United States · Health & Fitness · D2C
An untrained algorithm, wasted spend, and a $31 cost per purchase. Ninety days of disciplined weekly optimization later: 543 purchases in a single week at $10.87 each.
Forty Forty is a faith-based health and fitness program targeting adults, particularly women over 40, who want a structured and values-aligned approach to wellness. The product had clear demand, a defined audience, and strong mission alignment. The paid acquisition strategy did not.
When ads.expert came on board in November 2025, the Google Ads account was running without a trained algorithm, spending budget inefficiently across campaigns, and delivering a cost per purchase of $31.85, a figure that made profitable scale impossible. Branded and non-branded search campaigns were cannibalising each other's traffic. The Performance Max campaign had no clear purpose and was not suppressed after its urgency window had closed. Audience insights existed in the data but had never been acted on.
The account was generating purchases every week, but an underoptimised campaign structure meant a large share of potential buyers were never reached, never converted, and never counted.
Campaigns were running without a fully trained bidding strategy. Without sufficient conversion history and properly configured Target CPA or Target ROAS signals, Smart Bidding was allocating budget based on weak signals, inflating CAC and buying impressions that were unlikely to convert. At $31.85 per purchase, the account was structurally unprofitable at any meaningful scale.
Search term overlap between Branded and Non-Branded campaigns meant both were bidding against Forty Forty's own traffic, driving up CPCs on queries that should have been captured cheaply. Without regular search term filtering and negative keyword discipline, the account was paying a premium for clicks it should have owned at minimal cost.
The account data clearly showed that women aged 45 to 64 were the highest-converting demographic in Non-Branded Search. This insight had never been used to inform bid adjustments, ad copy, or audience targeting. The campaigns were serving generic messaging to a broad audience when a clearly defined high-value segment was sitting unused in the data.
The approach was disciplined and sequential. Every week had a clear performance review, a specific optimisation action, and a decision framework for when to hold spend versus when to scale. The result was nine consecutive weeks of improvement with no panic adjustments.
Set differentiated Target ROAS targets across campaign types to give the algorithm clear, achievable goals without over-constraining volume. Non-Branded Search was set at 250% ROAS to prioritise efficiency; Christian Fitness campaigns were set at 90 to 100% to allow volume at a slightly looser threshold where audience overlap justified it. This prevented a single blended ROAS target from optimising toward the wrong campaigns.
Implemented a weekly negative keyword addition cadence across all campaigns, systematically filtering irrelevant search terms before they could waste budget. Simultaneously ran regular search term audits to identify and block cross-campaign cannibalisation between Branded and Non-Branded Search, ensuring each campaign owned its intended query segment without competing against itself.
Made a deliberate decision to cut spend during early optimisation weeks, reducing budget by approximately 54% to allow the bidding algorithm to re-optimise without burning through budget on low-quality conversions. Spend was only scaled back up once CAC had stabilised below the target threshold, preventing the common mistake of scaling before the algorithm was ready.
The PMAX campaign was built for a specific urgency window and paused once that window closed, rather than left running and diluting budget efficiency. Keeping a campaign live past its useful purpose increases algorithm confusion and cost per lead. Pausing it at the right moment preserved budget quality for the always-on campaigns heading into January.
Identified women aged 45 to 64 as the highest-converting demographic segment in Non-Branded Search and activated this insight across bid adjustments, ad copy, and audience targeting. This allowed the algorithm to prioritise the highest-value traffic segment while messaging was refined to speak directly to this audience.
Established a consistent weekly performance review covering spend, CAC, purchase volume, search term quality, and bidding behaviour, with a documented win, action, and next-step framework for each week. This prevented drift, ensured every change had a clear hypothesis, and created an accountability layer that meant no optimisation opportunity was missed.
A 66% reduction in CAC across 9 weeks, achieved through bid strategy discipline, weekly negative keyword cadence, budget pacing, and demographic targeting, without a single learning phase reset.
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