A residential solar lead clicks a Facebook ad in March, downloads a financing guide in May, and signs a contract in September – and your ad platform still calls it a cold prospect. We build the attribution layer that connects online marketing activity to procurement, financing, and interconnection outcomes, so your reporting matches what the board and your investors actually need to see.
The Problem
Ad platforms report on a sales cycle that doesn't exist in this category
Meta and Google attribute conversions inside a 7 or 28-day click window, but a commercial battery storage deal or a utility DERMS pilot takes 6 to 18 months from first touch to signed contract. Every campaign looks like it failed by the time it actually closes. Marketing gets blamed for weak performance on deals that are still moving through engineering review and financing approval.
Offline conversion events live in systems marketing never sees
Install confirmations sit in field service software, financing approvals sit with a third-party lender, interconnection approval sits with the utility, and signed PPAs sit in a CRM the sales team barely updates. Without a pipeline that stitches these back to the original marketing touch, you cannot say which channel produced a closed deal versus which one just produced a form fill.
Board and investor decks lean on vanity metrics that don't survive diligence
Impressions, clicks, and cost-per-lead look fine in a slide but climate investors and boards are asking for CAC by channel, marketing-sourced pipeline velocity, and how many marketing touches actually turned into signed installs or executed contracts. When those numbers aren't tracked, the marketing function loses credibility in the room where budget gets decided.
Greenwashing scrutiny means every claim in a report needs a data trail
Technically skeptical buyers and increasingly skeptical regulators expect marketing claims about emissions impact, capacity, or efficiency to be defensible with a source. If your reporting stack can't show where a stated number came from, a single misquoted stat in a case study or a webinar deck becomes a credibility problem that outlasts the campaign that created it.
How We Help
We start by mapping your actual buying journey, not a generic funnel template. For a DERMS or grid software company that means separate tracking for utility RFP research, industrial procurement, and policy-driven inbound from IRA or interconnection news cycles. For residential solar or EV charging, it means tracking DTC ad clicks through to financing applications and install scheduling.
From there we build the identity and event bridge.
Once the pipeline is live, we build the reporting layer for two different audiences. The marketing team needs channel-level performance: cost per marketing-sourced opportunity, time-to-close by channel, and content engagement that correlates with pipeline movement. The board and investors need a different view entirely – CAC trended over time, marketing-sourced pipeline as a percentage of total pipeline, and closed-deal attribution tied to real installs or executed contracts, not form fills.
Measurement in this category has to handle a long lag between spend and outcome, so we build cohort-based reporting rather than month-over-month snapshots that punish long sales cycles. A campaign that ran in Q1 gets judged on the cohort of leads it generated, tracked all the way to close, however many quarters that takes.
We also build a fact-check layer into the reporting stack itself. Every claim that goes into a case study, a webinar deck, or an investor update – project capacity, estimated emissions offset, customer count – gets a documented source in the same system, so when a buyer or a regulator asks where a number came from, there's an answer that takes thirty seconds to pull, not three days.
What makes this different from hiring a data analyst or a traditional agency is that we embed as operators, not vendors. We've run growth for companies selling into utilities and industrial buyers, so we build the reporting model around how those deals actually close, not around a generic SaaS attribution template.
What we deliver
- CRM-to-ad-platform attribution model built for multi-month, multi-touch cleantech sales cycles
- Offline conversion pipeline connecting install, financing, and interconnection milestones back to marketing source
- Board and investor reporting dashboard: CAC, marketing-sourced pipeline, and pipeline velocity by channel
- Cohort-based campaign performance reporting that accounts for long sales-cycle lag
- Documented source-of-truth layer for every metric used in case studies, decks, and investor updates
If your attribution model can't survive a sales cycle longer than a fiscal quarter, it isn't measuring your business – it's measuring your ad platform's default reporting window.
Our Methodology
We run this as a 90-day build, not an open-ended retainer with vague deliverables. Days 1-30 are the audit: we map every system that touches a lead from first ad click through signed contract, document where offline events currently get lost, and agree with your team on which board and investor metrics actually matter for your stage and category.
