NCDM 2010 - Target Customers Effectively Through Advanced Analytics - Netezza - Intuit

Ta rg e t Cu s to m e rs Effe c tive ly
Th ro u g h Ad va n c e d An a lytic s

Brad Terrell
VP & General Manager,
Digital Media

Arup Ray
Director, Data Warehousing &
Business Intelligence
Development and Architecture

“Innovation distinguishes between
a leader and a follower”

- Steve Jobs

After…

1 00x THE
PERFORMANCE

½ THE COST

UNMATCHED
SIMPLICITY

Right message…

Right person…

Right time…

Netezza wins 2010 DMA Innovation Award
for Market Segmentation and Optimization technology

“25% conversion rate increase
with 33% lower CPA”

“300% to 2,000% conversion
rate improvements”

Consumer attention is fragmenting

Digital Exhaust
benefits marketers

Marketing and Data Analysis
are Intertwined

The Segmentation Problem

High
Age: 18-24
Income: High Age: 25-35
Recency: Low Income: High

Income
Recency: High

Recency of visits to
High
YourWebSite.com
Age: 50-65
Income: Low
Recency: Low

Age: 36-49
Income: Low
High Recency: High

The Matching Problem
Target
Segment

Awareness

Consideration

Intent

The Bidding Problem

Price/Volume Forecast Market X: Price/Volume Curve

Curves Show the Optimal
1,200,000

IMPRESSIONS PER DAY
1,000,000

Bid in Each Market: 800,000

600,000

max((R − B) ⋅ N(B))
400,000

200,000

0
0.00 1.00 2.00 3.00 4.00 5.00
R = revenue derived from showing ad CPM Bid

B = ad’s bid
N(B) = impression volume for bid B as Market X: Profit Curve
predicted by P/V Curve 3,500
3,000
2,500
PROFIT
2,000
1,500
1,000
500
0
0.00 1.00 2.00 3.00 4.00 5.00
CPM Bid

Customer Insight Through Deeper Analysis
(The Fastest Climbers Win)
Optimization

Predictive
Analytics
BI Reporting and
Ad-Hoc Analysis

• What is the
best choice?

• What will happen?
• What will the impact be?

• What happened?
• When and where?
• How much?

Arup Ray
Director, Data Warehousing &
Business Intelligence
Development and Architecture

Intuit Company Information
Who We Are …
A leading provider of business and
financial management solutions

Company Founded: 1983
Date Public: 1993
Stock Symbol: NASDAQ: INTU
GAAP Net Revenue (Fiscal 2010): $3.2 billion
Employees: ~ 8000
Locations: 60 locations in 40 cities around the globe

20

Multiple Channels for Online Acquisition
• Ad Networks
Display • Portals
• Content Sites

Paid Search • Brand
• Generic

Organic Search • Brand
• Generic

Affiliates

Email
22

Life stage of customer acquisition

Pre- Post-
Awareness
Conversion Conversion
First impression

Authentication

Conversion
23

What is working?

• Which channels are yielding results? Which sub-channels?
• Are channels cannibalizing each other?
• What works at what stage of the acquisition funnel?

24

High Level Goals of Intuit Marketers
• Optimize spend across
channels
• Coordinate spend across
channels
• Optimize messaging in
ads
• Use early converter
behavior for mid-course
adjustments

Where is the data to help me?
• Doubleclick tracks all converters and non-converters across
web sites as well as on key pages of our web site

• Omniture tracks customer behavior on our site

• These data sets are warehoused in our Customer Experience
Data Warehouse running on Netezza

• Massive volumes of data – the impression table alone has
more than 40 Billion rows!

26

What does the data tell me?
• A lot …

– About the effectiveness of the acquisition channel as well as specific
campaigns

– About channel interferences

– About product issues

– About customer behavior with regards to acquisition campaigns

27

Example of Display Ads from Ad Networks

CHANNEL EFFECTIVENESS

28

29
Reach by Exposure Conversion
Frequency Rate

10.0%
15.0%
20.0%
25.0%

0.0%
5.0%

0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
3.50%
4.00%
4.50%
1 1
10 10
19 19
28 28
37 37
46 46
55 55
64 64
73 73
82 82
91 91
100 100
109 109
118 118
127 127
136 136
145 145
154 154
163 163
172 172
181 181
190 190
199 199
208 208
217 217
Ad Network – A

226 226
Display
Display

235 235
244 244
253 253
Impressions
Impressions

262 262
271 271
280 280
289 289
298 298

Average exposures per cookie = 28.9
Average conversion rate = 3.1%
Average impressions per conversion = XX.X

Ad Network - B
50.0%
Conversion

45.0%

Average impressions per conversion = X.X
40.0%
Rate

35.0%
30.0%

25.0%
20.0%

15.0%
10.0% Display Impressions
5.0%
0.0%
1
10
19
28
37
46
55
64
73
82
91
100
109
118
127
136
145
154
163
172
181
190
199
208
217
226
235
244
253
262
271
280
289
298
45.00%
Frequency

40.00%
Exposure
Reach by

35.00%
30.00%
25.00%
20.00%
15.00%
10.00% Display Impressions
5.00%
0.00%
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97

30

Reach by Conversion

31
Exposure Rate
Frequency

10.0%
20.0%
30.0%
40.0%
50.0%
60.0%

0.0%

10.00%
15.00%
20.00%
25.00%
30.00%
35.00%

0.00%
5.00%
1 1
10 10
19 19
28 28
37 37
46 46
55 55
64 64
73 73
82 82
91 91
100 100
109 109
118 118
127 127
136 136
145 145
154 154
163 163
172 172
181 181
190 190
199 199
208 208
217 217
Ad Network - C

