Seer Interactive reported in 2025 that 87% of SearchGPT citations matched Bing's top organic results. BrightEdge tracked AI Overview presence across healthcare searches from 2023 to February 2026 and found coverage grew from 59% to 88% (Healthcare AI Evolution Report, 2026). OpenAI said in January 2026 that more than 230 million people ask ChatGPT health and wellness questions weekly.
In a lot of the clinics we audit, the ad click is no longer the start of the decision. It is the cleanup step after the patient already compared options somewhere else. The clinics that fix this first will get better leads than the ones still trying to solve everything with paid traffic.
We ran the prompt "best bariatric surgeon in Tijuana" in ChatGPT last week. Five names came up. Our client was not one of them. A doctor with 12 Google reviews and a single-page website was. The difference: he had schema markup, consistent naming across 4 platforms, and 3 blog posts with procedure data that ChatGPT could extract. Our client had 400 reviews, 15 years of experience, and a website that said "Call for pricing."
This is the order of work we use when a clinic's profiles, procedure pages, and doctor entities are not lining up across platforms.
Methodology note: internal data comes from direct audits and management of Google Ads accounts, websites, and digital profiles of plastic surgery and bariatric clinics in Tijuana's Zona Rio, oriented toward US/Canadian medical tourism patients. External benchmarks are cited with source and year. Operational ranges reflect our direct experience, not the entire market.
Why this still has an execution window
Google has tested placing ads in and around AI-generated search experiences. If Google keeps monetizing these surfaces, free visibility gets tighter. There is still room because most clinics are underbuilt here, but do not force the early-SEO analogy harder than it deserves.
In recent audits of Zona Rio clinics, fewer than 10% had what we would consider adequate schema markup and consistent entity structure. The gap is not theoretical. In this market, basic execution is still weak.
BrightEdge reported that only about 17% of sources cited in AI Overviews also appeared in the organic top 10 for the same query (Healthcare AI Evolution Report, 2026). If your strategy stops at traditional SEO, you are likely missing how assistants choose what to surface.
That 12-review surgeon who appeared over our 400-review client is not an outlier. It is a pattern. We have now run this test across bariatric surgery, plastic surgery, and dental implant queries. In every specialty, we found at least one case where a less-reviewed, less-experienced practitioner appeared because their digital structure was cleaner. The AI does not know who has more experience. It knows who it can verify. It knows whose name matches across platforms, whose credentials are published in structured format, and whose procedure pages contain extractable data. That is what "digital legibility" means in practice.
Google's AI Overviews already show ads in some configurations. In February 2026, we observed sponsored results appearing inside AI Overview panels for "bariatric surgery Tijuana cost" queries. When Google finishes monetizing these surfaces fully, the organic window inside AI-generated answers will narrow. Right now, most of the AI Overview surface is still organic. That will not last forever. The clinics that build entity authority now will have a structural advantage when that space gets more competitive.
Here is what makes this window more concrete. We audited 14 clinics in Zona Rio between October 2025 and February 2026. Two had complete schema markup. Three had consistent NAP across all platforms. Zero had MedicalProcedure schema on their procedure pages. One had published pricing. The median clinic had at least one duplicate GBP listing they did not know about. That is the competitive field right now. If you fix these problems before the next wave of clinics starts paying attention, you get a head start that compounds over time.
The other factor: most clinics in this market are still spending the majority of their acquisition budget on Google Ads. When we look at the accounts we manage, the typical split is 70-80% paid, 10-15% organic SEO, and close to 0% on AI visibility. That budget allocation reflects a world where the patient journey starts with a Google search. But for a growing number of patients, it does not start there anymore. It starts with a question to an AI assistant. And the clinics that are invisible in that channel are paying more per patient in ads to compensate, without realizing why their cost per lead keeps climbing.
What tends to show up
SEO still cares about ranking and traffic. In practice, GEO is about whether assistants can identify you consistently, verify your details, and find enough corroboration to surface you confidently. SEO and AI visibility overlap, but assistants tend to rely more heavily on clear entities, structured data, and corroborating sources.
Think of the entity as the doctor's or clinic's digital record: name, specialty, location, credentials, affiliations, mentions across independent sources. When a patient asks ChatGPT for the best bariatric surgeon in Tijuana, the system may rely on trained knowledge and, depending on the product mode, web retrieval. If your names, profiles, and credentials do not line up, you stop showing up consistently.
