Delhi NCR Healthcare Search Report 2026

Methodology

Two first-party aggregate datasets underpin this report. Neither surfaces individual business names, addresses, phone numbers, or doctor identities — categorical and geographic aggregates only.

Dataset A — Google Business Profile portfolio (N = 201 healthcare listings). An anonymised roll-up of 104 distinct category-by-city cells covering Delhi (99 listings), Gurgaon (77), Noida (18), Faridabad (6) and Ghaziabad (1). Each cell records the count of active listings, the count of suspended listings, and category-level averages for three composite scores: GBP health (a 0-100 composite of completeness, review velocity, response rate, Q&A depth, post cadence and NAP consistency), rank operating-system score (a 0-100 composite of geo-grid presence, category presence and 3-pack surface area) and AI Overview citation score (a 0-15 composite that scores whether the listing is being referenced by AI-generated search summaries on branded and specialty queries).

Dataset B — Google Search Console query aggregate (N = 300 unique queries, 212,692 impressions). A rolled-up view of Delhi NCR healthcare queries drawn from Search Console properties over January-August 2026. Each row carries clicks, impressions, average position, aggregate CTR, and the number of distinct properties the query attracted. Queries were classified programmatically into intent buckets (branded / navigational, "best" comparison, cost, treatment, jobs, generic-specialty) and matched to specialty families (dermatology, mental health, ENT, fertility/IVF, hair transplant, plastic surgery, cosmetology, dental, urology, ophthalmology, gynaecology, oncology, endocrinology, physiotherapy, wellness, nutrition) via a keyword-map.

Anonymisation. Every stat published in this report is a category × city aggregate or an intent × specialty aggregate. Individual query strings, individual GBP names, doctor names, addresses and phone numbers are held on the working copy only and never rendered. Query intent classification is deterministic and reproducible from the source CSV.

What this report is not. This is a search-behavior and GBP-performance report, not a marketing spend or CPQL benchmark. Media spend, ROAS and lead-cost figures live in the sibling State of Healthcare Marketing India 2026 flagship. This report answers a different question: where does Delhi NCR healthcare demand actually sit — by city, by specialty, by intent — and how well is the current GBP inventory built to catch it?

1. Noida is the healthiest GBP city in NCR — and Gurgaon is the weakest

Average GBP health score by NCR city: Noida 79.9, Delhi 73.8, Faridabad 72.7, Gurgaon 70.0. Noida also leads on AI Overview citation score at 7.28 (versus Gurgaon at 4.66) and on rank operating-system score at 56.7 (versus Gurgaon at 45.3).

The reading counterintuitive at first — Gurgaon carries the biggest gross healthcare economy in NCR — but the pattern is consistent across every metric. Gurgaon has 77 sampled listings (second-largest city block) and posts the weakest averages. Noida has fewer listings but tighter GBP hygiene: category selection, review response cadence, Q&A depth, post recency, and — most importantly — schema markers that let AI Overview crawlers identify the entity.

Implication for healthcare marketers. A Gurgaon clinic on the median is competing against a citywide GBP field that is 10 percent behind Noida on health and 56 percent behind on AIO score. That is a headroom advantage for any Gurgaon operator willing to run the GBP layer with discipline; it is not a "saturated market". The Noida operators are the ones who should be worried — the ceiling is closer.

2. Dermatology owns the most GBP inventory in NCR — and the worst performance

Dermatology accounts for 21 healthcare GBPs across Delhi + Gurgaon (the largest specialty block in the dataset), yet posts an average GBP health of 58.3 — the lowest of any specialty with more than three listings. Its AI Overview citation score of 4.14 is also the lowest of any high-volume category.

Categories with fewer than 4 listings excluded. Data source: internal aggregate roll-up, January-August 2026.

The dermatology contradiction runs through every NCR city cell: 10 dermatology listings in Delhi (health 60.4, AIO 3.7), 6 in Gurgaon (health 51.7, AIO 3.5), 5 in "Delhi" with the lowercase spelling (health 62.0, AIO 5.8). The pattern is not one bad clinic — it is a category norm. Dermatology in Delhi NCR is running like a first-cohort GBP category that never got operationalised properly. Everyone claimed the pin; almost nobody built the listing.

