The decisions your
brand makes
every week

Pricing. Launch timing. Campaign mix. Channel spend. Competitive response. Kapnova gives your marketing team quantitative answers to the exact decisions that drive revenue at a beauty or CPG brand — in 60 seconds.

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The decision calendar

Decisions Kapnova helps
brands make

Every quarter has its pressure points. Here's what your team will be simulating.

Q1 — JAN–MAR
New year reset
New year pricing strategy
Valentine's Day promo depth
Spring collection launch timing
Skincare trend positioning
Q2 — APR–JUN
Peak season
Mother's Day promo decision
Summer SPF launch window
Sephora sale participation
Competitor price response
Q3 — JUL–SEP
Fall setup
Holiday SKU launch decision
Back-to-school campaign mix
Price increase before holiday
TikTok vs Meta rebalance
Q4 — OCT–DEC
Holiday sprint
Black Friday promo depth
Holiday gift set pricing
December markdown timing
Next year price architecture
Sample simulations

Real questions.
Real answers.

Click any scenario to see how Kapnova answers it — using real models, not a language model guess.

Pricing Launch Campaign Spend Compete Forecast
"Should we raise our hero serum price 8% for Q3?"
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Who uses Kapnova

The person in the
Monday morning meeting

You're a marketing leader at a consumer brand who has to answer the CEO's "what's the $5M move?" question every quarter. You don't have a hedge fund's quant desk. You shouldn't need one.

You have a Shopify dashboard, an agency deck that's six weeks old, and a gut instinct that deserves better backup. Kapnova gives you the backup — in 60 seconds, before the meeting.

Marketing Managers — run simulations before leadership asks, bring sourced answers instead of guesses
VPs of Marketing & Growth — review the team's simulations in the shared workspace, make faster decisions
CMOs & CEOs — see the decision log your team is building, stop relying on agency recommendations alone
Brands that fit
Beauty / skincare / CPG
DTC + retail mix
Active on social
Shopify or NetSuite
Multiple SKU launches/yr
Quarterly pricing decisions
Decisions you'll simulate
Hero SKU pricing · Launch timing & positioning · Campaign creative & budget mix · Spend allocation across TikTok / Meta / retail · Competitor price moves · Forecasts with sentiment factored in
Why beauty brands specifically

The signals that matter
in your category

REDDIT SENTIMENT
The backlash signal
r/SkincareAddiction, r/MakeupAddiction, and r/BeautyDeals are where price sensitivity gets surfaced first — before it hits your reviews. Kapnova monitors these in real time and adjusts your simulation when backlash risk is elevated.
TIKTOK TRENDS
The velocity signal
TikTok trend cycles in beauty are fast and punishing. A product going viral the week you planned a price increase is a different decision than the same increase in a quiet week. Kapnova adjusts for trend velocity so your timing is right.
COMPETITOR PRICING
The competitive signal
When a direct competitor drops price, the naive model doesn't know. Kapnova tracks pricing changes across 4 competitor benchmarks per simulation and factors them into the recommendation before you decide.
Built for CPG, not retrofitted

A CPG-calibrated model.
Sharper every quarter.

Kapnova's engine is the same across categories. The model weights aren't. Brands have their own elasticity profile, their own sentiment communities, their own competitive dynamics. We've calibrated for all three.

CATEGORY ELASTICITY
Brand's own price curve
The price elasticity of a $48 serum isn't the same as a $12 cleanser, and neither matches food or supplements. Kapnova's model uses category-specific elasticity benchmarks calibrated from 300+ brand relationships and historical SKU outcomes.
SENTIMENT GRAPH
Brand's own signals
r/SkincareAddiction, r/MakeupAddiction, r/BeautyDeals, beauty-specific TikTok creators, Sephora and Ulta review velocity. The sentiment graph is built around where beauty conversations actually happen — not a generic social listener.
LEARNED OUTCOMES
Compounds with every decision
Every customer's outcome — what they decided, what happened, how the prediction held up — feeds back into the model. Your data trains your dedicated tenant. The pattern learning improves the category model. Nothing leaks across brands.
Get started in 60 seconds

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No signup. No data upload. No IT ticket. Type a pricing, launch, campaign, spend, compete, or forecast question — and see what the math says.

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