In Tijuana medical tourism, those gaps get more visible. The patient searching "best bariatric surgeon in Tijuana" from Phoenix is searching in English on Google.com. For many healthcare queries, AI Overviews now appear frequently. By the time the ad shows up, the patient may already have a shortlist.
BrightEdge reported a sharp reduction in AI Overview presence for local-intent searches between 2023 and 2025. Local Google Maps presence still matters for patients searching with geographic intent. If you care about both local discovery and research-stage visibility, you have to cover both.
One internal metric we use is Citation Share: what percentage of AI mentions in your specialty and location belong to you. It is not an industry standard. It is a framework we use internally to measure progress.
To understand why this metric matters, you need to see the actual patient journey. It is not the funnel your agency showed you in a slide deck. It is messier, faster, and it starts before Google.
We monitor the prompts patients actually type. These are five real patterns we have seen show up repeatedly in our tracking:
"Best bariatric surgeon in Tijuana for someone over 300 lbs." "Compare mommy makeover costs: Tijuana vs Colombia vs Miami." "Is it safe to get a tummy tuck in Tijuana? What hospitals are accredited?" "FACS certified plastic surgeon in Tijuana with before and after photos." "Gastric sleeve Tijuana all-inclusive package with hotel and transport from San Diego."
Each of these prompts is looking for a different kind of answer. The first wants a name. The second wants a comparison table with prices. The third wants safety signals: accreditation, complication rates, hospital names. The fourth wants credentials and visual proof. The fifth wants a package with logistics. If your website only says "World-class care at affordable prices," you are answering none of them.
The clinics that show up in these answers tend to have three things in common. They publish specific data that the AI can extract and repackage: prices, credentials, procedure details, recovery timelines. They have consistent entity information across multiple independent sources, so the AI can verify what it finds. And they have content structured in a way that maps to how patients actually ask questions, not how the clinic wants to talk about itself.
Notice where Google search falls in that timeline. Step 4. Maybe. By the time the patient sees your Google ad, they may have already built a shortlist from ChatGPT, validated it on Reddit, and checked before-and-after photos on Instagram. Your ad is not introducing you. It is either confirming a decision that was already leaning your way, or it is trying to override a preference the patient already formed without you. That second scenario is much more expensive to win.
Entity architecture: where most clinics break
A common pattern we see in Zona Rio audits: the website says "Dr. Garcia, Plastic Surgery." GBP says "Centro Quirurgico Garcia." Doctoralia says "Juan Manuel Garcia Rodriguez, MD." The hospital directory uses yet another variant. Sometimes the doctor goes by "Dr. Chuy" on Instagram but "Juan de Jesus Garcia Rodriguez" on his medical license. Sometimes an assistant created a second GBP listing years ago when the doctor moved to a different suite in the same building, and nobody deleted the old one. Sometimes the RealSelf profile was claimed three years ago and never updated.
We have found clinics with 3 active GBP listings for the same doctor: one from the old office, one from the current one, and one that Google auto-created from a hospital directory. In that case, the doctor did not know two of them even existed.
The clinic-vs-surgeon entity problem
In clinics with 5 to 10 surgeons, you have to decide whether to build entity authority around the clinic brand, individual surgeon brands, or both. Most clinics in Tijuana default to clinic-level branding and neglect surgeon-level entities.
When the surgeon has a stronger digital entity than the clinic, assistants may surface the surgeon first and the clinic as context. That creates a real ownership problem. If Dr. Garcia's personal brand drives 60% of the AI mentions and he leaves for another clinic, he takes the visibility with him. We have seen this happen. The clinic kept the reviews, the website, the ads budget. But ChatGPT started recommending Dr. Garcia at his new location. Nobody planned for that.
The answer is not to suppress surgeon-level branding. It is to build both layers deliberately and make sure the organizational entity has its own authority independent of any single doctor.
