13da2fb3-9b7a-441d-bcc7-89154094c6b8.pptx

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1. Web Analytics

2. Introduction Web analytics is the process of tracking, collecting, analysis, and reporting of web data. It provides a number of key metrics which when analyzed can provide actionable insights. It is performed to optimize marketing activities over the internet. Some tools for web analytics Google analytics, Yahoo! Web analytics and web trends.

3. Key Metrics 1. Behavior analysis – visit/sessions – page requests with a gap of no more than 30mins between each one. i. click vs visit – click is when one clicks on ad or link, upon clicking the user visits the webpage. Ii. Unique visitors – unique visitors are the number of different users requesting webpages. Time on site – it indicates engagement of the visitor, more time spent means greater stickiness of the site. Page views – it is number of pages viewed or requested by a user. More pages views mean more engagement. Bounce rate – it is the percentage of single-page visits and user leaves from the landing page without interacting with the page. Exit pages – to know from which pages users are exiting the most. Pages from where visitors are dropping off in the process of buying a product are called exit pages. Traffic sources – there are three types of traffic source, i. direct traffic – user typing direct URL. ii. Search traffic – based on search query. iii. Referral visitors – as website was mentioned on another blog or website.

4. Key Metrics 2. Outcome analysis – Conversion rate – it is the percentage of users who perform an action that is desired by the website owner. Multi-channel funnel – enables understanding of the different channels users interact with on the path to conversion. Visitor frequency and recency – how often visitor visits the website is visitor frequency, while visitor recency is how long has it been since a visitor last visited a website. New vs return visitor conversion – on must keep an eye on how many new visitors they have in comparison to returning visitors. If returning visitors are less means users are less loyal. Value per visit – there is certain value that one must assign to every single visit to website these are categorized into two conversions micro and macro. Percent of visitors who view product pages

5. Key Metrics 3. Experience analysis Research data – through site survey, usability testing, site visits. Website experimentation and testing – i. A/B testing is sometimes also called split testing where one compares two versions of their webpage to see which performs better. ii. What to test – important pages like home page, calls for action, value proposition, creative, price and promotions.

6. 1. Last Interaction/Last Click Attribution model – entire credit for conversion is given to channel last clicked. 2. First Interaction/First Click Attribution Model – first interaction or click is given credit. 3. Linear Attribution Model – equal credit to all the sources. 4. Time Decay Attribution Model – the media touch point that is closest to the conversion will get most of the credit. 5. Position Based Attribution Model – last position gets the most credit. Multi-channel attribution