The Measurement & Optimization OS for Retail and Ecommerce

Platform-reported ROAS is calculated by each ad platform using its own attribution model, and every platform is incentivized to claim as much credit as possible for conversions. The result is systematic overstatement: channels that touch the end of the customer journey (branded search, retargeting) claim credit for sales that would have happened anyway, while upper-funnel channels (Paid Social, TikTok, display) are undervalued because they rarely get the last click. In practice, last-click attribution can undervalue Paid Social by up to 17x relative to its true incremental contribution. Sellforte replaces platform-reported ROAS with incrementality-corrected ROAS, derived from always-on Causal Bayesian MMM and calibrated by geo lift and conversion lift experiments, giving every channel a ROAS figure that reflects what it actually caused, not what it claimed credit for, at the campaign and ad-set level, every day.

Last-click attribution depends on cookies, pixels, and tracked sessions to connect ad exposures to conversions. Three structural trends have made this increasingly unreliable: iOS privacy changes have eliminated tracking for a large share of mobile users (in some cases only 7% of app sessions are correctly attributed to paid channels), GA4 migrations routinely introduce trend breaks that make historical comparisons unreliable, and entire revenue streams including Amazon, wholesale, physical stores, and offline sales are invisible to web pixels entirely. For some brands, more than 45 to 50% of users are effectively untracked, meaning budget decisions are being made on data that reflects less than half the picture. Sellforte uses Marketing Mix Modeling, which does not rely on cookies, pixels, or individual user tracking. It models the statistical relationship between media spend and total sales, including offline sales, app revenue, and cookieless environments, so the full picture of media impact is captured regardless of what your pixel can and cannot see.

Traditional Marketing Mix Modeling is delivered as a consulting engagement: data is collected, a model is built over several weeks or months, and results are presented in a report once or twice a year. By the time insights arrive, the media decisions they were meant to inform have already been made, and the model is immediately out of date as market conditions, competitive activity, and media mix change. For brands running tens of millions in annual media spend, this means a full year of budget decisions made without reliable incrementality data. Sellforte is an always-on MMM platform, not a consulting study. The model runs continuously, ingests new data automatically, and delivers updated incremental ROAS at the campaign and ad-set level on a daily cadence. Where a traditional MMM study might tell you which channels worked last quarter, Sellforte tells you which campaigns are working this week and recommends exactly what to do about it before the next media buying decision is made.

Sellforte connects to Meta, Google, and TikTok via direct API integration. When Sellforte's Media Buyer Agent generates a budget or bid recommendation, based on the latest incrementality-corrected ROAS and marginal return curves for each campaign and ad set, the recommendation appears inside the Sellforte platform for review. You confirm every change before it goes live; nothing is applied automatically. Once approved, the change is pushed directly to the ad platform with no manual re-entry and no platform-switching required. Every outcome is then measured against a modeled counterfactual, so the incremental impact of each change is tracked and fed back into the model, sharpening future recommendations over time. This closed loop from measurement to recommendation to execution to learning is what makes Sellforte an operational system rather than a reporting tool.

Sellforte connects to over 500 data sources, including all major ad platforms (Meta, Google, TikTok, Pinterest, programmatic), data warehouses (Snowflake, BigQuery), CRMs, ERP systems, and ecommerce platforms. Data ingestion is automated, replacing manual data pulls and fragmented reporting flows with a single, continuously refreshed data pipeline. For brands with existing data infrastructure, Sellforte writes results and recommendations directly into Snowflake or BigQuery, so outputs are available inside the tools your analytics team already uses. Approved media recommendations are pushed back to ad platforms via API, completing the loop from data ingestion to execution without manual intervention at any stage.

Most customers are connected and seeing initial model outputs within a few weeks of starting onboarding. The process begins with automated data connections to your ad platforms, data warehouse, and any additional data sources, replacing whatever manual data flows existed before. Every Sellforte customer has a dedicated Customer Success Manager and Data Scientist assigned from day one, who configure the model for your specific commercial environment including your market structure, promotional calendar, seasonality patterns, and media mix. For multi-market deployments, markets are typically onboarded in sequence with a validated first-market model used as the foundation for subsequent markets. Sellforte has committed to and delivered six-week onboarding timelines for complex enterprise deployments including data warehouse migrations and new market additions.

Sellforte is built for multi-market and multi-brand deployment from the ground up. The platform runs separate models per country or region, each calibrated to local market conditions, media mix, and commercial dynamics, while maintaining consistent methodology across all markets so results are comparable. For brand portfolios, Sellforte can model multiple brands simultaneously within a single platform instance, with shared infrastructure and separate model outputs per brand. Expansion to additional markets or brands does not require rebuilding from scratch: the validated model architecture from existing deployments is used as the foundation, significantly reducing time-to-value for each new market added. Sellforte currently runs always-on measurement across 22 live markets for brands including C&A (18 markets), bonprix (expanding across European markets), and Azzas 2154 (multi-brand fashion portfolio across Latin America).