Compare urology. Just 5 GBPs in the sample, health 92.4, AIO 11.62, rank OS 67. Urology in NCR looks like a category that a small number of operators are running seriously — full service catalogue, structured Q&A, weekly posts, review discipline, complete schema. Same city, same platform, same NMC constraint — different operating temperature.

Implication for healthcare marketers. Dermatology in NCR is the most contested category by GBP count and the least contested by GBP quality. A dermatologist entering Delhi or Gurgaon in Q4 2026 can leapfrog the entire median field with 90 days of disciplined GBP work — before spending a single rupee on Meta or Google Ads.

3. Position 1-3 pulls 13x the CTR of positions 11-20 on NCR healthcare queries

Aggregate click-through rate at positions 1-3 is 10.66 percent versus 0.81 percent at positions 11-20 — a 13.1x drop over ten position points. On the 106,303 impressions that fell into the 11-20 band, healthcare properties captured only 858 clicks. Positions 21 and below add another 8,633 impressions for 95 clicks (1.10 percent CTR).

The shape is unforgiving. Half the impressions in the dataset (106,303 of 212,692) land in the 11-20 band — the "second page" where CTR collapses under 1 percent. Only a quarter of impressions (27,202) reach the top-3 band that carries most of the click yield.

Implication for healthcare marketers. Ranking at position 4-10 is not "close enough" — it captures roughly one-fifth the click share of positions 1-3 on the same query. On a Delhi dermatology query with 5,000 monthly impressions, a top-3 result harvests 533 clicks, a page-two result harvests 40. That is the difference between an SEO programme that pays for itself and one that produces nothing but a report. The margin between ranking and not ranking, in this dataset, is not 3x — it is 13x.

4. Branded/navigational queries convert at 17.59 percent CTR — nine times the generic-specialty rate

Sixty of the 300 aggregate queries in the dataset are branded or high-recall navigational (defined as average position ≤ 2.0, CTR ≥ 10 percent, and impressions ≤ 3,000). They pulled 1,503 clicks on 8,545 impressions — an aggregate CTR of 17.59 percent. By contrast the 75 generic-specialty queries (dermatologist gurgaon-shape phrases, without a brand token) pulled 1,044 clicks on 114,584 impressions — 0.91 percent CTR aggregate.

That is a 19x CTR ratio between brand-recall demand and cold specialty demand. The click yield per brand-recall query (25 clicks per query on average) is nearly two orders of magnitude higher than the click yield per cold specialty query (14 clicks per query on 1,528 impressions per query).

Bucket definitions are non-exclusive; a "best dermatologist in delhi" query is both "best" and "generic specialty".

Implication for healthcare marketers. Brand-recall demand is where NCR healthcare click-yield actually lives — but you can only harvest it if you built the brand asset first. Operators without brand-recall demand are competing on a query base that yields sub-1 percent CTR at scale, and on which the top-3 position gap decides all click yield. The strategic split is unambiguous: (a) build the brand asset that turns 8,545 impressions into 1,503 clicks; (b) simultaneously build the technical and content depth that lets you appear in the top-3 on the 168,527 impressions of "best" and generic-specialty demand.

5. Mental Health and Dermatology own the impression pool — but click yield sits elsewhere

Mental Health (65 aggregate queries, 60,207 impressions, 1.70 percent CTR) is the largest specialty by impression share in the NCR dataset, followed by Dermatology (34 queries, 52,082 impressions, 0.85 percent CTR) and ENT (68 queries, 29,668 impressions, 3.49 percent CTR). Between them, these three specialties account for 66 percent of aggregate healthcare impressions in the sample.

But click yield is not proportional. On aggregate CTR:

• Wellness posts 20.44 percent CTR (small n = 2 queries, 367 impressions — but sharp brand-recall demand)
• Ophthalmology posts 12.76 percent CTR (6 queries, 1,301 impressions, 166 clicks)
• Nutrition posts 5.67 percent CTR (2 queries, 335 impressions, 19 clicks)
• ENT posts 3.49 percent CTR (68 queries, 29,668 impressions — best CTR-at-scale in the dataset)
• Cosmetology (Botox, filler, laser, tattoo removal) posts 2.99 percent CTR
• Dental posts 2.78 percent CTR
• Fertility/IVF posts 2.46 percent CTR — despite carrying 11,824 impressions

Implication for healthcare marketers. Mental Health and Dermatology are impression-rich but CTR-thin — a large opportunity for any operator willing to earn top-3 real estate. ENT is the standout on click-yield at scale (29,668 impressions × 3.49 percent CTR = 1,035 clicks captured on the aggregate). If you are picking a specialty to invest an SEO retainer against on pure demand economics, ENT and Cosmetology carry the best combination of impression pool and CTR conversion in the NCR sample.

