#1 moment for ‘바나나우유’: "달콤한 간식이 필요할 때" 88.5%

01At a glance

99,649

Monthly situation search volume

4

CEPs

4

Unclaimed situations

88.5%

Largest CEP share · 달콤한 간식이 필요할 때

Start here

1달콤한 간식이 필요할 때Unclaimed situation volume 88,234No brand shows up in this big situation yet → plant content & ads on its search terms first
2아침 출근길에 간편하게 에너지를 보충하고 싶을 때Unclaimed situation volume 6,673Low search volume → deprioritize for now (start with the big situations above)
3공부할 때 집중력을 높이고 싶을 때Unclaimed situation volume 1,656Low search volume → deprioritize for now (start with the big situations above)

Unclaimed situation = a CEP where no brand was detected in its journeys or SERPs · Unclaimed situation volume = situation volume × (1 − brand fit). Situation volume is a proxy for how often the moment happens, not the volume of category-name searches

02Decision summary

what to do first

Priority	Entry situation (CEP)	Power	Unclaimed situation volume	Brand competition	Next action
1	달콤한 간식이 필요할 때	88.5%	88,234	unclaimed	No brand shows up in this big situation yet → plant content & ads on its search terms first evidence weak
2	아침 출근길에 간편하게 에너지를 보충하고 싶을 때	6.7%	6,673	unclaimed	Low search volume → deprioritize for now (start with the big situations above) evidence medium
3	공부할 때 집중력을 높이고 싶을 때	1.7%	1,656	unclaimed	Low search volume → deprioritize for now (start with the big situations above) evidence medium
4	아이 간식으로 적합한 것을 찾을 때	3.1%	3,086	unclaimed	Low search volume → deprioritize for now (start with the big situations above) evidence weak

Click a column header to sort by it · click a CEP name to jump to its detail card

Power = this situation's share of all CEP situation searches (bigger = wider door in) · Brand competition = whether brands show up in this situation's journeys/SERPs · Evidence = strength of the supporting search evidence (strong/medium/weak)

03CEP occurrence over timederived

when it grew and when it fell

Total entry demand (all CEPs)YoY (12M)-6%Last 3M YoY-5%Peak–48 months · CEP 4stablenon-seasonal

Click a row to switch the chart above to that CEP. Click the same row again, or the top row, to return to the total.

CEP	YoY (12M)	Last 3M YoY	Peak		queries
Total entry demand (all CEPs)	-6%	-5%	–	stablenon-seasonal
달콤한 간식 필요할↗	-3%	-3%	–	stablenon-seasonal	4/4
아침 출근길↗	-22%	-19%	–	decliningnon-seasonal	2/2
공부 간식↗	-25%	-32%	3·4	decliningseasonal	3/3
아이 간식 적합한↗	-22%	-16%	4·10	decliningseasonal	2/2

Peak calendar: CEP × calendar-month index

	1	2	3	4	5	6	7	8	9	10	11	12
달콤한 간식 필요할	1.1	0.9	1.0	1.0	1.1	0.9	1.0	1.0	1.0	1.0	1.0	1.0
아침 출근길	1.0	1.0	1.3	1.1	1.0	1.0	0.9	1.0	1.1	1.0	0.9	0.8
공부 간식	0.8	0.6	1.3	1.7	0.7	1.3	0.7	0.8	1.1	1.2	1.1	0.6
아이 간식 적합한	0.8	0.7	1.2	1.5	1.1	0.9	0.8	0.8	1.1	1.3	0.9	0.8

Cell = that month's average volume ÷ overall monthly average (1.0 = average). Bold = peak month.

Monthly search volume per situation over 48 measured months: when and how often each situation occurs. Combined with survey data, it shows both the size of a situation and how it changes.

Rule: growing/declining = trailing 12-month sum vs the prior 12 months ±20% or more / peak month = calendar-month index ≥1.30 / seasonal = max ÷ min month index ≥1.8. Monthly values are measured monthly search volumes [measured]; CEP series are sums over measured measured queries [derived]. Unlike survey CEP power (share of respondents), this frequency is search occurrence.

