Explain velocity dips
Connect the Circana number to the occasion, format, or claim that moved it — every line clickable to source.
Merciv for Food & Beverage
Spot a demand shift soon enough to act on it
Read your trade spend, shipment records, and past concept tests against syndicated measurement, menu and foodservice signal, and live consumer conversation — for a complete view of your brand in one place.
Occasions
Read the occasion, not just the aisle
How usage moments are shifting under health, economic, and cultural pressure — and where your category shows up now that it didn’t before.
Flavor cycle
Catch the flavor and format cycle while it’s still upstream
What’s moving from foodservice and conversation toward retail shelves, tracked continuously, so the line review starts from where the cycle is heading.
Say/Do gap
They say healthier — what’s in the basket?
Health intent from surveys next to actual category behavior, so the read reflects what eaters actually buy, not just what they claim to want.
Private label
Defend the shelf against private label with evidence
Where your price and value perception actually stands, cited, and the category story that holds the facing at the next reset.
How food & beverage teams use Merciv
Map GLP-1 exposure by format
Which of your packs are losing units to smaller portions, and which protein and satiety plays are absorbing them.
Bring the why to the line review
Buyers pull their own numbers now. Arrive with the shopper reason behind them, ending in three prioritized actions.
Track occasion migration
Where your SKUs are gaining and losing — mini meals, purposeful snacking, late-night, alcohol substitution.
Pressure-test a claim before it ships
Which protein, gut-health, and clean-label claims consumers actually believe — in their words, with sources attached.
Fund or kill the concept
Put a pipeline concept against live category conversation and a decade of your own concept tests.
See which rival launches stick
Repeat behavior and consumer verbatims on competitor SKUs — not just their distribution gains.
Build the private-label value story
Where shoppers are trading down, why, and the cited case that holds your facing.
The problem
Every launch is a bet on a shift that hasn’t happened yet
A flavor can appear on menus, in recipe search, and in creator content before it moves a scan number. Category reviews and innovation gates leave little time to reconcile those signals with panel, POS, and shipment data.
Common questions
How Merciv works with your data
Does this replace our Circana subscription?
No, and you would not propose that internally. Merciv connects what happened to why — the panel and syndicated read you already license, joined to menu, reviews, and category conversation, every line cited to source.
We built an insights GPT on our own archive. Why add this?
Your archive is the half Merciv doesn’t have to rebuild. What it adds is the licensed external and live-category layer around it, cited to source, and honest when the evidence is thin instead of inventing a plausible answer.
How do you handle the say/do gap?
Stated intent from surveys next to observed behavior in the category, quantified and cited — so the read reflects what eaters actually buy, not just what they claim to want.
Case studies
What teams have done with Merciv
- Beverage
How a Top 10 U.S. Beverage Company Completed 3 Major Research Studies in 3 Months — Down from 18-Month Cycles
A top 10 U.S. beverage company cut research cycles from 18 months to 3 and reduced costs by ~87% with Merciv. 3 major studies completed in one quarter.
Case studyRead case study - Retail
How a Fortune 50 Home Improvement Retailer Prevented a ~$12M Overstock with Real-Time Consumer Demand Intelligence
A Fortune 50 retailer prevented ~$12M in potential overstock after Merciv detected a 43% increase in AC breakdown mentions and identified demand for fans.
Case studyRead case study
Built for how food & beverage handles data
Visit the Trust CenterLicensed data, retailer terms respected
Built on licensed sources with retailer data terms honored, not scraped or resold
No PII, no individual-level decisions
Category and segment intelligence, never person-level targeting
Sourcing methodology published
How every answer is sourced is documented and reviewable
Every claim cited
Each answer links back to source material the reader is authorized to open
Zero training on your data
Your data is never used to train models, yours or anyone’s
SOC 2 Type II
Independently audited controls, cleared for procurement
Who uses it
For insights, brand, and data teams
Request a demo
Make sense of Food & Beverage
Bring a subcategory and the shift you have to explain. We’ll show Merciv reading the occasion behind it, cited.
FAQ