Interested in building a Web Analytics Framework that really works? Here's a deck to guide you create the same. Originally presented at TiEcon Delhi 2012 by Aloek Bajpai (iXiGO) and Pradeep Chopra (Digital Vidya).

1. Building a Web Analytics Framework
that works!
Aloke
Bajpai
Pradeep
Chopra
CEO,
iXiGO
CEO,
Digital
Vidya

2. 3 Fundamental Questions
• Why? (Objectives)
• What? (Metrics)
• How? (Tools, Techniques, Dashboards…)

3. Lets Learn from Real Examples!

4. 1. E-commerce Tracking
Source
Visits
Trials
Transac9ons
SEO
33413
481
79
Direct
7041
193
82
Google
Adwords
1664
204
8
Referral
(SiteA)
732
28
6
Referral
(SiteB)
384
11
4

5. 2. UTM Tracking
Source
Visits
Sign-­‐Ups
(%)
Bounce
Rate
Source
A
150
7
65
Source
B
35
9
45
Source
C
46
12
48
Source
D
95
8
56
Source
E
140
5
67
digitalvidya.com?utm_source=tb;utm_medium=email&utm_campaign=jun-­‐12

6. 3. Revenue Modeling
Monthly
India
Asia
Total
Revenue
(Rs)
800,000
400,000
12,00,000
No
of
ParUcipants
100
50
150
No
of
Leads
2000
1000
3000
No
of
Visitors
20000
10000
30000
Cost
of
Adv
(Rs)
160,000
80,000
240,000
Daily
Calls
150
75
225
No
of
Callers
2.5
1.25
3.75
The
odds
of
contac9ng
a
lead
if
called
in
5
minutes
versus
30
minutes
drop
100
9mes.
The
odds
of
qualifying
a
lead
if
called
in
5
minutes
versus
30
minutes
drop
21
9mes.

7. 4. Top 10 Metrics for CEOs
1. Daily Visits
2. Daily Unique Visitors
3. Unique Pageviews for important pages
4. Multi-Channel Conversion Funnel
5. Bounce Rate
6. Direct Visits (including brand keyword visits)
7. SEO Visits + Keywords Base
8. Referring Sites (Deep-Dive)
9. No. of server errors (404s / 500s)
10. Qualitative Feedback/Sentiment Report

8. 5. Using Advanced Segments &
Custom Reports
• Advanced Segments
– Segment a section of visitors for deep-dives (e.g. only visitors
who viewed 3+ pages, only visitors who visited a particular
page, only visitors who landed on a particular page
– Useful for understanding behaviour for various source/
campaign segments
• Custom Reporting
– Very useful for deep analysis of paid search, SEO, Browsers,
Device type data
– Choose metrics (columns)
– Choose dimensions (drilldowns)
– Choose filters (for any metric)
• Most of the time you want to use both of above
• Please mind the sampling gap !

9. Examples

10. 6. Qualitative Analytics
• Measuring Happiness
• How do my users behave ? What do they spend
their time looking at ? Why do they do what
they do ?
• User Interaction / Behaviour (Clicktale/UserFly)
• Net Promoter Score
• Surveys (on-site / off-site)
• Social actions on the website (Likes/Shares)
• Social Media Mentions / Sentiments

11. NPS Example
NPS
=
46

12. Qualitative Analytics

13. 7. The HEART Framework
• Happiness
– User attitude, qualitative metrics, perceptions
• Engagement
– Behavioral signals, Depth of Interaction, Frequency, Clicks
• Adoption
– % Users who adopt new product / feature, “Get” the product
• Retention
– Returning users / Churn
• Task-Action
– Efficiency, Error Rates, Time Taken, % who complete a specific goal
– Specific metrics / signals critical for your product’s success

14. HEART Metrics in Action

15. Thank you!
pradeep@digitalvidya.com | abajpai@ixigo.com