Retail and consumer brands
A promotion buys the first purchase. The household’s routine decides the second.
Loyalty files and order exports show who bought what and when. Syndicated panels describe the category. What’s missing is how a household lives and shops, and which episodes are open right now: a move, a remodel, a new school-year routine. Moonbrush adds that read to your customer records and finds the same patterns across 270M+ U.S. adults, including households you don’t know yet.
The decisionWhere a household shops this week, and whether it comes back.
01Pressures
What retail and consumer brand marketers are up against
Units are flat, shoppers are trading down, and most large retailers now sell media to the brands on their shelves.
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Retail media is now a cost of the shelf
Retailers expect brands to fund their media networks out of trade and brand budgets alike, and each network grades its own homework. Finance wants one incremental read across all of them.
$63.4B
U.S. commerce media ad revenue in 2025, up 18.0% from 2024.Source: IAB and PwC, Internet Advertising Revenue Report: Full Year 2025, April 2026. 2025 calendar year. -
Shoppers are trading down and spreading out
Store brands keep gaining unit share, and households split their trips across club, discount, mass and online. A deal can win this week’s trip without winning the household.
23.5%
Of units sold across all U.S. channels in 2025 were store brands, a record (21.6% in 2021).Source: PLMA, U.S. Private Label Industry Reached $282.8 Billion in Sales in 2025, January 2026 (Circana Unify+ data). 52 weeks ending December 28, 2025. -
Price can’t carry the growth plan any longer
For several years, price increases carried dollar growth while units and visits stalled. Next year’s plan has to add households and trips, not just ticket.
02Blind spot
You know the basket. Not the routine behind it.
What your data shows
Loyalty and order files
Who bought what, when and how often.
Syndicated panels
How the category moves, in aggregate.
Promotion data
Who redeemed, and at what cost.
What it can’t show
How a household lives
Its week, its occasions, its trade-offs.
Which episodes are open
A move, a remodel, a new routine.
Why a trier didn’t return
The second purchase the coupon didn’t buy.
What Moonbrush adds
Moonbrush reads households by routine and occasion around every store and channel, and finds new households living the same patterns. Visits and repeat purchases are read against a holdout you choose.
03Decision
From routine to habit
Households switch stores and brands when a routine breaks. This is the cycle, and where each brand can step in.
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01
The routine
The weekly shop, on autopilot.
We read
How each household lives and shops.
You can
Know who is settled, and who isn’t.
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02
A disruption
A move, a new store nearby, a new school year.
We read
Moves, remodels and routine changes in each trade area.
You can
Arrive while the routine is up for grabs.
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03
The first trip
A new store or brand feels unfamiliar.
We read
What makes a first trip feel easy, by cohort.
You can
Show the trip before they make it.
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04
The second purchase
Repeat, or one and done.
We read
Why triers didn’t come back.
You can
Give a reason to return, not another coupon.
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05
The habit
A new routine settles in.
We read
Verified visits and repeat purchases, against a holdout.
You can
Spend where it moved people.
04Calendar
When retail decisions get made
Households switch stores and brands around a few moments each year, and budgets lock around a few more.
January
New-year reset
After the holidays, households rebuild routines: new diets, tighter budgets, new weeknight meals. Stores reset wellness and value aisles to meet them.
With MoonbrushFind households in each trade area whose routines changed over the holidays, split by the reason they’d switch, before the new habit sets.
February to March
Tax refund season
By law, refunds that include the earned income tax credit can’t go out before mid-February, so a wave arrives by early March. Stock-up trips and put-off purchases follow.
With MoonbrushTime offers to the weeks refunds land, for the cohorts that wait on them, and read the lift against a holdout.
May to September
Moving season
Moving peaks in summer. A move resets the grocery store, the pharmacy, the takeout order and the brands in the pantry, all at once.
With MoonbrushReach households inside a move in each store’s trade area, before and after the move date, with the first-trip message each cohort needs.
July to September
Back to school
School-year routines replace summer ones: lunches, breakfasts, weeknight dinners. Spending starts with July’s deal events, and school starts anywhere from late July to after Labor Day.
With MoonbrushTime messages to local school start dates instead of the national calendar, and split households by the routine that’s changing.
September to November
Next year’s plan
Many retailers close their fiscal year at the end of January, so promotion calendars, joint business plans and retail media commitments get set in the fall.
With MoonbrushStart a 60-day proof in late summer so planning starts from incremental results on your own data, against a holdout you chose.
November to December
Holiday
NRF counts all of November and December as the holiday season. Hosting, gifting and stock-up trips crowd together, and deal-only shoppers arrive with them.
With MoonbrushSeparate the households you’d win anyway from the ones a holiday offer moves, and keep a holdout running through December.
05Cohorts
Same basket. Three different reasons to come back.
Your loyalty file shows three triers who bought the same thing. Their reasons to return are nothing alike.
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Value-first stockers
Buy on deal, stock up, move on.
- What holds them back
- The next coupon, somewhere else.
- What they answer to
- Everyday value, not another promotion.
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Occasion shoppers
Bought for an event or a recipe.
- What holds them back
- The occasion ended.
- What they answer to
- The next occasion, timed to their calendar.
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New to the category
Trying it for the first time.
- What holds them back
- Not sure they did it right.
- What they answer to
- How to get the most from it, early.
Illustrative cohorts, shaped like the splits we return.
06Lessons
What we’ve learned in this market.
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Every store has its own audience.
ALDI gave each of its 2,300+ stores an audience built from its own two-mile trade area, with local creators showing neighbors what a trip there is like.
+9.02% verified store visits, year over yearALDI USA: The Two-Mile Radius -
The moment beats the calendar.
