Module5 other analytics


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Module5 other analytics

  1. 1. OTHER ANALYTICS Module 5
  2. 2. Agenda  Section 1: Testing and targeting  Section 2: Surveys  Section 3: Email  Section 4: Competitive Intelligence  Section 5: RSS feeds
  3. 3. Section 1 Testing and targeting
  4. 4. Introduction to testing  Testing is the technique used to know the actual intent of the customers who are visiting a web sites  Though a website has a major goal like, content production or e-commence or engagement. There are micro elements that are also part of this. Ex: Looking for careers link in Amazon web site.  So its important to know how each group of users are responding to different group of people.
  5. 5. Types of tests  There are many types of testing techniques that are used. Most popular are,  A/B testing or Split testing  MVT testing or Multivariate testing or bucking testing  Any testing technique requires to have the hypothesis ready and the have a clear definition of test elements  By testing, you cant derive new learning’s other than the elements that we have hypothesis for.
  6. 6. A/B testing – Details  AB testing compares the effectiveness of two versions of a web page, marketing email, creative images, landing pages – in order to discover which has better response rates, better conversion rates, etc.  AB testing will test two samples of the test – Control and test groups, to see which single variable is most effective in increasing a response rate or other desired outcome  To be effective, the test must reach an audience of sufficient size that there is a reasonable chance of detecting a meaningful difference between the
  7. 7. A/B testing – Tools  Example: A company want to test two banners of a creative reaching out to 5000 people.  First 2500 people got a offer with CTA “Buy now”  Next 2500 people got a offer with CTA “Learn more”  All other elements of the creative remain the same  Record CTR for each banner and that will be the winning banner  Tools that provide that reports are, Google Analytics content experiments, Optimizely, Visual website optimizer, Unbounce, Omniture
  8. 8. MVT testing – Details  Multivariate technique for testing hypotheses on complex multi-variable systems, especially used in testing market perceptions  Multivariate testing is usually employed in order to ascertain which content or creative variation produces the best improvement in the defined goals of a website, whether that be user registrations or successful completion of a checkout process  Testing can be carried out on a dynamically generated website by setting up the server to display the different variations of content in equal proportions to incoming visitors
  9. 9. MVT testing – Details  Dynamic creative optimization is the application of MVT testing. An automatic system will show the high performing creative to audience by testing the algorithm for targeted profiles  In a nutshell, multivariate testing can be seen as allowing website visitors to vote with their clicks for which content they prefer and will stand the most chance of their proceeding to a defined goal  This is one of the high growth area in digital marketing in the current digital marketing. All
  10. 10. Re-targeting – Details  Re-targeting is the technique of identifying the group of audience which fits the segment definition and giving them a relevant message for their next visit  This targeting can be applied on specific web- site or on an ad-network or with specific publisher website  Retargeting can happen based on many action. Ex: Click on the banner, drop out from the cart, visit to the site etc.
  11. 11. Re-targeting – Tools  Retargeting can be done four segment bases: demographic, geographic, behavioral, psychogr aphic  While using this technique, you can use the same message or different messages fine tuned  Currently all ad serving platforms are supporting re-targeting for media  Web analytics tools like – Omniture and Google Analytics has also that capacity
  12. 12. Section 2 Surveys
  13. 13. Surveys – Introduction  Analytics tools provide the data what has happened in the past. It does not really help us understand why people are doing what they are doing.  Data by itself does not give the “purchase intent”  With customer actions, we try to figure our this indirectly  The direct way of figuring this out is – Surveys  Surveys can be done to address a specific need or can be conducted as a general feedback mechanism , i.e at site level or at a session/page
  14. 14. Surveys – Details  It helps to understand – what are the macro and micro conversions that are happened on the site  Surveys can happened at any point of the visit of the user. However its been identified to have the survey happened at the end of the visit or entry of the visit.  With technology you can have surveys or feedback taken even on the display banners  You can conduct these to all users or only specific group of people selected based on segmentation
  15. 15. Surveys – Details  With a simple survey, you can get the data related to  Why a user has visited the site  Were they able to complete the task  If not, why not?  Guidelines for conducting surveys:  Don’t make surveys an obstruction to the user experience  Don’t collect personal level information of users  Always provide an option of opting out of the surveys  Don’t make surveys long. Limit them to a max. of 10 questions  Use industry benchmarks to design and evaluate your
  16. 16. Surveys – Details  Companies who can help you do the surveys –  Iprospects – Paid  Surveymonkey – Free  Forsee results – Paid  The data can be in the form of, desirability, preference, Discovery, was it helpful etc. depending on what vendor you are using  Surveys can collect the both positive and negative feedbacks
  17. 17. Section 3 Email data
  18. 18. Email marketing – Introduction  Email marketing also know as permission marketing is one of the old forms of marketing.  There are two types of email marketing.  Explicit permission marketing  Implicit permission marketing  Both are powerful marketing forms, but there is a good probability people will consider them spam if the messages are not relevant over the time  Using the tracking parameters, we can collect different metrics, however these are very different from normal metrics that we collect via websites
