How to choose

canvassing turfsknocking area

efficient

Complete SolarSolution

Installs solar systems on residential homes

Market base: Bay Area, Chino Hills & San Diego CA

Prominent canvassing team of 40 canvassers

no presence of pool

presence of pool

Turf 1 VS. Turf 2

Turfs currently chosen based

on:

intuition&

pool presence density

~17% 80%

Canvassing areas are chosen poorly,

not based on demographic data or analytics

Data has found that our

consists mostly of homeowners that:

client market base

Are Married

[existing customers]

Middle-aged Lived in their home for over 5 years

, , ,

Ages46-65

Credit score of over 650

Presence of pool

,

Decision Support System

Allow managers to choosemost efficient turfs

Based on demographical data & pool density

optimizes canvasser’s time & leads

Decision Support System

consists of two parts:

1K means clustering algorithm

2K-nearest neighbours (KNN) algorithm

&

Constraints  Age ≥ 40 years oldMarital Status

Married

Income $175,000+ per yearHome Value $350,000+Credit Rating A-D (A being the best and

H being the worst)

1K means clustering algorithm

to divide potential customers into groups according to characteristics

33.885 33.89 33.895 33.9 33.905 33.91 33.915 33.92 33.925 33.93117.95

117.96

117.97

117.98

117.99

118

118.01

118.02

118.03

118.04

Distribution of Potential Clients

Location

Latitude

Long

itude

1K means clustering algorithm

2K-nearest neighbours (KNN) algorithmto determine which cluster is the closest and likelihood of purchase

Probability of purchase

LATITUDE &

LONGITUDE

INPUT OUTPUT

The End. thank you for your time

Questions?