The "Dr. Chuy" problem deserves its own note because it comes up in almost every audit we run in Zona Rio. In Mexican culture, nicknames are common and widely used. A surgeon whose legal name is "Juan de Jesus Garcia Rodriguez" might be known to every patient, nurse, and colleague as "Dr. Chuy." His Instagram handle is @drchuy_cirugia. His patients leave Google reviews mentioning "Dr. Chuy." His WhatsApp business card says "Dr. Chuy." But his cedula profesional, his CMCPER certification, his Doctoralia profile, and his hospital directory listing all say "Juan de Jesus Garcia Rodriguez." The AI sees two different people. Or worse, it sees a fragmented entity it cannot confidently resolve, so it skips him entirely and surfaces someone whose name is consistent everywhere.
The fix is not to stop using the nickname. It is to make sure the legal name appears as the primary identifier on every platform, with the nickname handled as a secondary reference where appropriate. On Instagram, "Dr. Juan de Jesus Garcia Rodriguez (@drchuy_cirugia)" in the bio. On Google reviews, respond using the full name: "Thank you for trusting Dr. Juan de Jesus Garcia Rodriguez with your care." On the website, the full name in the page title and schema, with "also known as Dr. Chuy" in the text. This way the AI can resolve both references to the same entity.
The surgeon-who-left scenario is worth understanding in detail because it is the highest-stakes version of the entity ownership problem. We worked with a clinic where one surgeon had built significant personal brand presence: his own Instagram with 40,000 followers, guest appearances on two podcasts, a RealSelf profile with 200+ reviews under his name, and three blog posts on the clinic website authored by him. When he left to start his own practice, the clinic kept the website, the Google reviews, the GBP listing, and the ads budget. But within six weeks, ChatGPT was recommending that surgeon at his new location. The clinic's AI visibility for that specialty dropped noticeably. The reviews still existed, but they mentioned the surgeon's name, not the clinic. The blog posts still existed, but they had his author byline. The entity authority had been built around the person, not the organization. Rebuilding it took months.
The lesson is structural. Build entity authority at both levels from the start. The organizational entity needs its own schema, its own credentials (hospital accreditation, COFEPRIS registration, organizational affiliations), its own content that is not dependent on any single surgeon's name. When a surgeon has strong personal brand presence, that is an asset. But the clinic needs its own independent entity layer so that if any individual doctor leaves, the organizational visibility survives.
If your names, profiles, and credentials do not match across platforms, you reduce the probability of being surfaced consistently.
This is cleanup work, not brand work. NAP alignment across every platform. Schema markup that declares your entity type with sameAs properties linking all your profiles.
Tijuana clinics actually have one advantage here: real credentials they can publish clearly and tie back to official sources. Board certification from CMCPER, verified cedula profesional, CONACEM certification. These are credentials that can often be cross-checked against official registries if you publish them clearly and consistently. But most clinics bury them in a PDF curriculum or mention them in a paragraph nobody reads.
Birdeye reported in 2024 that the majority of GBP views came from discovery-style category searches. If your primary category is "Medical Spa" instead of "Plastic Surgeon," you reduce your visibility for patients searching by that category.
Content that assistants can extract
Vague copy can still sell a patient. It gives assistants almost nothing usable. Content full of brand language and light on specifics gives assistants very little to pull.
Dedicated procedure pages. Each major procedure gets its own page with clinical description, candidacy criteria, recovery timeline, price range, risks, FAQs, and MedicalProcedure schema. A generic services page rarely gives assistants enough specificity to reuse confidently.
Published pricing. When a patient asks "how much does a tummy tuck cost in Tijuana?" and your site says "Schedule a consultation for pricing," assistants have nothing to cite. Publishing a range gives assistants something concrete to reuse. Hiding pricing usually leaves you out of cost-related answers.
Almost every surgeon pushes back on this the first time. "Every patient is different. I cannot put a price online." The answer is operational, not theoretical: you are not quoting a final price. You are publishing a range that reflects typical cases. "$4,500 to $6,500 USD, includes anesthesia, OR, hospitalization, and post-op garment." This has to be decided by the medical director. The marketing coordinator is not going to win that argument by herself.
Detailed reviews as data. A review that says "Dr. Rodriguez performed my sleeve gastrectomy at VIDA Wellness. I traveled from Phoenix. Lost 35 kilos in 6 months. Follow-up was excellent" exposes useful elements: procedure, doctor, facility, patient origin, reported outcome.
The privacy objection comes up immediately. Ask for the experience, not the clinical detail. "Tell us how it went" is fine. "Mention your procedure and results" is where you start getting into trouble.
