Analytics: measuring web site success MBA 563 Week 4
Overview: Methods of measuring marketing success You can t manage what you can t measure (Bob Napier, ex CIO, Hewlett Packard) 1. Data mining and predictive analytics 2. Focus on web analytics
Results of Accenture's 2014 CMO Insights Survey In what areas do you believe the marketing function will change the most? Accenture's 2014 CMO Insights Survey
DATA MINING AND PREDICTIVE ANALYTICS
Data mining (aka Big Data ) Data mining = extraction of hidden predictive information in large databases through statistical analysis. Real-space primary data collection occurs at offline points of purchase with: Smart card and credit card readers, interactive point of sale machines (ipos), and bar code scanners Online data both actively and passively provided by internet users Offline data, when combined with online data, paint a complete picture of consumer behavior for individual retail firms. Data collected from all customer touch points are available for analysis and distribution to marketing decision makers. How it works: Analytics (IBM SocialMedia) video
Data trails.. Write down all the ways in which you have left data behind you this week. Both actively and passively. Where, how, what kind of data? "Information is flowing like mighty rivers from a trillion connected and intelligent things... IBM SocialMedia
Data Analysis for Marketing Marketers are looking for hidden patterns in the data predictive analytics Analysis for marketing decision making: Customer profiling - How 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)
Marketing data and consumer privacy There is a big tension between what marketers want to know about people, and how comfortable people are in providing that data 86% of internet users have taken steps online to remove or mask their digital footprint Anonymity, Privacy, and Security Online Pew Internet (September 2013) It is very important to respect this concern and to give people confidence in the integrity and ethics of your business
Privacy: legal requirements Increasingly strict legal framework around privacy rights in most jurisdictions Canadian federal legislation (PIPEDA (Personal Information Protection and Electronic Documents Act) requires a business that collects personal information to : Identify purpose for which info is being collected Knowledge and consent of individual is required Use only for the purpose for which it was collected Keep it secure Make public the policies and practices about how private information is deal with (usually done via Terms of Service / Privacy Policy
FOCUS ON WEBSITE ANALYTICS
Website Analytics Onsite analytics Web site traffic attributes and trends Referrals from affiliates Clickstreams and clickpaths Website usability testing Purpose to optimize websites in order to meet business objectives via data-driven decision making Source: emarketing excellence. 2012. Smith &Chaffey
Technology-Enabled Approaches to market research The Web provides marketers with huge amounts of information about users This data is collected automatically It is unmediated (and therefore unbiased) Where does this data come from? Server-side data collection Log file analysis - historical data Real-time profiling (tracking user Clickstream analysis) Client-side data collection (page tagging and cookies) 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
WEB ANALYTICS SOFTWARE
Web analytics software The volume of data generated by even a small website is so large that human analysis would be impossible Format and sophistication of reports depends on software used (and the price paid) Many software packages / hosted solutions available one wellknown example of each Google Analytics (browser-based solution only, closely tied to its search marketing products) WebTrends - offers both server and browser-based (hosted) solutions And integrates metrics from other sources to help manage and measure integrated online campaigns Several examples and case studies are available from Webtrends
Web analytics approaches Two main approaches to obtaining website analytics data: 1. Server-based: analysis of automatically generated first-party server log files (ie. the server on which the site resides) 2. 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.
Server versus browser based analytics solutions Advantages of server-based approach Data is always available from the server no alterations to web pages needed Does not rely on JavaScript being enabled by the user Includes information about visits from search engine spiders and other automated robots Lets the firm know about potential problems with the site eg. failed requests Can be analyzed in real time Advantages of browser-based approach Solves the page caching problem (page is counted each time it is reloaded) Available to firms without their own web server attractive to small businesses Pay-as-you go pricing Becoming the standard approach for analytics
What is automatically recorded includes: Sessions and interactions Number of page views Total unique visitors - using cookies (video explanation from Google) 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)
Remember this about web You cannot identify individual people. The log file records the computing device IP address and/or the cookie, not the user. Unless the user has logged in (for example, to Chrome) As the use of multiple devices grows, there are significant audience overlaps which might lead to double counting This is why benchmarking is so important trends rather than absolute numbers analytics
USING WEB ANALYTICS EFFECTIVELY
First decision before we start analytics? What are our business goals? What are our key performance indicators that will tell us whether or not we have reached those goals?
Second decision: 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. 2012. 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. 2012. 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. 2012. 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. 2012. 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. 2012. Smith &Chaffey
So.how do you use web analytics effectively? 1. Identify leading indicators of business success via the web channel (ie. set goals) 2. Identify the key performance indicators (KPI) with which to measure them 3. Establish benchmarks to track changes over time 4. Configure software and use settings consistently Source: emarketing excellence. 2012. Smith &Chaffey
REAL-TIME ANALYTICS
Real-time profiling / behavioural targeting 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 : sense and respond Very expensive to implement and do well
Behavioural targeting Past actions determine the advertising or content you will see in the future Onsite behaviour Web analytics are used to identify customer profiles The behaviour on the site is then tracked and appropriate content served Network behaviour Used extensively by advertising networks Entails tracking across third party sites Many privacy concerns have been raised
GOOGLE ANALYTICS SOFTWARE IN PRACTICE
Focus on Google Analytics Google Analytics Tutorial for Beginners 2014 (video) YouTube Channel for Google Analytics