04Competitive structurederived

fixed leaders, contested and open situations

fixed leader (0)

–

contested (0)

–

dispersed (0)

–

open (4)

달콤한 간식 필요할 88.5%
아침 출근길 6.7%
아이 간식 적합한 3.1%
공부 간식 1.7%

Open has two kinds: measured with no brand mentions is a claim candidate; unmeasured needs a deep run or survey before claiming. · Contested = gap between #1 and #2 ≤10pt · dispersed = leader share <35% · HHI = sum of squared shares. Core CEPs (power ≥ median) are filled, others faded. Unmeasured are dashed (unknown, not empty).

05CEP power

each situation's share of all situation searches

total 4 CEP · [derived] power = the CEP's search volume ÷ total volume of all CEPs

06Brand × entry situation

claimed vs. open (all CEPs)

Brand links measured for 0 of 4 entry situations · the other 4 are graded as opportunities. Small k/m in a cell = brand-mention sample (small m = low confidence).

	Brand link
달콤한 간식 필요할88.5%	Big land-grab: large unclaimed situation 88.5% · mo. 88,234
아침 출근길6.7%	Land-grab: unclaimed 6.7% · mo. 6,673
아이 간식 적합한3.1%	Land-grab: unclaimed 3.1% · mo. 3,086
공부 간식1.7%	Small situation: low priority 1.7% · mo. 1,656

[derived] · colored cell = measured share (k/m sample) · green/amber row = land-grab opportunity (no brand linked, by situation size) · gray row = small · "·" = not queried (no data ≠ 0)

Discovered category brands (unlinked): 가나디, 빙그레, 덴마크, 서울우유, 상하목장, 푸르밀, 칸타타, 미노스, 이도온화, 산가 리아

Brand counting basis: direct brand-name mentions (no product-name mapping).

07Category link rate on search pathsderived

does the situation lead to the category next

달콤한 간식 필요할 88.5% category-growth candidatelink rate 0% · low · 0/200 paths

Link rate = share of search paths through this situation whose later queries contain a category term (바나나우유) [derived]. low <20% · high ≥50%. Power ≥ median and low = category-growth candidate (the situation is big but the category is not chosen yet). Only journeys starting from the situation term are used; the category-anchor journey is excluded (linked by construction). CEPs whose own queries already contain the category term are skipped.

08W-axis mixassumption

where this map's situations cluster

Why · purpose/benefit2 CEPs · power sum 8%

Who · for whom0 CEPs · power sum 0%

When · timing/trigger0 CEPs · power sum 0%

Where · place0 CEPs · power sum 0%

While · doing what0 CEPs · power sum 0%

With whom0 CEPs · power sum 0%

Feeling · mood0 CEPs · power sum 0%

BEP (benefit entry points): 0 / 4

Empty axes: Who · for whom, When · timing/trigger, Where · place, While · doing what, With whom, Feeling · mood. This is where a candidate list may be trapped in the designer's hypotheses; add entry-situation candidates on these axes in the next run's review step.

The W-axis shows the angle each CEP arises from (why, for whom, when, where, while doing what, with whom, feeling) [assumption]; when scene-7W evidence exists, the most populated axis is used [derived]. BEP = entries where the desired outcome comes first, like why or feeling.

09Searcher profilemeasured

age and gender by situation

	13-19	20-24	25-29	30s	40s	50+	Gender split
달콤한 간식 필요할	14	16	15	25	21	10	F 74%
아침 출근길	1	5	14	39	31	11	F 69%
공부 간식	6	4	4	4	52	30	F 89%
아이 간식 적합한	0	1	2	47	44	5	F 85%

lowhighEach cell is that age band's share (%) of the CEP's searchers

10Audience in the query

Who it is for

Only searches that name an audience (the recipient, companion or user) are counted, and their monthly volume summed. It reads who people search for, and with whom, straight from the queries.

Audience	Top queries	CEP	Monthly volume
Kids 아이	아이 간식	아이 간식으로 적합한 것을 찾을 때	2,803
Students 수험생	수험생 간식	공부할 때 집중력을 높이고 싶을 때	910
Pets 강아지	강아지 바나나우유		87
Babies 아기	아기 바나나우유		82

Measured queries × fixed lexicon classification [derived]. A query naming two audiences counts in both.

11Evidence grade

What the qualitative attributes rest on

Nano intents, KBFs, constraints, avoidances, thresholds and reasons to believe carry one of four labels. Measured means the condition exists as real search queries with measured monthly volume. Consensus means Google's SERP and AI Overview state the same thing across several queries. A SERP is ranked and summarized from the click feedback of the people who searched that query, so content that repeats across queries and independent sources is read as what that society agrees on about the topic.

measured 25%assumption 75%

measured2 · exists as search queries, monthly volume measured

consensus0 · repeated in SERP/AIO of 2+ queries (or 3 independent sources)

derived0 · found in a single SERP sentence

assumption6 · interpretation without direct evidence

Based on the 8 qualitative attributes in this report; each counts once, at its strongest evidence.

