Solar, EV, and home-electrification companies depend on a form: enter an address, return utility rates and incentive stacks, and send a qualified lead to an installer. If that form is slow, inaccurate, or outdated, the lead disappears before a person ever sees it. We build and maintain the growth infrastructure that keeps the experience fast and up to date.
The Challenge
Quote calculators fail as soon as utility rates or incentive rules are updated
A solar or heat-pump quote calculator is only as good as the utility rate schedule and incentive data behind it, and both change on a schedule nobody in engineering is tracking. A rate tier update or a state rebate program running out of funds can silently push every quote in a territory 15-20% off, and the first sign is usually a spike in sales complaints, not an alert.
Address-level eligibility checks become fragile at precisely the moment they matter most
Eligibility depends on utility territory, net metering rules, interconnection queue status, and local permitting, and all four vary by address, sometimes street by street inside the same zip code. A geocoding edge case, a utility territory boundary that doesn't match zip-code assumptions, or a cached lookup that's a quarter stale turns a qualified homeowner into a false rejection or a false approval. Both failure modes cost money: the first kills a real lead, the second sends an unqualified lead to an installer who wastes a truck roll.
No growth owner is responsible for routing leads to installer and contractor networks
Once a lead clears the calculator, it has to route to the right installer based on territory, capacity, certification, and current queue depth, then get a response inside the window where the homeowner is still comparing options. Most climate tech companies built this routing logic once around a handful of launch partners and never revisited it as the installer network grew, so lead-to-response time degrades quietly as the partner list scales past what the original logic was designed for.
IoT monitoring data lacks a growth or marketing distribution layer
Hardware products with monitoring, solar inverters, battery systems, smart thermostats, generate a stream of real performance data (production, savings, uptime) that would make genuinely differentiated marketing content and retention triggers. Instead that data sits in the ops or engineering data pipeline, built for alerting and support, with no export or aggregation layer feeding lifecycle marketing, referral triggers, or case study generation. The company ends up writing generic savings claims in marketing copy while sitting on the actual customer-level numbers that would be more credible and convert better.
What We Do
We begin by mapping the real conversion journey, not the marketing funnel shown in the slide deck.
Then we build the specific infrastructure that's typically absent: a rate and incentive data layer with a genuine refresh schedule rather than a one-off import, address-level eligibility logic that manages utility territory edge cases instead of relying on zip-code approximations, and installer routing based on current capacity and certification rather than only the initial partner list.
We work inside your existing engineering team instead of delivering a spec and vanishing.
For measurement, we monitor the signals that truly predict revenue in this category: territory-level quote-to-lead conversion, eligibility check accuracy (false rejects and false approves), lead-to-installer-response time, and the funnel stages where stale utility rate or incentive data is reducing conversions.
The outputs are tangible. We rebuild or strengthen the quote calculator's rate and incentive data pipeline, giving it a defined refresh cadence and a fallback for unavailable sources instead of letting it quietly serve outdated numbers.
This fractional model works particularly well for climate tech because the team is deep-tech first. Your strongest engineers are appropriately focused on hardware, physics, and certification, not whether the quote form converts at 12% or 22%.
What we deliver
- Rate and incentive data pipeline audit and rebuild – a defined refresh cadence for utility rate schedules and incentive programs, with fallback behavior when a data source is stale or unavailable
- Address-based eligibility checker hardening – territory-accurate net metering, interconnection, and permitting logic with instrumented false-reject and false-approve tracking
- Installer and contractor lead routing rework – capacity- and certification-aware routing that scales past the original launch partner list, with response-time tracking by territory
- IoT and monitoring data export layer – aggregated, anonymized performance data (production, savings, uptime) piped to lifecycle marketing and case study workflows
- Full-funnel instrumentation from quote calculator entry through installer handoff, so conversion loss is visible by step and by territory, not just as a single top-line number
In climate tech, the quote calculator isn't a marketing asset layered on top of the product. It IS a real customer's first product interaction, and it breaks just like hardware does: quietly, until someone downstream bears the cost. An outdated rate table doesn't trigger an error. It simply costs you the lead.
Our Methodology
We run a 90-day sprint using the same disciplined phases as every WF engagement, with diagnostics tailored to this category. Days 1-30 focus on auditing: we follow each step from address entry through installer handoff, examine the utility rate and incentive data sources in active use, and pinpoint where stale data, geocoding mistakes, or routing logic gaps are reducing conversions. We also catalog any existing IoT or monitoring data and assess whether its current form is usable for growth.
