One Measurement System, Built on Three Foundations
Most teams run incrementality testing, MMM, and attribution as three separate workstreams — different tools, different teams, conflicting results. Social Vriddhi MMM unifies all three into a single always-on system, so each layer makes the others more accurate.
Incrementality Testing
The Causal Layer
Geo-Lift tests, Conversion Lift studies, and A/B tests, unified in one Experiments Hub. This is where you get real causal truth — and results feed back into the MMM as Bayesian priors, sharpening accuracy with every experiment you run.
Marketing Mix Modeling
The Integration Layer
Always-on Causal Bayesian MMM that fills the gaps experiments cannot cover across every channel and every market, continuously refreshed. It calculates marginal return on the next dollar spent and connects causal truth to daily execution.
Attribution Correction
The Execution Layer
Social Vriddhi applies calibration multipliers from MMM & experiments to correct your attribution, delivering true incremental ROAS at the campaign and ad-set level with a unique multiplier for every channel reflecting what each one actually drove.
Calibrate Your Attribution with MMM
Most enterprise teams have invested heavily in MTA and attribution infrastructure. Social Vriddhi doesn't ask you to replace it.
Social Vriddhi is built around the modern measurement framework: the measurement triangle of MMM, incrementality experiments, and attribution. Rather than replacing your MTA, Social Vriddhi runs MMM and incrementality experiments alongside your existing attribution, then applies calibration multipliers — channel-level correction factors derived from causal measurement — to align your MTA output with true incremental ROAS.
The result is an incrementality-corrected attribution layer that works inside your existing stack, giving your analytics team the auditability they need and your performance team the accuracy they've been missing.
