ACCELERATING THE SOLAR REVOLUTION WITH DATA SCIENCE

We use machine learning techniques to drive down solar customer acquisition costs

We combine your historical customer data with open source information to provide meaningful customer lead scoring. We use behavioral modelling techniques to identify high value customers, and discover new growth areas.

We provide data-driven insight on strategy and pricing at each step of the sales process. Sales teams receive tailored recommendations for each individual customer, allowing them to maximize their conversion rates.

Our algorithm maximises the return of sales team in the field by providing score-optimized routing and scheduling of customer visits.

Identify High Value Customers

Ensure High

Pull-Through Rates

Optimize Sales Teams In The Field

How SolFox Works

Open Source

Data

Your Customer

Data

Accurate Lead Scoring

High Value Neighbourhoods

Optimized Sales Team Routing

Tailored Recommendations

Reduced Customer Acquisition Costs

Open Source

Data

Your Customer

Data

Accurate Lead Scoring

High Value Neighbourhoods

Optimized Sales Team Routing

Tailored Recommendations

Reduced Customer Acquisition Costs

Our approach is completely data-driven. We augment your dataset with essential information about a customer's environment: government incentives, installed solar density, electricity rates, demographics, weather... This also involves classic qualification criteria such as roof direction, typical utility bills, and months in residence.

We use techniques from machine learning and behavioral modeling to assign each lead a score based on their likelihood of going solar. It can complement or replace existing methods you may have for classifying and prioritizing leads. We use clustering methods to provide geospatial analysis and shed light on high value areas for new potential customers.

We maximise the return and efficiency of time spent in the field by providing score-optimized routing and scheduling to sales teams. We can also dig deeper into customer and lead data to generate insights into what really influences people on their decision to go solar. This allows us to make detailed recommendations on sales strategy and pricing for each individual customer.

Being smarter about how you interpret and manage data makes for a more successful approach to sales and customer acquisition!

Jonathan Mather

e: jonathan.mather@solfox.io

SolFox is a pre-seed startup, co-founded by two UC Berkeley Engineering PhDs. It was the winning entry at the 2015 HackTheSun hackathon at the SfunCube Accelerator in Oakland (now PowerHouse). We are on the lookout for strategic partners in the solar industry. If you feel that your company could use a boost from cutting edge data science and machine learning techniques then we would love to hear from you! Please get in touch at:

Caroline Le Floch

e: caroline.le-floch@solfox.io

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