Solo Stove

CHALLENGE

Measuring Incremental Contribution Across Every Channel, Region, and Cost

Solo Stove’s marketing, ecommerce, and finance data lived in a dozen platforms, each with its own login, its own definition of a conversion, and its own claim on the credit. Last-click attribution over-credited the channels that touched a customer last and under-credited everything that built demand earlier. Amazon data came from multiple partners and needed heavy validation. Revenue, COGS, and fee data across four regions and four currencies reconciled in spreadsheets, not in a single margin view. And no single view tied upper-funnel spend to downstream sales, revenue to real contribution margin, or daily performance to decisions that had to be made the same week.

The stakes were real. Leadership was weighing a budget shift toward influencer marketing, and the team needed data-driven scenarios before moving money — but the deeper constraint was operating posture itself: defending every channel against contribution margin, in-season, on the same numbers marketing, finance, and operations could all stand behind. Their wish list featured a few must-haves above all else:

1. One governed source of truth unifying every marketing, ecommerce, advertising, and finance system
2. A measurement approach that estimates true incremental contribution by channel, against real margin rather than top-line revenue
3. Daily-grain data, available in time for in-season decisions
4. A clean split of upper-funnel awareness from lower-funnel performance, so ROI stays honest

Beyond unifying the data, Solo Stove needed an AI-powered operating layer that could read margin alongside revenue, flag drift the moment it appeared, and put answers in front of marketing, finance, and operations in time to act on them.

SOLUTION

Turning Fragmented Spend Into One Model of What Actually Works

CorralData unified Solo Stove’s marketing, ecommerce, and finance data into one AI-powered operating platform. Every dollar of revenue reads against Solo Stove’s own SKU-level COGS, fulfillment, card fees, and shipping costs, currency-normalized across the US, EU, Canada, and Australia. Salesforce Commerce Cloud across all four regions, Amazon Seller Central, Amazon DSP, Google Ads, Meta Ads, Microsoft Advertising, Google Analytics 4, and Impact all flow into the same warehouse, joined to a contribution-margin layer Solo Stove maintains for every SKU.

On top of that foundation, CorralData built a marketing mix model that tells the team where the next dollar earns the most contribution, a Pre-Marketing Contribution Margin view that lets finance read every channel and region against real cost, and AI agents that put answers in front of marketing, finance, and operations in real time.

Benefit #1: A Region-Aware, Margin-Aware Marketing Mix Model

The centerpiece is a marketing mix model that answers one question directly: of all the dollars going out, which ones are actually driving contribution to the business? The model credits ad spend across the days it keeps working, not just the day it ran. It looks at every channel at once, so channels that spend together don’t all claim the same sale. It fits separately for each region, because what works in the US doesn’t carry over to the EU. And because the MMM output sits next to the same contribution-margin layer Solo Stove maintains for every SKU, channel decisions are grounded in margin and not just top-line revenue. Every number in every dashboard traces back to SQL the team can inspect.

Benefit #2: Model Truth Next to Platform Claims

CorralData puts the model’s contribution view next to what each ad platform claims and what last-click attribution credits, all on the same board. The team sees in real time how much of a platform’s self-reported revenue is genuinely incremental versus inflated. The model updates as new data comes in, and weekly trend views surface when a channel’s real contribution starts shifting. When ad platforms over-report, the gap shows up immediately, not at quarter-end.

Benefit #3: Margin-Aware Commerce Across Four Regions

The same warehouse that runs the MMM also runs Solo Stove’s contribution margin. Every order line reads against SKU-level COGS, fulfillment, card fees, and shipping, currency-normalized across the US, EU, Canada, and Australia into one Pre-Marketing Contribution Margin view that refreshes daily. Finance defends every channel and every region against real margin, not just top-line revenue. Marketing operates against the same number underneath. When a channel’s revenue is up but margin is flat, the platform shows it in the same view, in the same week.

Benefit #4: A Daily Operating Cadence Built for In-Season Decisions

Paid media, ecommerce, and contribution margin all refresh at daily grain, feeding the MMM, the dashboards, and an AI-generated executive summary email that the team reads every morning. The data pipeline is actively monitored, so when the Impact affiliate connector dropped credentials, the issue was identified, fixed, and resolved within days. Dashboard and reporting requests turn around in hours, not weeks. The result is an operating cadence where the MMM, the margin view, and the channel-level dashboards refresh in time for in-season decisions, not weeks after they’re due.

Benefit #5: Plain-English Answers Through AskCorral

Solo Stove’s team asks questions of their unified data through AskCorral, CorralData’s AI agent. Marketing, finance, and operations all pull from the same governed data layer, and media questions always run through the marketing mix model under the hood. The same AI delivers automated executive summaries on a regular cadence, plus alerts when something needs attention. The team doesn’t have to look for what’s changed; the platform brings it to them.

RESULTS

From Guesswork to One Operating Layer Across Marketing, Finance, and Ops

Marketing decisions now run through the MMM. The model has surfaced significant variation in real channel contribution, with paid search delivering several multiples of the return generated by paid social. It has also worked as a control: during a week when a Meta account issue distorted in-platform reporting and shifted credit toward Google Brand, the MMM caught the distortion before the team could misread it as a real performance shift.

Finance reads every channel against contribution margin, not just top-line revenue. Revenue, COGS, fulfillment, card fees, and shipping all flow through one currency-aligned view across four regions, and Pre-Marketing Contribution Margin is a daily metric, not a quarterly reconciliation. The proposed influencer budget shift can now be pressure-tested as a margin-aware scenario, not a hunch.

Operations works off a daily cadence. Paid media, ecommerce, and margin data all refresh at daily grain, feeding every team’s dashboards and an AI-generated executive summary that lands every morning. Reporting and dashboard requests that used to take weeks now turn around in hours, and pipeline issues surface and resolve before they cost a decision. The cadence held under load through peak holiday: when the business scaled more than 23x in four months, the operating layer kept the team in front of the surge instead of behind it. 

For a brand running media across a dozen platforms in four regions, the difference is no longer about which dashboard is open. It’s whether marketing, finance, and operations are all working from the same numbers, at the same speed, against the same definitions.