Paid media that's measured in patients, not leads.

Reasoning

• Google gets the larger share at launch because search captures people already looking for a treatment. It produces booked consultations fastest and gives us clean data in the first two weeks.
• Meta gets a meaningful share because a new treatment has little search demand yet. Meta is where we introduce it to people who don't know it exists. Much of Meta's impact will show up later as branded Google searches.
• The split depends on search volume. Before launch I'd check Google Keyword Planner for the treatment name and related concerns in RUMA's area. If monthly searches are low (a brand-new device or treatment name), I'd flip the split toward Meta, since Google can't spend money on searches that don't happen.
• $4,000 on Meta is about $133 a day. That's enough for one consolidated campaign, not many small ones. Meta's algorithm needs roughly 50 conversions per ad set per week to exit learning, so splitting the budget thin would starve it.
• The reserve keeps us from committing too early. On day 14 I compare cost per booked consultation (not cost per lead) by channel and move the $1,000 to whichever channel is winning.

• Why a website instead of instant forms: instant forms produce cheap leads with low intent. If we test them, I'd use the "Higher intent" form type with a review screen and 1–2 qualifying questions (treatment interest, timeline).
• Why so few ad sets: at about $133/day, consolidating gives the algorithm enough data. I test new ideas through creative, not by adding more ad sets.
• Policy check: Meta limits some data use for health-related businesses, so I'd confirm that our events and custom audiences are allowed before relying on them.

Between stages, the things that move people forward are: speed to lead (contact within 5 minutes), automated reminders (text at 48 hours and 2 hours before the appointment to protect show rate), and a treatment plan presented at the consultation. After treatment, a review request and rebooking reminder timed to the treatment cycle (e.g. about 3–4 months for neuromodulators) turn one patient into recurring revenue.

What I'd look at next: average revenue per patient is $1,500 ($40,500 ÷ 27). The weakest step is booking: 75% of leads never schedule. Raising lead-to-booking from 25% to 35% with the same spend, and the rest of the funnel unchanged, would produce about 38 patients instead of 27 and roughly $16,000 more revenue. I'd fix follow-up (Q16) before spending more on ads.

What I'd review before reallocating

• Revenue per patient by channel: do Google patients buy higher-value treatments or packages? Compare collected revenue and 90-day lifetime value, not just conversion rate.
• Sample size and time lag: Meta leads often take longer to decide. A 30-day window can undercount them, so I'd check 60- and 90-day cohorts.
• Overlap between channels: is Meta generating the branded Google searches? If branded search volume drops when Meta is paused, Google is getting credit for Meta's work (see Q10).
• Headroom: Google impression share lost to budget. If Google already has 90% impression share, more budget buys little.
• Marginal cost: the next $1,000 on Google will cost more per lead than the average $1,000 did. I'd decide on expected marginal cost per treated patient.
• Campaign-level detail: one bad Meta ad set or an instant-form test could be dragging the whole channel down.
• Follow-up parity: were Meta leads contacted as fast as Google leads? Slow follow-up makes any source look worse.
• Data integrity: is lead source captured reliably in the CRM (UTMs and click IDs), or are "unknown" leads hiding Meta's true results?

Decision rule: move budget toward whichever channel has the lower marginal cost per treated patient, as long as it stays below our maximum allowable acquisition cost (Q7).

How I'd set RUMA's maximum allowable acquisition cost

1. Start with first-visit gross profit ($780). Spending more than this loses money on the first visit.
2. Subtract costs gross margin doesn't cover: free-consultation time, no-show cost, front-desk labor, and payment processing fees.
3. Agree on a profit share with leadership. For example, if RUMA wants to keep two-thirds of first-visit gross profit, the maximum is about $260.
4. Add lifetime value where it's proven. If CRM data shows injectable patients return 3× a year, 12-month gross profit might be about $2,000. We could then pay more for those patients while staying profitable, but only on repeat rates we've actually measured, not assumed.
5. Set it per treatment. A one-time laser package and a recurring neuromodulator patient have different maximums.