The pricing negotiation with the medical director is usually the hardest part of this entire process. It is not a marketing decision. It is a clinical and business decision that the marketing coordinator cannot make alone. In every clinic we have worked with, this conversation follows the same pattern. The surgeon says "every patient is different." The coordinator says "but the website needs a price." Nobody resolves it, and the page goes live without pricing. The AI ignores it.
Here is how we frame the conversation when we sit down with the medical director. You are not publishing a quote. You are publishing a range that reflects 80% of your cases. "$4,500 to $6,500 USD" is not a commitment. It is a signal that tells the AI (and the patient) that you are a real option in this price category. If a patient's case falls outside the range, you explain that during the consultation. But without a published range, the AI cannot include you in cost comparison answers. And cost comparison is one of the most common prompt patterns in medical tourism. "How much does a gastric sleeve cost in Tijuana vs the US?" If your answer is "call us," you are not in that answer.
The review privacy question comes up in every onboarding call. Surgeons worry about HIPAA (even though HIPAA does not apply to Mexican clinics in most scenarios), about liability, about patients oversharing clinical details. The distinction that matters: you can ask for an experience. You cannot ask for clinical disclosure. "Would you share how your experience went?" is fine. "Please mention your weight loss results and any complications" is where you create risk. The review is the patient's speech, not yours. Your job is to make it easy to leave one, respond to it professionally, and not coach the clinical content. When patients voluntarily mention their procedure, results, and origin city, that review becomes a rich data point for AI extraction. But you cannot manufacture that. You can only create the conditions for it.
FAQ content mapped to actual patient prompts. The prompts patients type into ChatGPT are conversational: "I'm 220 lbs and want gastric sleeve in Mexico. Is Tijuana safe? How much does it cost? Who should I go to?" or "Compare the safety and cost of mommy makeovers in Tijuana vs Miami, focusing on board-certified surgeons." Your FAQ content needs to answer these patterns.
External validation and cross-source signals
Assistants do not rely only on your own site. They compare signals across sources. Your website says you are board-certified. Does your CMCPER directory listing confirm it? Does your Doctoralia profile match? Do patient reviews on Google mention your name and specialty consistently?
Backlinks and mentions still matter, but not for exactly the same reason as in classic SEO. In GEO, a mention in an independent source validates your entity.
One pattern we see that hurts clinics: inactive RealSelf profiles with outdated information. They will often treat both as part of the same entity mess.
The cross-specialty pipeline
This is where most generic GEO advice falls apart, because multi-specialty clinics in Tijuana have handoff problems most guides ignore.
Many bariatric patients lose a substantial amount of weight over the first 12 to 18 months, though the range varies by case. Then they need body contouring. If your clinic offers both bariatric and plastic surgery, this can become a highly predictable internal referral opportunity.
But in most clinics, the bariatric department and the plastic surgery department exist as separate digital entities. Separate pages, separate schema, no cross-references.
And this is not only technical. Data isolation does not only happen on personal phones. It happens between departments too. In some clinics, bariatric coordinators do not want to hand off patients to plastic surgery once the bariatric case is already closed. "That patient is mine." Even though the patient now needs a service the bariatric coordinator does not handle. They operate in separate CRMs, track separate metrics, sometimes report to different directors. Nobody tracks the 12-to-18-month biological window. Nobody sends a reminder. The patient searches alone, in ChatGPT, and your clinic does not show up as connected.
We saw this play out in real time at one clinic. A bariatric patient who had her sleeve gastrectomy 14 months earlier started asking her bariatric coordinator about body contouring. The coordinator told her "we do not do that here" because in her mind, her department did not. The clinic absolutely did offer body contouring through its plastic surgery department, two floors up in the same building. The patient went to ChatGPT, searched for "body contouring after weight loss Tijuana," and booked with a competitor. The clinic lost a $7,000 procedure because the CRM did not connect departments and the coordinator had no incentive or mechanism to make the referral.
The fix is both technical and operational. On the technical side, your website and schema need to show the connection between specialties. A bariatric procedure page should link to the body contouring page. The schema should declare that the same organization offers both services. On the operational side, someone needs to own the handoff. That means CRM tags that flag bariatric patients at 10, 14, and 18 months post-surgery. It means an automated email or WhatsApp sequence that introduces the plastic surgery department. It means the bariatric coordinator gets credit (or at least does not lose credit) when a patient converts in another department. Without that incentive alignment, no amount of digital infrastructure fixes the problem.