Days 31-60 are the build phase. We wire up the CRM-to-ad-platform connection, build the offline conversion pipeline for install and financing data, and stand up the first version of the reporting dashboard. We test it against real historical deals so you can see whether the model correctly attributes a deal you already know closed – that validation step is non-negotiable before anyone reports these numbers to a board.
Days 61-90 are refinement and handoff. We tune the cohort windows based on your actual sales cycle length, build the recurring reporting cadence your team will run going forward, and train whoever owns marketing ops on maintaining the pipeline without us. Unlike a traditional agency retainer, the goal is a system your team can run – we're not building a dependency, we're building a capability.
How We Work
The engagement runs on a fractional model – you get senior operators embedded in your existing tools and cadence, not a junior account team learning your category on your dime. A typical team is a lead strategist who owns the attribution model design, a data analyst who builds and maintains the pipeline, and a dashboard specialist who builds the board-facing reporting layer.
Week one is discovery: system access, stakeholder interviews with sales and finance, and a review of what's currently reported to the board so we know what to fix versus what to keep. By day 30 you'll see a documented map of your buying journey and a gap list of every broken data connection. By day 60 the attribution pipeline is live and pulling real data, even if the reporting layer is still being refined. By day 90 you have a working dashboard and a documented handoff plan.
We run a weekly working session with your marketing and sales ops leads, not a monthly check-in call. Cleantech sales cycles move slowly deal-by-deal but the data plumbing work moves fast, and we've found weekly cadence catches broken integrations before they cost you a quarter of bad reporting. Clients should expect direct access to whoever is building their pipeline, not an account manager relaying messages to an offshore team.
After the 90-day build, most clients move to a lighter maintenance arrangement – we're available for quarterly model reviews and new-channel integration, but the goal is that your team owns and runs the reporting day to day. We don't structure this as a retainer designed to run indefinitely.
- Marketing performance reporting that reflects actual deal cycles instead of ad-platform attribution windows
- Board and investor decks with CAC, pipeline velocity, and marketing-sourced pipeline tied to real installs and contracts
- A documented, defensible source for every metric used in external-facing claims
- A reporting system your internal team can maintain without ongoing agency dependency
If your cleantech & energy company needs data, reporting & analytics leadership, we should talk.
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Frequently asked questions
How much does a marketing attribution and reporting engagement cost?
Most cleantech engagements for this scope run $25K-$60K for the 90-day build, depending on how many systems need to be connected and how messy the existing CRM data is. Companies with financing partners, install/field service software, and multiple ad platforms to integrate land toward the higher end.
How long until we see usable reporting?
The audit and gap map are done by day 30. A working attribution pipeline pulling real offline conversion data is typically live by day 60.
Do you replace our CRM or ad platforms?
No. We build the connective layer between the tools you already run – HubSpot, Salesforce, your ad platforms, your financing partner's data export, your field service software.
How is this different from hiring a traditional marketing analytics agency?
Most agencies default to a SaaS attribution template built around a 30 to 90 day sales cycle, which breaks immediately against a utility RFP or a financed residential install that takes months longer. We've operated inside cleantech and energy go-to-market motions, so the cohort windows, offline conversion events, and board metrics we build are calibrated to how deals in this category actually move, not a generic playbook.
How do you measure ROI on this kind of engagement?
ROI shows up as decision quality, not a single dashboard metric – can your team defend a budget request with real CAC and pipeline-velocity data instead of impressions, and can a board member ask where a claimed number came from and get an answer in one click. We also track a harder proxy: the percentage of closed deals your reporting can now trace back to a marketing source, compared to what you could trace before the build.
Can this work if our sales cycle spans utility procurement and residential DTC at the same time?
Yes, but it requires two separate cohort models rather than forcing both into one attribution framework. A utility DERMS RFP and a residential solar install don't share a sales cycle length or a buying committee, so we build parallel tracking paths that report into the same board dashboard without averaging two very different journeys into one misleading number.
What kind of company is the right fit for this engagement?
This fits cleantech and energy companies past early-stage – typically Series A or later, or an established company with an active marketing spend of at least $15K per month – where the board or investors are already asking for CAC and pipeline metrics marketing can't currently produce. If you don't yet have consistent CRM data entry from sales, we'd start with a lighter data-hygiene engagement before the full attribution build.
