Built for India's D2C brands. Know exactly where your next rupee should go.
[01] Introducing Loom
LOOMMarketing Intelligence Engine
Computes every scenario using deterministic modeling and proprietary intelligence.
Insights
What's happening and why
Simulations
What-if scenarios and forecasts
Recommendations
The most actionable next step
Benchmarks
How you compare against the best
Loom is our proprietary marketing intelligence engine, computing every scenario to surface the most actionable insight.
No guesswork. No black-box attribution. Just deterministic intelligence you can trust.
Deterministic
Every number traces back to real computation, never a guess.
Comprehensive
Every channel and signal, reconciled into one view.
Predictive
Models what happens before you commit real budget.
Actionable
Surfaces the one decision that matters, not nine metrics.
What Loom does
From data to decisions. All in one place.
Brand Intelligence
One score for whether the brand is fundamentally healthy.
Channel Intelligence
Reconciled from real signals, never one platform’s self-reported claim.
Budget Simulator
Expected revenue and confidence before you commit real budget.
Benchmarks
See exactly where you sit against real brands in your category.
Recommendations
A specific channel, a specific change, graded against what actually happened.
[02] How it works
One path to a real answer. Not the ones platforms take.
Loom computes every scenario using real data and proprietary intelligence, then explains the answer with confidence.
Google Ads
Campaigns, keywords, spend, conversions
Meta Ads
Campaigns, creatives, audiences, spend
Shopify
Orders, revenue, products, customers
Other Sources
CRM, email, offline, benchmarks, more
LOOMMarketing Intelligence Engine
Real computation. Proprietary intelligence.
Response Curves
Diminishing returns modeled per channel, not assumed
Attribution
Real contribution share, triangulated from five signals
Marginal ROAS
What the next rupee of spend actually returns
Deterministic
Every number traces back to real computation, never a guess.
Comprehensive
Every channel and signal, reconciled into one view.
Predictive
Models what happens before you commit real budget.
Actionable
Surfaces the one decision that matters, not nine metrics.
Loom doesn't guess. It computes every scenario to surface the most actionable insight.
[03] How you compare
Ahead or behind. Not just up or down.
Blended Yield (MER) sits in the top quartile for fashion & apparel brands. Revenue Growth Rate is bottom quartile. That's what a trend line alone won't show you.
Blended Yield (MER)
Top quartile6.0×
Median for this category: 3.2×
Revenue Growth Rate
Bottom quartile3.8%
Median for this category: 15.0%
Repeat Purchase Rate
Above median40.9%
Median for this category: 35.0%
[04] What intelligence you get
A specific answer: scale this, pull back on that.
Run the what-if yourself. Drag spend up or down on any channel or campaign and see the projected outcome before you commit.
↓ ReduceMeta Ads
Marginal return on Meta has fallen to roughly 1.7×, below the ~1.8× breakeven point at your contribution margin, and spend is closing in on its economic ceiling. Reallocating a portion of this budget toward Google Ads, which still has meaningful headroom, is likely to lift blended returns.
Spend change
₹271,039 → ₹253,039
Expected impact
Minimal
Confidence
medium
Based on your own data
Revenue vs. spend, High reliability fit
High confidence↑ Scale upGoogle Ads
Google Ads' marginal return is still roughly 1.9×, comfortably above the ~1.8× breakeven point, and its economic ceiling is much further away than Meta's. Increasing spend here is likely value-additive before diminishing returns set in.
Spend change
₹218,573 → ₹240,573
Expected impact
₹52,800 – ₹79,200
Confidence
high
Based on your own data
Revenue vs. spend, High reliability fit
High confidence[05] Why trust it
Every recommendation gets graded against what actually happened.
Scaled spend 14% last quarter on this same reasoning — revenue landed within the modeled range.
Flagged as near its economic ceiling two periods ago — marginal return has continued to fall since.
Called as a high-yield, low-spend opportunity — revenue rose, though less than the upper estimate.
[06] Questions
Before you get started.
A dashboard shows you numbers. Needlwork tells you what to do about them, a specific channel and a specific spend change, and grades its own past calls against what actually happened afterward.