226 226
235 235
244 244
253 253
262 262
Display Impressions

Display Impressions

271 271
280 280
289 289

Average impressions per conversion = XX.XX

Portal Home Pages – Distinct Visitors
0131 MSN HP Money Module Txtlink
0131 MSN HP
0201 MSN HP
0125 MSN HP
0215 MSN HP
0214 MSN HP
0131 Yahoo HP RM
0207 Yahoo Marketplace - Logo + text
0124 MSN HP
0201 AOL RM - User Initiated
0131 AOL HP RM - Host
0131 AOL HP Textlink
0125 AOL HP
0221 AOL HP - Textlink
0124 AOL HP
0221 AOL HP 300x250
0201 AOL HP NB
0131 AOL HP NB
AOL HP 01/10

0 1000000 2000000 3000000 4000000 5000000 6000000 7000000 8000000
32

Portal Home Pages - Impressions
0131 MSN HP
0201 MSN HP
0125 MSN HP
0215 MSN HP
0214 MSN HP
0131 Yahoo HP RM
0124 MSN HP
0125 AOL HP
0124 AOL HP
0221 AOL HP 300x250
0201 AOL HP NB
0131 AOL HP NB
AOL HP 01/10

0 10000000 20000000 30000000 40000000 50000000

33

Portal Home Pages – Distinct Converters
0131 MSN HP
0201 MSN HP
0125 MSN HP
0215 MSN HP
0214 MSN HP
0131 Yahoo HP RM
0124 MSN HP
0125 AOL HP
0124 AOL HP
0221 AOL HP 300x250
0201 AOL HP NB
0131 AOL HP NB
AOL HP 01/10

0 50000 100000 150000 200000 250000 300000 350000

34

Portal Home Pages – Distinct converters
per Impression
0131 MSN HP
0201 MSN HP
0125 MSN HP
0215 MSN HP
0214 MSN HP
0131 Yahoo HP RM
0124 MSN HP
0125 AOL HP
0124 AOL HP
0221 AOL HP 300x250
0201 AOL HP NB
0131 AOL HP NB
AOL HP 01/10

0.00% 0.50% 1.00% 1.50% 2.00% 2.50% 3.00%
35

Portal Home Page – Impressions per
distinct converter
0131 MSN HP
0201 MSN HP
0125 MSN HP
0215 MSN HP
0214 MSN HP
0131 Yahoo HP RM
0124 MSN HP
0201 AOL HP RM - Host Good value?
0125 AOL HP
0124 AOL HP
0221 AOL HP 300x250
0201 AOL HP NB
0131 AOL HP NB
AOL HP 01/10

0 20 40 60 80 100 120 140 160 180 200

36

Affiliate clicks versus paid search

CHANNEL INTERFERENCE

37

Paid Search Clicks and Affiliate Clicks
Paid Search does not currently interact significantly with Affiliate
3%

No Affiliate click
before
At least one
Affiliate click before
97%

15%

No Paid Search click
before
85% At least one Paid
Search click before

38

Paid Search Clicks and Affiliate Clicks
Paid Search does not currently interact significantly with Affiliate

Number Paid Search click alone

of Affiliate click alone
cookies
Paid Search click followed by Affiliate click
with…
Affiliate click followed by Paid Search click

0 1000000 2000000 3000000 4000000 5000000 6000000

Paid Search click alone
Conversion
rate of Affiliate click alone

cookies Paid Search click followed by Affiliate click
with…
Affiliate click followed by Paid Search click

0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20%

Why do people not convert?
Which are the
problem pages?
Create alternate flows
and do A/B testing

Pre- Post-
Awareness
Conversion Conversion
Authentication

Conversion
impression
First

41

Converted on Display Click…
People who convert on display click tend to stick with display clicks…

Awareness Stage Navigation Stage

Email Click
Email Click
Email Impression 1.46 Email Impression 1.78
Affiliate Click 1.92 2.40
1.41 Affiliate Click
1.69
Paid Search Click 1.43
Paid Search Click 1.96
1.39 1.92
Display Click 52.0 Display Click 56.5
Display Impression Display Impression

0% 50% 100% 0% 20% 40% 60% 80% 100%

Average number of exposures,
Percentage of converters
for converters who had at least one exposure
who had at least one exposure

43

Converted on Paid Search Click…
People who convert on paid search click tend to stick with paid search clicks…


Email Click Email Click

1.96 2.15
Affiliate Click Affiliate Click
1.43 1.60
Paid Search Click 1.31 Paid Search Click 1.87
1.34 1.67
Display Click 26.8 Display Click 34.5

0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100%

44

Converted on Affiliate Click…
People who convert on affiliate click tend to stick with affiliate clicks…


Email Click Email Clicks
2.04 2.66
Affiliate Click Affiliate Click
1.34 1.83
1.32 1.63
Display Click Display Click 40.5
28.2

0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100%

45

Converted on Email Click…
People who convert on email click tend to stick with email clicks…


Email Click Email Click
Email Impression Email Impression 1.77
1.32
Affiliate Click 1.98 Affiliate Click 2.66
1.41 1.83
1.28 1.63
Display Click Display Click 40.5
23.2

0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100%

46

Messages that are funnel aware
• Based on where the user is in the funnel we can target them
with relevant messages

• This could be a better offer if they are in awareness stage or a
reinforcement of value proposition if they are in navigation stage

• Doubleclick provides reach beyond the confines of the Intuit
websites

• The impressions in post-conversion stage are used to cross-sell
other products and hence are not wasted

48

Keys to success
• Ability to load large data volumes daily

• Complex queries that process billions of rows in minutes and
not hours

• Ability to leverage intelligent messaging mechanisms within
Intuit website and Doubleclick for intelligent messages across
the web

Data Insight Action
49

NCDM 2010 - Target Customers Effectively Through Advanced Analytics - Netezza - Intuit

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