For context, Q5's $222 cost per patient sits comfortably inside this range.

Before increasing

• Confirm the 5× is based on collected revenue in the CRM, not platform-reported conversion value.
• Check search impression share lost to budget. That's how much room is left. Lost to budget at 30% means real headroom. At 5%, we'd need to expand keywords, not just add budget.
• Confirm the clinic can handle more patients: provider schedule availability and front-desk capacity.

How fast

• +20–30% every 5–7 days. Larger jumps can push Smart Bidding into recalibration and spike CPA.
• Account for the lag: revenue arrives 2–4 weeks after the click, so I judge each increase on booked consultations first, then confirm with revenue.

What I'd monitor

• Marginal ROAS: extra revenue ÷ extra spend.
• CPC and CPA trend, impression share, and top-of-page rate.
• Search term quality. More budget often pulls in looser queries.
• Lead-to-booking and show rate, to confirm quality holds.
• Stop condition: marginal ROAS below 3× (or cost per patient above target), or impression share maxed out. Next steps at that point: new keyword themes, a wider radius, adjacent treatments, or YouTube/Demand Gen remarketing.

The piece that holds it together: a single lead ID created at first contact and carried onto the patient record. Every downstream event can then be tied back to the original click and campaign.

HIPAA guardrails: BAAs with call tracking and data-routing vendors. No pixels on patient portal or intake pages. Server-side tagging to strip anything sensitive. Ad platforms only receive hashed contact info, a generic event name, and a dollar value, never the treatment or health condition.

• What the platforms will say: Meta claims it (7-day click window) and Google claims it (last click). Add up platform reports and this one patient becomes two. That's why platform totals always exceed actual patients.
• How I'd credit it: Meta is the originating channel. Google Brand is the capturing channel. A branded search means the person already knew us, so I wouldn't treat brand search as a demand generator when deciding budget.
• Source of truth: the CRM counts one patient, one revenue amount. Channel credit is shown as first touch (Meta) and last touch (Google Brand). Internally I'd use a 40/20/40 position-based model, where the first and last touch each get 40%, as a tiebreaker.
• Self-reported attribution: add "How did you hear about us?" at booking. Answers like "I saw you on Instagram" are strong evidence of Meta's contribution.
• Test incrementality: track branded search volume against Meta spend, and run a periodic geo holdout or Meta Conversion Lift study to measure what Meta actually adds.

How I'd present it to leadership: "One new patient, two paid touches. Meta introduced her to RUMA. Five days later she searched our name and called. She's counted once in the $X revenue. In the channel view, Meta gets credit for starting it and Google Brand for closing it. Our overall number is blended cost per patient (total spend ÷ total new patients), which can't be double counted."

1. Agree on definitions and a source of truth. What counts as a lead, a booking, a patient? The CRM/scheduler owns bookings and patients, and the POS owns revenue.
2. Line up the data. Same date range, time zone, and currency. Note each platform's attribution window and whether it reports by click date or conversion date.
3. Build a reconciliation sheet. One row per system, one column per event, and the gap between each system and the source of truth.
4. Inventory Google Ads conversion actions. Look for duplicates (e.g. a GA4 import and a native tag for the same form), "every" vs "one" counting, and secondary actions mistakenly set as primary.
5. Inventory Meta events. Check pixel and Conversions API deduplication (matching event_id), Event Match Quality, and duplicate or legacy events.
6. Test the tags live. Use Tag Assistant, GTM preview, and Meta Test Events. Look for tags firing on button click instead of success, on thank-you page reloads, or not at all inside the booking iframe.
7. Check GA4 setup. Key event configuration, cross-domain tracking to the scheduler, referral exclusions (booking and payment domains), and Consent Mode.
8. Check call tracking. Number swap coverage, repeat callers counted as new leads, and qualified-call thresholds.
9. Check CRM data. UTM and click ID capture rate, duplicate records, spam leads, and manual entries with no source.
10. Connect the scheduler and CRM. Confirm bookings are linked to their originating lead.
11. Fix and document. Write a one-page tracking plan with event names, triggers, and owners.
12. Monitor ongoing. A monthly reconciliation with an agreed tolerance (e.g. ad platforms within ±15% of the CRM).