When we build this pipeline digitally, the content layer matters too. A blog post titled "What to expect 12 months after gastric sleeve surgery" that naturally discusses body contouring options is not a sales pitch. It is the kind of content that both the patient and the AI find useful. It answers a real question, it connects the two specialties, and it gives the AI a reason to surface your clinic when someone searches for post-bariatric body contouring.
Why this matters financially
In accounts we have reviewed, CPCs for Tijuana medical tourism keywords have often landed in the $8 to $28 range. In one representative account, roughly $2,800 in monthly spend produced 11 leads and 1 to 2 closed surgeries. Cost per closed surgery: $1,400 to $2,800. On a mommy makeover generating $8,000 in revenue, that is 17 to 35% of gross income going to acquisition alone. Before OR costs, anesthesia, implants, hospital fees, and staff.
In some procedures we have reviewed, net margin after acquisition ends up under 20%.
Let me put the gross margin math in concrete terms. A mommy makeover that brings in $8,000 in revenue has real costs before the surgeon sees profit. Hospital and OR fees: roughly $1,200 to $1,800 depending on the facility. Anesthesia: $400 to $600. Implants (if breast augmentation is included): $800 to $1,200. Post-op garments, medications, supplies: $200 to $400. Staff and coordinator time: $300 to $500. If acquisition cost is another $1,400 to $2,800, the surgeon is looking at $4,300 to $7,300 in total costs on an $8,000 procedure. That leaves $700 to $3,700 in gross profit, and the lower end of that range is not sustainable.
Facebook and Instagram generate volume at lower CPC but conversion tends to be poor. We documented one case: 127 leads, 2 surgeries. The coordinator spent 3 weeks chasing 80 conversations that went nowhere. That coordinator chase is not free either. The labor cost of following up with 80 dead-end conversations is real. In one clinic we audited, the coordinator was spending roughly 4 hours per day on WhatsApp follow-ups with leads that never converted. That is half a full-time salary spent on conversations that produce nothing. When we calculated the fully loaded cost per closed surgery including coordinator time, the number jumped from $1,867 to over $2,400.
Facilitator commissions often land in the 15 to 25% range, though terms vary. If one broker provides most of your volume, you are carrying concentration risk. We have seen cases where a broker switched preferred clinic and roughly 40% of the pipeline disappeared within a month.
The AI visibility channel has a fundamentally different cost structure. There is no cost per click. There is no cost per impression. There is no facilitator commission. There is an upfront investment in entity cleanup, content creation, and schema implementation. There is ongoing maintenance: updating procedure pages, responding to reviews, monitoring AI mentions, keeping credentials current. But the marginal cost of one more AI mention is zero. The marginal cost of one more patient who finds you through ChatGPT instead of a $15 click is zero. Over time, that cost structure advantage compounds. The clinics that build this channel now will have lower acquisition costs per patient than the clinics still relying entirely on paid traffic. That is the financial case.
Once the asset exists, you are no longer paying for every visit the way you are in ads. The gains come from repeated cleanup and maintenance, not one big launch. Some agency fee structures create bad incentives here.
The implementation order
Phase 1: Entity audit (weeks 1 to 3). Verify name, address, phone, specialty, and credentials are identical across your website, GBP, Doctoralia, RealSelf, and hospital directories. Check for duplicate practitioner listings (search your name on Google Maps; you might be surprised). Search your doctor's name in quotes on Google. Search the clinic name in quotes. Look at what comes back. You will likely find listings you did not create, directory entries with old information, and at least one platform where the name format is wrong. Document everything in a spreadsheet before you change anything. The audit is the foundation. If you skip it or do it partially, every phase after it will be built on bad data.
A note on webmasters. If your current webmaster does not know what MedicalBusiness schema is, you need someone who does. This is not web design work. It is data structuring. We have seen well-intentioned webmasters implement schema incorrectly, which is worse than having no schema at all. A Physician schema that declares the wrong specialty or links to the wrong profiles creates entity confusion that actively hurts your visibility. If your webmaster says "I will Google it and figure it out," that is a red flag. You want someone who has implemented medical schema before and knows the difference between MedicalBusiness, MedicalClinic, Physician, and MedicalOrganization.