  19. 19. Email marketing – Metrics  The metrics that are used for email marketing success are,  No. of emails sent  No of successful emails sent  No of emails opened  Open rate  No of emails read  CTR from emails  No of responses  Response rate
  20. 20. Email marketing – Details  Email marketing is very effective if maintained as an integral communication channel of campaigns  Its little costly compared to the remaining forms of marketing and need to be maintained for valid customers  Its powerful channel to increase the loyal users and keep them for up-selling and cross- selling  This is also very good medium to conduct surveys
  21. 21. Section 4 Competitive Intelligence
  22. 22. Competitive intelligence – Introduction  Competitive Intelligence is the process of defining, gathering, analyzing & distributing intelligence about products, customers, competitors and any aspect of the environment needed to support executives and managers in making strategic decisions for an organization  Key points of CI are,  Benchmark the effectiveness of your existing customer acquisition strategies  Determine what is driving competitors’ success  Use historical consumer data to forecast future trends
  23. 23. Competitive intelligence – Details  The data can we collected from,  Toolbar data: Toolbars are add-ons on web browsers, which are used to collect limited information about the browsing behaviour of the customers who use them, including the pages visited, the search terms used, perhaps even time spent on each page, and so forth. Typically, data collected is anonymous and not personally identifiable information. Ex: Alexa  Panel data: A company may recruit participants to be in a panel and each panel member installs a piece of monitoring software. The software collects all the panel’s browsing behaviour and reports it to the company running the panel. Additionally the person is also required to self report demographic, salary, household members, hobbies, education level and other such detailed information. Ex: Comscore, Neilsen
  24. 24. Competitive intelligence – Details  ISP (Network) data: Network provides collect data from server logfiles. The data collected by the ISP consists of elements that get passed around in URLs, such as sites, page names, keywords searched etc.. The ISP servers can also capture information such as browser types and operating systems. Ex: Hitwise  Search Engine Data: Search engines, such as Bing, Google, Yahoo! and Baidu, are logged by those search engines, along with basic connectivity information such as IP address and browser version.
  25. 25. Competitive intelligence – Details  Benchmarks from Web Analytics vendors: Web analytics vendors have lots of customers, which means they have lots of data. Many vendors now aggregate this real customer data and present it in the form of benchmarks that you can use to index your own performance. Ex: Google Analytics, Omniture, Coremetrics  Self-reported data: Some websites can report their data intentionally to panel data collectors to attract more advertising
  26. 26. Competitive intelligence – Details  Hybrid data: Any mix of above collected data can be used for the analysis. Google Trends for search is one of the freely available tools which helps to provide the search query analysis based on keywords  External voice of data: You can upload data that is collected offline to support the online CI  Any of these methods has its own advantages, short-comings and privacy related issues. So its advisable to use a collection of data sources to have the best solution possible
  27. 27. Section 5 RSS feeds
  28. 28. RSS – Introduction  Rich Site Summary is an aggregator that used to publish frequently updated works such as blog entries, news headlines, audio, and video  RSS Tracking is a methodology for tracking RSS feeds  This tracking is tricky when measuring the user usage  We discuss these methods in the following slides with its advantages and limitations
  29. 29. RSS – Tracking Method  Method 1:  Transparent 1×1 pixel images - These images can be embedded within the content of the RSS feed by linking to the image which should be held on the web server. The number of requests made can be measured by using the web server log files. This will give a rough estimate as to how many times the RSS feed has been viewed.  The problem with this method is that not all RSS feed aggregators will display images and parse HTML
  30. 30. RSS – Tracking Method  Method 2  Third-party services - There are services available on the Internet that will syndicate RSS feed and then track all requests made to their syndication of RSS feed. These services come in both free and paid forms.  The problem with this method is that all analytical data about the feeds are controlled by the service provider and so not easily accessible or transferable.
  31. 31. RSS – Tracking Method  Method 3  Unique URL per feed - This method requires heavy web server programming to auto generate a different RSS feed URL for each visitor to the website. The visitor's RSS feed activity can then be tracked accurately using standard web analytics applications.  The problem with this method is that if the feed is syndicated by a search engine for instance then this will defeat the purpose of the unique URLs as many people could potentially view the RSS feed via a single URL
  32. 32. RSS – Tracking Methods  Method 4  Estimating number of subscribers from the log files. Some aggregators (For ex: Bloglines and Google Reader) include a number of unique users on whose behalf the feed is being downloaded in the HTTP request. Other readers, such as web browsers, can be counted by noting the number of unique IP addresses that retrieve the file in a given period.  This provides an estimate of actual readership, although it is probably higher than the real number because people may sign up for accounts with multiple aggregators and never delete their subscriptions and because they may read the same feeds at different computers, or the same computer may have a different IP address at different times.
  33. 33. For Q&A: Contact: Thank you