Each market model in Sellforte is built to reflect the specific commercial reality of that market, including local currency, local media mix, local competitive environment, and local promotional calendar. Seasonal events, peak trading periods, and promotional mechanics (discount depth, coupon structures, category sales) are modeled explicitly per market rather than applied as a global assumption. This means a Black Friday campaign in the US, a Singles Day campaign in APAC, and a summer sale in Germany are each modeled with the correct market-specific context, so media ROI figures are comparable across markets without being distorted by differences in promotional intensity or seasonality. For grocery retailers and fashion brands where promotional depth is a primary revenue driver, Sellforte separates promotion-driven sales from media-driven sales in each market independently, ensuring media ROI is never inflated by a discount event that would have driven sales regardless of media investment.

Incrementality-corrected ROAS is the true incremental return on ad spend for each campaign and ad set, calculated by applying calibration multipliers derived from Sellforte's always-on MMM and incrementality experiments to your existing attribution data. Standard platform-reported ROAS measures what each channel claimed credit for. Incrementality-corrected ROAS measures what each channel actually caused: the sales that would not have happened without that specific media investment. The difference is commercially significant. A channel with a platform-reported ROAS of 9.0 may have a true incremental ROAS of 5.0 once sales that would have occurred organically are removed from the calculation. Budget decisions made on the 9.0 figure systematically overinvest in saturated or low-incrementality channels and underinvest in channels that are genuinely driving new revenue. Sellforte delivers incrementality-corrected ROAS at the campaign and ad-set level on a daily cadence, so every budget decision from annual planning to next week's pacing is based on what media actually drives, not what platforms claim credit for.

Most MMM tools model media in isolation, treating promotional periods as noise to be controlled for rather than signals to be understood. Sellforte explicitly models your full commercial picture including promotional mechanics (discount depth, coupon codes, targeted offers, category sales, mass discount events), seasonality (weekly, monthly, and annual patterns), weather effects, and major trading events like Black Friday, alongside media spend. This matters because promotional periods are exactly when media measurement is most likely to be corrupted. A revenue spike during a 20% off coupon week will be attributed to whatever media was running at the time by any tool that does not explicitly separate promotional uplift from media uplift. Sellforte decomposes total sales into base sales (what would have happened with no media and no promotion), promotion-driven sales, and media-driven sales, so your media ROI reflects what media actually did, independent of what happened to be running alongside it.

No. Sellforte is designed to work alongside your existing attribution infrastructure, not replace it. Most enterprise teams have invested significantly in MTA tools, GA4, or custom attribution builds, and Sellforte does not require you to unwind that investment. Instead, Sellforte runs always-on MMM and incrementality experiments alongside your existing attribution, then applies calibration multipliers, which are channel-level correction factors derived from causal measurement, to align your attribution output with true incremental ROAS. The result is an incrementality-corrected attribution layer that works inside your existing stack. Your analytics team retains the auditability and user-level data they need; your performance team gets the accuracy they have been missing. For brands that have invested in MTA infrastructure, Sellforte is the layer that makes that investment more accurate, not the tool that replaces it.

A quarterly MMM consultancy delivers a report. Sellforte delivers a decision. Traditional MMM consultancies run a study, present findings, and repeat the process once or twice a year. The output is a slide deck or dashboard that tells you what worked last quarter, by which point the budget has already been spent and the media mix has already moved on. Sellforte is an always-on platform where the model runs continuously, data is ingested automatically, and updated incrementality-corrected ROAS is available at the campaign and ad-set level every day. Beyond measurement, Sellforte closes the loop to execution: the Media Buyer Agent pushes approved budget recommendations directly to Meta, Google, and TikTok via API, so the insight and the action happen in the same system. No consultancy does this. The result is not a better report; it is a fundamentally different relationship between measurement and media buying.

Most customers are live and seeing model outputs within a few weeks of starting onboarding. Sellforte has delivered fully operational deployments, including data warehouse migrations and new market additions, within six weeks for enterprise customers. The speed of implementation depends primarily on data availability and the complexity of your market structure, not on Sellforte's internal processes. Every customer has a dedicated Customer Success Manager and Data Scientist from day one, who manage the onboarding process end-to-end and configure the model for your specific commercial environment. For multi-market deployments, the first market is typically validated and live fastest, with subsequent markets onboarded progressively using the first-market model as a foundation.

Sellforte is used by leading ecommerce and retail brands across North America, Europe, Latin America, and APAC. Current customers include C&A, Lidl, Intersport, Tchibo, bonprix, Represent, Odlo, BrandAlley, FCP Euro, Farmacity, Douglas, KiK, Peek & Cloppenburg, Finnish Design Shop, Musti Group, Azzas 2154, Brahmin, and smartphoto, among others. More than $1 billion in annual media spend is optimized on Sellforte across 22 live markets. Customers span fashion retail, fashion ecommerce, grocery retail, specialty retail, quick service restaurants, and DTC, including more than 20 businesses operating at $1 billion or more in annual revenue. Sellforte achieved an NPS of 76 in 2025 across its customer base, among the highest recorded in the MMM software category.