6. Zero suspensions across 201 healthcare GBPs — the platform is not the risk

Across the 201-listing sample and the 8-month coverage window, suspension count was zero. Every GBP in the dataset was active on read date. Given the healthcare category is one of the more suspension-sensitive verticals on Google Business Profile globally (medical device, weight-loss, aesthetic-procedure and rehab categories all carry elevated risk), a zero-suspension rate across a portfolio of this size is a signal that the compliance layer — NMC Section 6 language discipline, DPDP consent workflows, and category selection hygiene — is being observed in the NCR operator base.

Implication for healthcare marketers. The "GBP is too risky" argument does not fit this dataset. Suspension risk is a real operational discipline problem, not a platform accident. The four hard rules — no cure claims in posts, no patient testimonials in Q&A, category selection matches primary service, verified NAP across every citation — are enough to keep a healthcare GBP live at scale. The operators posting a 90+ health score are the ones running these rules as a workflow, not an afterthought.

7. City-tagged queries beat "NCR"-tagged queries on click yield 8:1

Delhi-tagged queries (158 aggregate) pulled 2,373 clicks. Gurgaon-tagged (83) pulled 1,667. Noida-tagged (37) pulled 1,093. Faridabad-tagged (9) pulled 228. Meanwhile queries containing the token "NCR" (14 queries) pulled just 102 clicks — a ~23x gap versus Delhi-tagged demand.

Two things worth noticing. First, patients tag by city, not by region — "psychiatrist delhi" and "dermatologist gurgaon" are the phrasing shape, not "psychiatrist ncr" or "dermatologist delhi ncr". A GBP or a landing page that leads with "NCR" is speaking a language patients are not searching in.

Second, the smaller cities (Noida, Faridabad, Ghaziabad) carry meaningfully higher aggregate CTRs and better impression-weighted positions than Delhi or Gurgaon — precisely because the local competition density is lower. Noida's 5.14 percent aggregate CTR at impression-weighted position 6.48 is a materially better healthcare search economy per query than Delhi's 2.27 percent at position 11.90.

Implication for healthcare marketers. The city-specific content and GBP infrastructure needs to be built at the city level, not the "NCR" level. A single "Delhi NCR" landing page will underperform three per-city landing pages (Delhi, Gurgaon, Noida) both on schema clarity and on user-query match. GBP service-area configuration follows the same rule.

8. Cost queries are small in count but disproportionately high-intent

Only 13 of the 300 queries in the dataset carry a cost/price/fee token — but between them they attracted 6,826 impressions and 210 clicks (3.08 percent aggregate CTR). Per-query impression yield on cost queries (525 impressions per query) is 3x the dataset average (709 impressions per query — but heavily skewed by a few high-impression queries; the median query attracts ~50 impressions).

Treatment queries (70 of them — rhinoplasty, hair transplant, tattoo removal, botox, laser, braces, etc.) carry a similarly high yield: 38,097 impressions and 1,016 clicks at 2.67 percent CTR. Treatment + cost phrasing (e.g. "rhinoplasty cost in delhi", "braces cost in delhi") sits at the intersection and typically outperforms both parents.

Implication for healthcare marketers. Cost and treatment queries are the highest-yield content targets in NCR healthcare search. They are also the queries where NMC and ASCI compliance is most brittle — cost pages must be built as informational and educational, not as offer or promotional pages, and treatment pages must be framed around the procedure, not the outcome. The compliance-safe version of a Delhi rhinoplasty cost page (procedure explanation, cost drivers, comparative cost brackets, aftercare, decision framework) is also the version that ranks and converts.

What this means for healthcare marketers

Frequently asked questions