Account Consolidation
Campaigns collapsed into a structure with enough conversion volume per ad set to exit learning, plus exclusion logic that stops prospecting and retargeting bidding against each other.
Your hot sauce is already on a shelf at Jewel-Osco. The job here is not just creating demand — it is proving the demand you created was new, and not a shopper who would have reached for the jar anyway.
Delivered remotely for brands across Chicago and Illinois.
A Fulton Market hot sauce has no search volume until somebody manufactures a reason to want it. That manufacturing is creative work — how many genuinely different concepts you put into the auction, how fast you replace them, and how well the ad speaks to a Midwest buyer who is more comparison-minded and less impulse-driven than the coastal audience most DTC playbooks were written against.
Chicago adds a measurement complication that a pure-DTC brand never faces. The same snack, sauce, beverage or housewares line is very likely stocked at regional grocery and hardware chains, moving through a foodservice distributor, and listed on a marketplace by somebody. Meta will cheerfully claim credit for a customer who saw the ad and then bought the product in an aisle in Lincoln Park. That is why the channel gets judged on blended MER and geo holdouts rather than on platform-reported ROAS, and Chicago's metro is genuinely well suited to holdout design because you can match markets on comparable retail distribution.
Underneath both sits signal. Conversions API done properly — server-side events, hashed identifiers, correct deduplication, match quality watched rather than assumed — because since iOS 14 the quality of what you send Meta is a bidding lever, not a reporting detail. It is also worth handling carefully in Illinois, where the state's privacy statutes make casual identifier collection a bad habit to fall into. Then the catalogue: multi-pack and case architecture segmented by margin and stock cover, so Advantage+ is not quietly selling the SKU that loses money once freight is counted.
The Chicago version of this service lives or dies on two things a national playbook ignores. The first is incrementality against retail. When a brand here advertises nationally it is simultaneously driving grocery and hardware sell-through in its own backyard, so we design geo holdouts around DMAs with comparable retail distribution and read the difference in direct orders and, where the data exists, in retail velocity. Most brands discover both cannibalisation and genuine lift; knowing the ratio changes what you are willing to spend. The second is the production constraint. Chicago gives you a usable outdoor shooting window from roughly May to early October, so a grill, patio, cooler or outdoor-living brand that wants summer-looking creative in June has to have banked it the previous season. Accounts here fatigue in February running last year's three images while CPMs climb into the spring ramp, and no amount of media buying fixes a creative library that the weather closed.
The same standard of work we run for every client — applied to a Chicago brand’s realities.
Full service detailCampaigns collapsed into a structure with enough conversion volume per ad set to exit learning, plus exclusion logic that stops prospecting and retargeting bidding against each other.
ASC campaigns with the existing-customer budget cap set deliberately, creative slotted in by concept rather than dumped in bulk, and a clean boundary with the manual prospecting that feeds it.
Catalogue connected through the Shopify channel, product sets segmented by margin and stock cover, and DPA templates that look designed rather than machine-assembled.
Server-side events with hashed identifiers, correct browser-to-server deduplication and an event match quality target of 8 or better. Since iOS 14, signal quality is a bidding lever.
A rolling calendar of concepts, hooks and formats across UGC, static and motion, briefed from customer language and structured so results read by angle rather than by ad ID.
Geo-split and conversion-lift tests across prospecting and retargeting, so budget decisions rest on revenue the business actually gained rather than on what the platform claimed.
We do not work off a rate card. Every Chicago engagement starts with a fixed statement of work — named deliverables, named dates, one number — written after we have looked at your store, not before. If a smaller first step would serve you better, we will say so.
Get this scopedPixel, CAPI, deduplication, match quality and catalogue health checked first. Everything else in this service is downstream of what Meta knows about your buyers.
We cut the account back to a structure with enough conversions per ad set to learn, then set the prospecting-to-retargeting split on purpose instead of by accident.
Angles mined from reviews, support tickets and comment threads become a monthly production plan with named hooks and a fixed number of new concepts entering the auction.
Naming and structure that roll performance up by angle, hook and format, so the lesson outlives the asset that taught it and the next round starts smarter.
A geo holdout or lift test before any step change in budget. Meta reports on itself; we would rather know what happens to revenue when the ads stop.
Anonymised under NDA. Figures pulled from the client’s own analytics.
~$6M/yr DTC, 900+ SKUs across size and colour variants, US · Shopify Plus
Returns ran at 31% and refund cost consumed the entire paid media margin. One size chart image served 40 different fits, and 62% of add-to-carts started on a collection page that never showed variant availability. The named constraint: no new product photography budget, so every fix had to come out of the existing asset library and the review corpus.
~$3.1M/yr, 28 SKUs, subscription + one-time, US · Shopify (Klaviyo, Recharge)
A 14-day roast window meant every discount cut into a 41% gross margin that could not be rebuilt. First-order CAC was $52 against a $38 AOV, so the business only worked on the second order and 64% of customers never placed one. The named constraint: no discount deeper than 10%, ever, on any channel.
“Our last agency was reporting a 6.2 ROAS in Meta while the bank account told a completely different story. First thing these guys did was get CAPI wired up properly and rebuild the product catalogue feed, so the dynamic ads stopped pushing flavours we hadn't stocked in months. Then they made us report blended MER from month one and the first number was ugly and honest. It took about four months to move MER from 2.1 to 3.4, and I actually trust the dashboard now, which I did not expect to say about an ad agency.”
Thirty minutes with the strategist who would actually run your account. We screen-share your store, read your data live, and tell you the three highest-value things we can see from the outside.
Prefer to write it out? [email protected] gets a real reply the same business day, Mon-Fri, 9am-6pm MT.