Maths and stats for Web analytics and conversion optimization /
By: Sharma, Himanshu.
Publisher: [Seattle?] : [Amamzon Digital Services LLC], 2015Description: 428 p. : ill. ; 25 cm.ISBN: 9781364849184; 1364849186.Subject(s): Web usage mining -- Handbooks, manuals, etc | Internet users -- Web site devlopmentDDC classification: 006.312Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds |
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ATU Sligo Yeats Library Main Lending Collection | 006.312 SHA (Browse shelf(Opens below)) | 1 | Available | 0064166 |
About the author -- Part one : the maths for web analytics and conversion optimization -- Lesson 1 : an introduction to return on investment (ROI) -- Lesson 2 : ROI analysis in Google Analytics -- Lesson 3 : conversions and ROI in a multi-channel marketing world -- Lesson 4 : ROI calculations for SEO -- Lesson 5 : ROI calculations for phone call tracking to your client/boss -- Lesson 6 : powwrful methods to improve phone call conversion rate -- Lesson 7 : how to measure the ROI of content marketing -- Lesson 8 : calculating true conversion rate -- Lesson 9 : analysing and reporting conversion rate -- Lesson 10 : fundamental issues with te conversion rate metric --Lesson 11 : unsuspected correleations between conversion rate and critical business metrics -- Lesson 12 : avoid making marketing decisions based on conversion rate -- Lesson 13 : why conversion volume is a better metric than conversion rate -- Lesson 14 : why you should stop optimizing for conversion rate -- Lesson 15 : undertsanding averages -- Lesson 16 : important business metrics -- Lesson 17 : key performance indicators (KPI) -- Lesson 18 : selecting the best Excel charts for data analysis and reporting -- Part two : statistics for web analytics and conversion optimization -- Lesson 1 : introduction to statistics for web analytics and conversion potimization -- Lesson 2 : statistical inference -- Lesson 3 : population and sub-population -- Lesson 4 : understanding samples -- Lesson 5 : data sampling issues -- Lesson 6 : statistical significance -- Lesson 7 : significance level (or confidence level) -- Lesson 8 : effect and eggect size -- Lesson 9 : hypothesis -- Lesson 10 : false positive and flase negative -- Lesson 11 : statistical power (or power of the A/B test) -- Lesson 12 : minimum detectable effect -- Lesson 13 : outliers -- Lesson 14 : confidence interval -- Lesson 15 : conversion rate and improvement metrics in A/B testing -- Lesson 16 : confounding variables -- Lesson 17 : the multiple comparisons problem -- Lesson 18 : predictive analytics -- Lesson 19 : analysing data trends -- Lesson 20 : the 80/20 rule -- Lesson 21 : making the switch from traffic to conversions -- Lesson 22 : making good marketing decisions -- Lesson 23 : making the switch from data driven to data smart marketing.
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