Analytics: measuring web site success. MBA 563 Week 3

Transcription

1 Analytics: measuring web site success MBA 563 Week 3

2 You can t manage what you can t measure (Bob Napier, ex CIO, Hewlett Packard)

3 FOCUS ON WEBSITE ANALYTICS

4 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

5 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

6 WEB ANALYTICS SOFTWARE

7 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

8 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.

9 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)

10 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

11 USING WEB ANALYTICS EFFECTIVELY

12 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?

13 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 Smith &Chaffey

14 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

15 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

16 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

17 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

18 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 Smith &Chaffey

19 GOOGLE ANALYTICS SOFTWARE IN PRACTICE

20 Focus on Google Analytics Google Analytics Tutorial for Beginners 2014 (video) YouTube Channel for Google Analytics