives them to gain a competitive edge. 
    • In their book, "Competing on Analytics,” Tom Davenport and Jeanne Harris define an analytical competitor as an "organization that uses analytics extensively and systematically to out-think and out-execute the competition.” These analytical competitors use analytics as a strategic weapon to share information enterprise-wide, grow revenues and streamline operations in hopes of winning in this ultracompetitive, highly economically unstable business environment.
  • A trend that is particularly worrisome is the problems that many companies are having dealing with “big data,” which is the term being bandied about to describe the combination of growing data volume and complexity. 
    • To be able to leverage analytics software effectively, it‘s essential to have a handle on how much and what types of data you have to analyze. 
    • It‘s important to have the tools and policies in place to help achieve data quality in critical areas. 
    • It’s also essential to be able to work with both structured and unstructured content. 
    • It’s also a necessity to have newer parallel processing technologies in place to handle the sheer volumes of data required to run the complex analytical algorithms that can help you spot emerging trends and potential problems.
  • Agile development techniques, new data quality tools and methodologies, and technical innovations like in-memory analytics are taking analytics (and business intelligence in general) out of the realm of the data warehouse. 
    • With the demands executives are placing on IT in the form of more complex information in near real time – with a short development lifecycle – the enterprise data warehouse will likely be relegated to a supporting role and an aggregative function rather than the mainstay of reporting and analysis. 
    • Companies will store data in their warehouses for distribution to mobile analytics consumers and for use in temporary one-off applications that may or may not survive long-term.

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