A fuel and convenience retailer reached drivers while they were fueling, with ten-minute offers, and held out pump clusters in every market to prove the visits were new.
+48% verified store entries vs. a holdoutA U.S. fuel and convenience retailer: From Pump to Counter -
Sell the occasion, not the product.
The Padres sold casual fans a full night out, matched to how each neighborhood spends an evening, with the game as the middle act.
+22.0% ticket sales in 30 days vs. the prior 30San Diego Padres: The Night, Not the Game
07Plays
Three places to prove it first.
Each is scoped to one decision, measured against a holdout you choose and read out on day 60.
Usually through
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Spend trial money where it fits
Split launch audiences by occasion and need state, and flag the value-first stockers a coupon only rents for a week.
What you getLaunch audiences by occasion and need state, with the value-first stockers flagged.
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Turn trial into repeat
Split your loyalty file into repeaters, one-and-done triers and category regulars new to the brand, each with its own reason to return.
What you getYour loyalty file split by reason to return, ready for CRM and media.
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Reach movers around every store
Find households inside a move or remodel within each store’s trade area, before they ever search your name.
What you getMover and remodel audiences for every trade area, refreshed daily.
In the workspace.
Every trade area, read on its ownDescribe the households you want in plain English. stage sizes each store’s trade area against the graph and shows whose routines are changing.
A stage screen with demo values.
08Metrics
The numbers retail and CPG teams report upward
Retailers report comps and traffic, brands report penetration and trade return, and media is now judged on incremental sales.
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Comparable sales (comps)
Sales at stores open at least a year, split into traffic and average ticket. Traffic is the half that shows whether households are choosing you.
With MoonbrushMoonbrush flags movers, remodelers and routine changes in each store’s trade area and reads visits against holdout geographies, separating new traffic from traffic you’d have had anyway.
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Household penetration
The share of households that bought the brand in the past year, usually read from a purchase panel. Most CPG growth plans are built around it.
With MoonbrushMoonbrush finds households that live the category’s routines but don’t buy you yet, sized against 270M+ U.S. adults, and reads new buyers against a holdout.
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Trial and repeat
The share of households that try a new item, and the share of triers who buy it again. Repeat, not trial, is what keeps an item on the shelf.
With MoonbrushTriers are split by their reason to return, the second message is timed to their routine, and repeat is read against a holdout of triers.
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Trade promotion ROI
The incremental volume a promotion produces over baseline, set against its cost. Volume from households who would have paid full price counts against it.
With MoonbrushThe persuadability model separates households who’d buy at full price from those a deal moves, so targeted offers and promo media go where they change the outcome.
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Incremental ROAS (iROAS)
Sales caused by the media, divided by its cost, read against people who didn’t see it. Attributed ROAS also counts sales that would have happened anyway.
With MoonbrushEvery audience ships with a holdout you choose, so each channel you activate in is read on the same incremental basis.
09Proof
How you’ll know it worked.
What we measureIncremental trial, repeat rate, store visits and cost per incremental order, read against a holdout you choose.
Also in this market
The first 60 days
- Week 0
Agree on the decision, the data and the success criteria. Paperwork includes the data use agreement and the acceptance criteria.
- Weeks 1–2
Match keys and attach scores in the clean room or your warehouse. Your match rate is reported before anything is built.
- Weeks 3–8
Activate in your channels against a holdout you choose. Outcomes return as they happen.
- Day 60
Read-out on lift and impact, with the validation report. Then an annual program, if the numbers earn it.
10Questions
What retail and CPG leaders ask us first
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We already buy retailer audiences built on their purchase data. What do you see that they can’t?
A retailer’s network sees what a household does with that retailer. Moonbrush reads what it researches, compares and buys across its week, and splits audiences by why each household would act.
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Every partner shows me ROAS. How do I know you’re not just finding people who’d buy anyway?
The persuadability model separates households likely to buy regardless from the ones contact actually moves. Every engagement then starts as a 60-day proof on your data, read against a holdout you choose.
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Can this work store by store? Every one of my trade areas is different.
Yes. Each store gets an audience built from its own trade area, with households inside a move, remodel or routine change flagged, and visits read against matched control geographies.
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Our loyalty data is a strategic asset. What stops it from improving a competitor’s targeting?
It stays in your own instance, and only hashed keys cross the match boundary. It is never pooled with another client’s data and never trains models shared with other clients.
11Rules
The rules that shape retail and CPG targeting
Loyalty programs, baskets, prices and age-restricted products each fall under their own rules, and these are the ones we work within.
CCPA/CPRA and state privacy laws
Shoppers can opt out of sale and targeted advertising, and California treats loyalty discounts as a financial incentive that needs its own notice. Moonbrush applies your opt-out and do-not-contact files to every activation.
New York’s Algorithmic Pricing Disclosure Act
Prices set by algorithm from personal data need a disclosure in New York, and California’s attorney general is examining the practice in retail and grocery. Moonbrush scores are for reach, timing and message, not prices.
Washington’s My Health My Data Act
Purchases like pregnancy tests can be consumer health data, and geofencing around in-person care sites for health ads is banned. Moonbrush excludes Washington and Nevada consumers from health and wellness audiences.
Alcohol ad codes and COPPA
Beer, wine and spirits codes set a minimum share of legal-drinking-age adults for every placement, and COPPA restricts collecting data from children. Moonbrush’s data excludes minors by design.
The lines we don’t cross here
Purchase data comes only from the loyalty, order or partner files you’re entitled to share, hashed before upload.
Your customer data stays in your own instance, is never pooled with another client’s and never trains models shared with other clients.
Modeled ethnicity is never selectable, in any audience.