1. Capture at the lead: gclid/gbraid/wbraid and Meta's click cookies (fbc, fbp), plus email and phone. Store them on the lead record so they stay attached through the patient record.
2. Define stages in the CRM: Lead → Booked → Attended → Treated (with collected value).
3. Google: use enhanced conversions for leads, which matches hashed email and phone and uses the gclid when present. Upload via a native CRM integration, the Google Ads API, or Zapier, at least daily and always within 90 days of the click. Each stage is its own conversion action. Treated (with value) becomes the primary bidding goal once volume allows, and the others stay secondary.
4. Meta: the Conversions API from the CRM sends custom events (e.g. QualifiedLead, ConsultAttended) and Purchase with value, matched on hashed email and phone, fbc, and the lead ID. For instant-form campaigns, use Meta's "Conversion leads" optimization, which learns from CRM stage updates.
5. Move the bidding goal down the funnel: Google goes from Target CPA on bookings to Target CPA on attended, then Target ROAS on revenue once there are about 30–50 a month. Meta moves from Lead to a deeper custom event when it reaches about 50 a week.
6. Keep it compliant: generic event names and dollar values only. Never send treatment type, diagnosis, or anything that reveals a health condition. BAAs with integration vendors, and a legal review before launch.

1. Tracking: submit a test lead. A broken tag or booking iframe can make a good page look like it doesn't convert.
2. Message match: does the headline repeat the ad's treatment, offer, and promise?
3. First mobile screen: what it is, who it's for, the result, and a visible CTA, all without scrolling.
4. Load speed: mobile Largest Contentful Paint (LCP) under 2.5 seconds. Most paid traffic is mobile.
5. Offer and pricing clarity: "starting at" pricing, consultation fee policy, financing. Hidden prices lose price-checkers.
6. CTA and booking path: one primary action, the number of steps to book, and whether online booking is available.
7. Form friction: number of fields, required fields, and click-to-call as an alternative.
8. Trust: real results photos (compliant and consented), review rating and count, provider credentials (MD/NP/PA), and clinic photos instead of stock.
9. Objection handling: pain, downtime, how long results last, safety, and who performs the treatment.
10. Exits and behavior: navigation links that pull people away, plus Microsoft Clarity heatmaps and session recordings showing where people stop scrolling.

A high CTR with low conversion can also mean the ad attracts curiosity clicks. I'd check whether it's all audiences or only certain placements.

Why it's 40% at any CPC: cost per lead = CPC ÷ conversion rate. Going from 3% to 5% multiplies CPL by 3/5 = 0.6, a 40% reduction whether CPC is $2 or $8.

The caveat: I'd confirm the extra 40 leads book at the same rate. A change that adds leads by lowering the bar (like removing a qualifying question) can raise lead count while lowering booked consultations.

• If one staff member books 40% and another 15%, it's a process and training problem, not a lead problem.
• If booking rate varies by ad or campaign with the same follow-up, it's lead quality or offer mismatch.
• Quick wins while diagnosing: an instant automated text with a booking link, a 5-minute response time goal during business hours, a 6-touch follow-up over 10 days, and held-open consultation slots for new leads.

How I'd protect the accounts

• Verified business and domain, two-factor authentication for every user, at least two admins, and a clean payment method.
• A pre-launch compliance checklist for every ad and landing page, with provider sign-off on medical claims.
• Landing pages held to the same standard as the ads. Platforms review both.
• Handle disapprovals through the proper review process. Don't repeatedly resubmit rejected ads, because that hurts account standing.
• Build creative around what's allowed and effective anyway: provider expertise, the process, education, patient experience, and reviews.