Web Analytics MGMT 230 WEEK 10

After today’s class you will be able to: Explain the types of information routinely gathered by web servers Understand some of the uses for web analytics Understand how analytics can be used to ensure the effectiveness of your website and track how well you are meeting your goals

Web Analytics - definition Techniques used to assess and improve the contribution of online marketing to a business or organization Onsite analytics – Web site traffic attributes and trends – Referrals from affiliates – Clickstreams and clickpaths – Website usability testing – Offsite analytics – Measurement of potential audience, social media activity, “buzz” Purpose – to optimize websites and web marketing initiatives in order to meet business objectives

Technology-Enabled Approaches The Web provides marketers with huge amounts of information about users  This data is collected automatically  It is unmediated (and therefore unbiased) Server-side data collection – Log file analysis - historical data – Real-time profiling (tracking user Clickstream analysis) Client-side data collection (page tagging and cookies) Social media analysis Data Mining These techniques did not exist prior to the Internet.  They allow marketers to make quick and responsive changes in Web pages, promotions, and pricing.  The main challenge is analysis and interpretation (plus increasing consumer privacy concerns)

We will focus on website data analytics Web site activity can be analyzed to produce quantitative information about the activities and behaviour of web site users. Analysis of this freely available data should be a routine form of information for marketers and business managers – for all sizes of organizations So much data is available that software is needed to assist in analysis Analysis can be performed at varying levels of sophistication (and cost)

Two main approaches to obtaining website analytics data Server-based: All web servers automatically log (record) each http request That request contains information about the requesting client computer and software – This allows you to identify a user at the “visitor” level Browser-based page tagging: uses JavaScript code embedded on each html page to let a third-party server know each time the page is loaded into a web browser – very similar data is collected

Web analytics software tools available to measure web site activity Analytics software available from a variety of vendors – a couple of examples – WebTrends – enterprise software application used to analyze server log files (and other data about users) WebTrends Now also tracks via browser tagging and offers a desktop and a hosted solution – Google Analytics – requires tracking code to be inserted into web pages – then analyzed remotely (a hosted solution) Google Analytics

What is automatically recorded includes: Sessions and interactions Number of page views Total unique visitors (using “cookies”) The referring web site Number of repeat visits Time spent on a page Visit duration Route through the site (click path) Search terms used (now no longer fully available from Google) Most/least popular pages Understanding Google Analytics: key metrics and dimensions defined (video 6 minutes) Understanding Google Analytics: key metrics and dimensions defined

Some commonly used indicators using this data Bounce rate Time on page Unique visitors Conversion rate Number of pages viewed Advertising success (via referrers)

Steps to effective use of web analytics 1.Identify website goals 2.Identify the key performance metrics with which to measure business success – how will you know how well you are doing? 3.Establish benchmarks to track changes over time 4.Configure software and use settings consistently Recognize its limitations: – Cannot identify individual people. The log file records the computer IP address and/or the “cookie”, not the user.

First decision before we start analytics? What are our business goals? What are our key performance indicators? In other words, what metrics can we use to measure success?

The big picture – types of online business objectives and how they are measured Business ObjectiveMeasurable outcome eCommerceSell products Lead generationContact information for sales prospects Content publishingAds shown to visitors Online info / supportHelp customers find information BrandingDrive awareness, engagement, and loyalty The importance of digital analytics (Google)

What should we measure via the web channel? Channel promotion – where did visitors come from? Channel buyer behaviour – what do they do when they get to the site? Channel satisfaction – how happy are the visitors? Channel outcomes – conversions Channel profitability – online sales contribution – the primary aim of eCommerce Source: eMarketing eXcellence Smith &Chaffey

Web channel promotion – where did web site users COME FROM? Which site “referred” them – Search engine – Affiliate site – Partner – Advertisement – Contribution to sales or other desired outcome Measures - allows the evaluation of the referrer – What percentage of all referrals came from this source? – Calculation of the cost of acquisition of each visitor Source: eMarketing eXcellence Smith &Chaffey

Web channel buyer behaviour - what do people DO when they get to the site? We can monitor – Which content is accessed by users – When they visit – How long they stay – Whether interaction with content leads to sales or other desired outcome Measures – eg. – Bounce rate: proportion of visitors to a page who leave immediately – Stickiness: how long a visitor stays on the site, and how many repeat visits they make – Conversion rate: % of visitors who perform a desired action Source: eMarketing eXcellence Smith &Chaffey

Web channel satisfaction - how HAPPY are the visitors? Customer satisfaction is vital, but hard to measure directly with technology Stickiness is one indirect indicator of satisfaction Conversions are another Bounce rate is very important Can measure indirectly by testing and via survey tools – Ease of use – Site availability (down time) – Performance Source: eMarketing eXcellence Smith &Chaffey

Web channel outcomes Measure sales, leads, and conversions from the web channel – Conversion rate Percentage of site visitors who perform a particular action such as registering for a newsletter, subscribing to an RSS feed, or making a purchase – Attrition rate Percentage of site visitors who are lost at each stage of a multi-page transaction (the “funnel”) – Related concept is “shopping cart abandonment” Source: eMarketing eXcellence Smith &Chaffey

BEYOND WEB ANALYTICS - BIGGER DATA…

Real-time profiling: building relationships with customers Much more sophisticated that simple “historical” log file analysis Uses real-time Clickstream Monitoring - page by page tracking of people as they move through a website Uses server log files, plus additional data from cookies, plus sometimes information supplied by user Real time profiling entails monitoring the moves of a visitor on a website starting immediately after he/she entered it. – Can be served personalized content in real-time according to the “profile” - called “sense and respond” using a “recommendation engine” – Amazon.com has invested heavily in this technology Amazon.com Called “collaborative filtering” when combined with data from other users to create profiles

“Big” Data Analysis for Marketing Marketers are looking for hidden patterns in the data – predictive analytics – How it works: Analytics (IBM SocialMedia) videoHow it works: Analytics Analysis for marketing decision making: – Customer profiling - How Target Figured Out A Teen Girl Was Pregnant Before Her Father DidHow Target Figured Out A Teen Girl Was Pregnant Before Her Father Did – Behavioural targeting of advertisements – Predicting behaviour – RFM analysis (recency, frequency, monetary value of customer) Source: eMarketing eXcellence Smith &Chaffey

In-class exercise Setting specific goals and using web analytics to measure success