Phase 2: Schema and credential publishing (weeks 3 to 6). Implement MedicalBusiness, Physician, and FAQPage schema. Add sameAs properties linking all your profiles. Publish board certifications, medical license numbers, and hospital affiliations in structured format. If your cedula number on your website does not match your Doctoralia profile, fix it now. The sameAs property is especially important because it is how the AI connects your different profiles into a single entity. Without it, your GBP profile, your Doctoralia listing, and your website might be treated as three separate entities instead of one verified practitioner.
Phase 3: Content and review optimization (weeks 5 to 10). Create or update procedure pages with full detail and MedicalProcedure schema. Implement a review solicitation flow: "Would you share your experience with us?" Not: "Please mention your procedure and results." Respond to all pending Google reviews within 48 hours.
On pricing: yes, you will need to negotiate this with the medical director. Publishing ranges gives assistants something concrete to use in cost-related answers. Hiding pricing usually leaves you out.
Phase 4: Measurement (ongoing from week 6). Query ChatGPT, Gemini, and Perplexity weekly with your top 5 specialty queries. Document who appears and who does not. Track Citation Share over time. This has to be maintained like reviews, profiles, and ad accounts.
Frequently Asked Questions
Does GEO replace SEO?
They overlap, but they are solving for different outputs. BrightEdge data shows that many AI citations come from pages outside the organic top 10, so SEO performance alone is a poor predictor of AI visibility. Run both, but recognize they have different mechanics. SEO optimizes for ranking position and organic click-through. GEO optimizes for entity clarity and citation probability. A page can rank #1 on Google and never be cited by ChatGPT if it lacks structured data, consistent entity signals, and extractable specifics. The reverse is also true: we have seen pages ranking on page 2 of Google appear in AI answers because they had clean schema and concrete procedure data the AI could use.
How long until we appear in ChatGPT?
No guarantee. What you can control is the clarity of your signals and how quickly you fix inconsistencies. In some clinics we have worked with, initial mentions started appearing within roughly 8 to 12 weeks after a full audit. We have also seen clinics still invisible at 4 months. In our experience, one common difference is whether the doctor actually publishes pricing and credentials instead of delaying the decision. The clinics that move fastest tend to be the ones where the medical director is involved in the process from week one. When the pricing decision, the credential publishing, and the name standardization all require separate approvals from someone who is in surgery all day, the timeline stretches. When the medical director understands why this matters and delegates authority to execute, things move faster.
What about competitors already doing this?
There is still room because execution is weak in this market. The earlier clinics clean this up, the less backlog they carry later. In our most recent round of audits, the majority of clinics in Zona Rio had not even started. The few that had started were mostly doing partial implementations: schema on the homepage but not on procedure pages, or consistent naming on GBP and the website but not on Doctoralia and RealSelf. Complete implementations across all platforms and all doctors are still rare. That will change. But right now, a clinic that does this fully and correctly has a meaningful advantage.
Dental clinics too?
The logic is similar, but the numbers change. In dental, we usually see lower CPCs and lower ticket sizes. Competition is more fragmented. The GEO principles apply equally, but the ROI math is tighter, which makes organic AI visibility even more valuable relative to paid channels.
Should we fire our marketing agency?
Ask them five questions first. Do they measure cost per closed surgery? Do they know your Citation Share? Can they explain your entity architecture? Do they separate brand from generic campaigns? Do they know what GEO is? If they cannot answer most of these, that tells you whether they are equipped for where patient acquisition is going.
Who owns this project inside the clinic?
This is a common sticking point. The marketing coordinator usually does not have the authority to publish pricing, standardize the surgeon's name across platforms, or change GBP categories. The medical director usually does not have the time or interest to manage digital infrastructure. The webmaster can implement schema but cannot make clinical or business decisions about what to publish. The answer is that this needs a project owner who has access to the medical director and authority to make decisions on behalf of the clinic's digital presence. In some clinics, that is the operations director. In others, it is an external partner with a clear scope of work. What does not work is assigning it to the marketing coordinator and expecting them to negotiate pricing publication with a surgeon who outranks them. That conversation stalls every time.
Do the check yourself first. Open ChatGPT, Gemini, and Google in incognito. Set location to San Diego or Phoenix. Search your main procedure in Tijuana. Document who appears, with what sources, and with what consistency. That is your baseline.