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Machine Learning Micro Segmentation at the Speed of Your Business...
Programs
Dropdown Example
Action
CAMPAIGNS
DATA and MODELS
DATASETS
SCHEMAS
MODELS
Dataset:
Upload a Dataset.
Action
PREVIEW
PROFILES
Save
Revert
Primary Key
Outcome
Treatment
Weight
Model Only
Stats Only
Ignore
Clear
integer
string
boolean
float
ATTRIBUTES
Education Level
Dataset:
ATTRIBUTES
Save
Revert
Primary Key
Outcome
Treatment
Weight
Model Only
Stats Only
Ignore
Clear
integer
string
boolean
float
Model:
Model 1
Action
Scored File:
Scored File1
Action
SEGMENTS
ATTRIBUTE IMPORTANCE
GAIN CHART
LIFT CHART
Segment 1 Profile
Education Level
PLANNING
FACEBOOK
GEO
LISTS
Campaign:
Create a Campaign.
Action
SCHEDULE
METRICS
Content coming soon
Model:
Model 1
Action
Color
Light
Dark
REGION
State, County & Zip
State, County & Zip
Media Markets
OVERLAY
Population
None
Population
Score File
Drag a new location on to the map
-or-
Search for location
Choose Location
0.0
0.1
Model:
Model 1
Action
OBSERVATIONS:
AVG RESPONSE RATE:
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Marketing Program Details
*
Program Name
Description
*Required
Campaign Details
*
Campaign Name
Description
Campaign Type
Not Set
Not Set
Acquisition
Retention
Other
Contact Channel
Not Set
Not Set
Email
Facebook
Telephone
Other
Fixed Cost
Variable Cost
Variable Cost Unit
Deployment Start Date
Deployment End Date
* Required
Model Details
Name
Description
Dataset
Not Set
Action
Another action
Something else here
Separated link
SPECIAL ATTRIBUTES
Outcome
Treatment
Treatment Emphasis
0.5 (Equal)
0.0
0.1
0.2
0.3
0.4
0.5 (Equal)
0.6
0.7
0.8
0.9
1.0
Row Weight
MISC SETTINGS
Missing Penalty
Global
Local
Equal
Global
Class Weight
1.0 (Balanced)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0 (Balanced)
Split Metric
Gini Index
Entropy
Gini Index
Gini-Hat Index
Stop Grow (%)
2.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4.0%
4.5%
5.0%
5.5%
6.0%
6.5%
7.0%
7.5%
8.0%
8.5%
9.0%
10.0%
Minimum Size (%)
0.5%
0.25%
0.50%
0.75%
1.%
SAMPLING OPTIONS
Sample Size
100% (No Sampling)
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
100% (No Sampling)
Phase
0
0
Compliment
False
True
False
Dataset Details
*
Dataset Name
Description
Dataset:
Score File Details
*
Name
Description
*
Dataset
Model Training Data.csv
Action
Another action
Something else here
Separated link
Generate Score Records?
*
Prune Level
Model Training Data.csv
0.0
0.1
0.2
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Sampling Percentage
100% (No Sampling)
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
100% (No Sampling)
Sampling Phase
0
0
Sampling Compliment
False (Use Base)
True
False (Use Base)
