The document provides tips for generating insightful insights from web analytics data. It recommends filtering and grouping data to clean it up and simplify granular information. Extreme segmentation of visitors by type, intention, source, and product engagement is suggested. If-then analysis can define and improve the customer funnel by identifying opportunities to send more traffic, optimize pages, lower risks, or improve incentives. Deriving business value, such as cost savings, is also recommended. Integrating web analytics data with other data sources like CRM can provide a fuller picture of customer interactions across channels. Building a data-driven culture is key to effectively analyzing web data.

1. Web Analytics Deep Dive
#SESSF
Garry Przyklenk,
Manager, Analytics Implementation
(@gprzyklenk)

2. Keys to “insightful” insights
Tried and true approaches:
Filter, group, then segment
If… then… analysis
Derive business value
Get closer to the customer
Integrate data sources
In general,
build a data-driven culture!
@gprzyklenk

3. Filtering and grouping
Any web analytics platform won’t be perfect, so a certain
level of filtering and grouping is required:
Filtering can be used to:
 Clean up data integrity issues
 Move beyond the “top 10” or “top50” entries
 Example:
TD has 60,000 employees and filters internal IP’s from
logging information in Omniture SiteCatalyst.
Groupings can be used to:
 Simplify extremely granular data
 Build complex segments effectively
 Example:
Referring URL values can be grouped to go beyond the
standard types, such as “internal referrer” and “external
affiliate”.
@gprzyklenk

4. Extreme segmentation!
 Visitor type  Visitor intention
 Prospect/New  Research
 Customer  Purchase/Broker
 Affiliate  Renew
 Employee  Transact
 Source  Product engagement
 PPC  Core accounts
 SEO  Credit cards
 Social Media  Lending (credit line/mortgage)
 External Display Ad  Investing
 Internal Display Ad  Insurance
 Affiliate  Business banking
@gprzyklenk

5. Isn’t that really hard?
YES, YES IT IS…
@gprzyklenk

6. Pivot tables are awesome
Source Visitor Type Intention Product Visits Conversions Transactions
PPC Prospect Research Credit Card 8 1 0
Savings Account
Internal Customer Transact Mortgage 5 1 4
Display Ad
Social Media Affiliate Broker Mutual Funds 35 0 8
Direct Employee Research None 55 0 3
Do we actually do this? Yes, yes we do.
Online sales reporting (Daily/Weekly/Monthly)
Public website reporting (Monthly)
Secure website reporting (Monthly)
@gprzyklenk

7. If…then… analysis
No one really cares about the metrics, but everyone cares about their
bonus. That equates to defining and improving the funnel.
Send more traffic?
Optimize landing
pages?
Lower the risk
profile?
Improve incentives?
IMPACT
@gprzyklenk

8. Derive business value
Paperless Statements
Postage $0.45
Opportunity:
Customers 1,000,000
Saves the bank at least the cost of a Avg. # of Products 2
stamp per customer per product per month per Customer
Reducing Yearly Savings $11 Million
calls to the contact center due to
lost paper statements
Customer benefit:
Improved customer experience with
scanned checks in near-real-time
Freedom to bank anywhere, anytime on
any device
@gprzyklenk

9. Derive business value
Where do you think the greatest opportunity exists?
@gprzyklenk

10. Get closer to the customer
Problem: web analytics can be complex to the business.
Solution: get closer to the customer.
@gprzyklenk

11. Integrate data sources
@gprzyklenk

12. Integrate data sources
Source Visitor Type Intention Product Visits Conversions Transactions
PPC Prospect Research Credit Card 8 1 0
Savings Account
Internal Customer Transact Mortgage 5 1 4
Display Ad
Social Media Affiliate Broker Mutual Funds 35 0 8
Direct Employee Research None 55 0 3
Channel Source Visitor Type Intention Product Visits Cx Tx LTV
Branch PPC Prospect Research Credit Card 8 1 0 $590,000
Savings
Account
Phone Internal Customer Transact Mortgage 5 1 4 $250,000
Display Ad
Online Social Media Affiliate Broker Mutual Funds 35 0 8 $675,000
ATM Direct Employee Research None 55 0 3 $1,200,000
@gprzyklenk

13. Thank You!
Questions?