Days 30-60 cover building and integration. We tackle the highest-leverage fix first, generally the rate/incentive data pipeline or eligibility checker, because both failure modes silently distort every downstream metric. Fixing routing on top of faulty eligibility data only sends bad leads faster. We build within your current stack instead of recommending a rebuild, since climate tech companies have already made substantial infrastructure investments in these systems; the missing pieces are usually maintenance ownership and instrumentation, not the architecture itself.
Days 60-90 focus on measurement and handoff. We test the fix using real territory-level conversion data, document refresh schedules and fallback logic so your team can maintain them once we roll off, and implement ongoing monitoring that detects the next rate change or incentive program update before quotes quietly deteriorate again. Unlike traditional growth agency work, which generally ends with campaign optimization, we address the underlying data pipeline that decides whether campaign leads convert in the first place.
Our Approach
The initial 30 days are fully embedded and diagnostic: we join your existing engineering standups, get read access to the quote calculator, eligibility checker, and routing logic, then map the full data flow from end to end. By day 30, you receive a detailed findings document identifying where conversions are being lost – whether through stale rate data, geocoding false rejects, or routing to over-capacity installers – ranked by estimated impact.
Days 30-60 move into building. Depending on your preferred engagement structure, we work directly in your codebase or alongside your team. We focus on one or two fixes instead of touching everything simultaneously, because a partial solution that's shipped and measured is better than a complete rebuild still awaiting code review three months later. Your team must give us access to data (rate sources, installer network information, historical conversion logs) and designate one contact who can quickly resolve integration blockers.
Starting on day 60, we follow a weekly rhythm: a standing review of what shipped, what the instrumented conversion data indicates, and what comes next. Each month, we zoom out to assess funnel-wide metrics rather than only the individual fix, since a routing improvement may perform well alone without increasing total quote-to-install conversion when eligibility accuracy remains the actual constraint.
Most climate tech engagements last 3-6 months for the first build-and-validation cycle because utility rate and incentive data follows its own timeline, and the engagement should include at least one complete change cycle to demonstrate that the pipeline holds. Work beyond that usually covers continued data pipeline maintenance and ownership of expansion into new territories, priced separately from the original build.
- Quote-to-lead conversion rate by territory
- Eligibility check accuracy (reduction in false-reject and false-approve rates)
- Lead-to-installer-response time
- Rate and incentive data freshness (time from source change to production update)
- Usable output from IoT/monitoring data for lifecycle and retention marketing
If your climate tech company needs growth engineering leadership, we should talk.
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Frequently asked questions
What does growth engineering cost for a climate tech company?
Most engagements cost $15K-$35K per month, based on how much rate, eligibility, and routing infrastructure is already in place compared with what must be rebuilt. Repairing a functional but neglected calculator costs less than building for a company without any eligibility logic.
When will we start seeing results from a growth engineering engagement?
Within the first 30 days, you'll receive audit findings and a prioritized list of fixes, often giving the team its first clear view of exactly where quotes are being lost. The initial fix – usually the rate/incentive data pipeline or eligibility checker – typically launches and demonstrates measurable conversion impact by day 60.
How will the growth engineering team work with our current engineering staff?
Rather than operating separately, we embed with your existing engineers, participate in sprint planning, and access the actual calculator, eligibility, and routing codebases. Your team remains focused on the hardware and physics model – where deep-tech companies should devote their strongest engineering resources – while we take ownership of the growth-facing infrastructure layer.
How is Winston Francois different from a conventional climate tech growth agency?
Traditional growth agencies improve ad campaigns and landing pages while assuming that underlying data – utility rates, eligibility, and installer capacity – is accurate. We assume it likely isn't, because this category's data layer fails silently and often goes unnoticed until conversions decline.
How is ROI measured for a climate tech growth engineering engagement?
Our core metrics are territory-level quote-to-lead conversion, eligibility check accuracy, and lead-to-installer-response time, since these three measures determine how many genuine leads reach an actual installer. We also measure data freshness directly – how quickly a utility rate or incentive update reaches production – because stale data is this category's most common silent conversion killer.
Which climate tech companies are the best fit for this service?
This service suits companies that already have a live quote calculator, eligibility checker, or installer network in production, typically from post-seed to Series C, where growth-facing infrastructure was built quickly for launch and has lacked a dedicated owner ever since. It's especially suitable when your engineering team is deep-tech first – hardware, physics, certification – and growth infrastructure is the priority everyone recognizes but no one has capacity to address.
