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.
Facebook and Instagram for Inland Empire brands that need to create demand for a product nobody was searching for that morning.
Delivered remotely for brands across Riverside and California.
A rooftop tent, a new patio set, a bumper for a truck someone already likes the look of: none of that arrives as a search. The ad has to create it. Which means the constraint on growth is not targeting, it is how many genuinely different concepts you can put into the auction each month. For most Inland Empire brands that is a production problem before it is a media problem, and the good news is that the product is physically in your building, which makes shooting far cheaper than it is for a brand whose inventory sits with a supplier overseas.
The account gets built for throughput. Campaigns consolidated so ad sets accumulate enough conversions to get out of learning, Advantage+ Shopping running with the existing-customer budget cap set deliberately rather than left at whatever the platform picked, and a clean boundary between it and the manual prospecting that feeds it new angles. Concepts are briefed and tagged by angle — durability, install difficulty, capability, before-and-after, price versus the brand-name equivalent — so results read as lessons rather than as a list of winning ad IDs.
Catalogue is where heavy-goods brands leak money. Product sets segmented by margin after freight and by stock cover, so dynamic ads stop promoting a pallet item that is three weeks out on the next container or a SKU whose delivered margin does not survive the delivery. And Conversions API with hashed identifiers, proper browser-to-server deduplication and a real event match quality target, because since the iOS changes signal quality is a bidding lever rather than a tracking nicety.
Inland Empire demand for anything outdoor, off-road or powersports-related moves on a clear annual curve. Interest builds through autumn as temperatures drop and desert recreation gets going, holds through the winter events season, and falls off through triple-digit summers when nobody is planning a trip to Johnson Valley. Home and furniture runs on a different but equally sharp curve into Q4. We plan creative volume and budget against those curves instead of a flat monthly spend, front-loading concept testing before the ramp so the winners are already identified when demand arrives. The production advantage is local and real: you own the inventory, you have a warehouse with a loading dock and consistent light, and a scale shot next to a pallet or an install sequence in the yard is more persuasive than a rendered studio image. We build shoot blocks around what is already in the building, which is why creative volume here costs less per concept than it does for a brand that has to ship samples in.
The same standard of work we run for every client — applied to a Riverside 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 Riverside 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.