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Solar Lead Funnels

Rocket Solar - Aug. 2022 - Sep. 2023

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The Challenge

Rocket Solar provides consulting, system design, financing, installation and ongoing service for residential solar systems across the United States.

30% of leads for Rocket Solar came from paid digital traffic. Although there was an existing lead funnel, opportunities existed to increase conversion through varying strategies.

My Role

Product Designer — Interaction Design, Visual Design, User Flows, Rapid Prototyping

Our team was tasked to enhance the Rocket Solar paid search lead funnel to increase leads and loan applications for solar panel systems. My role as a Product Designer was to collaborate with the tech and product team to generate more leads.

Modern Architecture


Our team was tasked to enhance the Rocket Solar paid search lead funnel to increase leads and loan applications for solar panel systems. My role as a Product Designer was to collaborate with the tech and product team to generate more leads.

Measurements of success:

Lead to Credit Pull

We wanted to track how many users completed our lead funnel and got their credit pulled to determine eligibility for their loan.

Closed Solar Loan Volume

Dollar amount of solar loans that were originated.

Overall Impact:

(within a 7 month time span)

in closed solar loans

14% lift
in lead to credit pull

Savings Estimate Lead Form

We created a funnel that combined various learnings. This funnel tailored an electric bill savings estimate based on the lead's lifestyle, current electric usage, and their home's recommended solar system size.

The Savings Estimate Lead Form had a 14% lift in lead to credit pull after reaching statistical significance.

Desktop Prototype

What was our strategy?

Analyze baseline metrics

Determine existing lead funnels and how they're performing. This included collaborating with performance marketing and the Customer Experience team to understand varying causes for fall out during the operational pipeline.

Strategize iterations

Create small enhancements while defining an end strategy to incrementally achieve impactful results.

Test and review findings

Allocate split traffic on variants and observe quantitative data when each test reached statistical significance.

Apply learnings

Evaluate wins and losses and why they possibly happened. Then apply the learnings to the next test.


Part 1: Enhancing the paid search funnel.

One of the first lead forms our team was enhancing was the paid search funnel. Users would be directed to this page from sponsored search engine queries. In this funnel a user would answer several questions that would then give the user a lead score. A Solar Advisor would then call the user after becoming a successful lead. 

Our performance marketing team synthesized data that 2 main audiences existed within these keyword searches. 

solar system savings

People who were interested in how much money switching to solar could save them

solar savings estimate

People who wanted an estimate for a new solar system.

A hypothesis we inferred was that users going through this funnel had unmet expectations. This may have explained why the drop-off rate on the first question of the funnel was so high.

Headline Split Test

Our first split tests involved creating landing page headline tests to see if we could see lifts in conversion when content matched audience intent.

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The first headline test showed a 4% lift in lead to credit pulls. 

The general learning here was that content in our lead funnels should accomodate the specific intents of our paid search audiences. 

Part 2: Enhancing the storefront funnel.

Aside from the paid search funnel, existed the storefront funnel. This funnel actually gave a solar savings estimate to the user if they were eligible. Although traffic & submissions were significantly lower than the paid search funnel, the storefront funnel had a high ratio of users who got connected to a Solar advisor and had their credit pulled. 

Progressive Question Test

One of our first split tests for the storefront funnel involved breaking out the questions on the first question into two pages. Our hypothesis was that users would be encouraged to finish the storefront funnel faster if we utilized the Google Address API to reduce the number of input boxes needed for the address question. Having one task per page would help the user reduce cognitive load as well.

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The progressive question test showed a 2% lift in lead to credit pulls against the control. 

The general learning here was that reducing primary tasks on each question would help drive a lift in conversion.

This test led to another key hypothesis. If we could provide our audience an electric bill savings estimate in the paid lead form, would that create a lift in lead to credit pull?

Part 3: Compounding Strategy

The previous learnings from our split tests started to paint a clearer end vision of what a superior lead funnel would entail. 

We started to hypothesize that an effective funnel needed:

1. Clear messaging about gaining a solar savings estimate
2. One task per page
3. An actual electric bill savings estimate at the end of the funnel

These 3 learnings if applied into one funnel, could entice a user to get on the phone with a Solar Advisor and begin their application.

Compound Learnings Split Test

By combining the learnings of the successful split tests from both the paid search funnel and the storefront funnel, we created a variant that had a 7% lift against the paid search control funnel.

Eventually the Savings Estimate Lead Form became the default paid search funnel and helped garner $x-amount in closed solar loan volume.

Key Learnings

- Small enhancements lead to quicker learnings & iterations (lean UX methodology)

- Cross-functional relationships with data intelligence, engineering, marketing, and product will contribute to
creative solutions from important insights.

- Performance & growth marketing techniques can complement a design team's strategy if previous learnings are correctly implemented and tracked.

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