Conditions with measured search demand measured

Condition	CEP	Top queries	Monthly volume	Trend
Alternative커피	아침 출근길에 간편하게 에너지를 보충하고 싶을 때	바나나우유 커피 · 편의점 바나나우유 커피 · 바나나우유 커피 조합	7,028	↓-13%
Alternative초콜릿	공부할 때 집중력을 높이고 싶을 때	초코 바나나우유	221	↑+45%

Sum of monthly volume of measured queries that state the attribute's condition: queries containing its key terms verbatim, or queries that say the condition in other words (condition word checked, passed a separate review). Attributes hitting the same query set are merged. Trend uses 48 months of monthly volume (last 12 vs prior 12 months).

Rising conditions

Alternative초콜릿 ↑+45%

Conditions whose bound queries grew 20% or more, last 12 months vs the prior 12.

12Search data used in this report

A CEP is a situation that many search signals point to together, not a single keyword. This shows how much related-search, search-path, search-cluster, SERP text, PAA and AI Overview data was collected, and which of it served as evidence for each CEP's scene (when, where, why, with whom) and its nano context, KBF, constraints and avoidances.

Data	Collected	Used as CEP evidence
Related searches	250	in the dossiers of 0/4 CEPs
Search paths	696 paths (incl. 0 deep-measurement paths)	in the dossiers of 0/4 CEPs
Search clusters	0 clusters · 0 queries	in the dossiers of 0/4 CEPs
SERPs (Google results)	0	in the dossiers of 0/4 CEPs
AI Overview	0	in the dossiers of 0/4 CEPs
PAA (People also ask)	0	–

Where each CEP showed up

CEPs surface in different places depending on the topic and situation: some in search paths, some in clusters or related searches, some in AIO and PAA. Left: share of the CEP's measured query volume found in each source (discovery). Right: how often each source was cited for the scene 7W and attributes. 'none' means that source never reached this CEP.

CEP	Discovery (volume share)						Cited as evidence (count)
CEP	related searches	search paths	search clusters	AIO	PAA	mined from paths/clusters/AIO	CEP queries	search paths	search clusters	related searches	AIO	PAA	top results
달콤한 간식이 필요할 때	–	93%	–	–	–	–	·	·	·	·	·	·	·
아침 출근길에 간편하게 에너지를 보충하고 싶을 때	–	–	–	–	–	–	·	·	·	·	·	·	·
아이 간식으로 적합한 것을 찾을 때	–	–	–	–	–	–	·	·	·	·	·	·	·

13CEP detail cards

CEP 1purchase CEP

달콤한 간식이 필요할 때

Macroexplicit CEP

power 88.5% derived · avg monthly volume 88,234 · trend (3M) +8%

structure open YoY (12M) -3%stablenon-seasonalcategory link 0%

The situationassumption

일상에서 스트레스를 해소하고 싶거나 출출할 때가 있습니다. 이때 달콤한 간식을 통해 기분 전환을 원하게 됩니다. 사람들은 달콤한 간식이나 디저트를 검색합니다.

Next actionNo brand shows up in this big situation yet → plant content & ads on its search terms first evidence weak

Investment priority derived

Investment candidate #1Unclaimed situation volume up to 88,234/mo

Market size 100 · Brand fit – · Provability 0(evidence thin), highest-priority investment on this 3-axis combination

Combines the 3 selection axes + power/volume via a fixed rule; a new calculation only, no new data

Search journey: just before and after derived

Adjacent transitions aggregated from 200 measured paths; an aggregate graph flow, not one person's timeline

Show 3 evidence blocksHide evidence

Evidence queries measured

디저트 82,326measured스트레스 해소 4,796measured출출할 때 1,013measured달콤한 간식 99measured

Selection axes (market · fit · provability)

Market size100

Brand fit–

Provability0

Searcher profile

Appendix: AI search exposure

AI tracking questions assumption

1“달콤한 간식으로 바나나우유를 찾을 때”existing prompt

2“스트레스 해소를 위해 바나나우유를 고를 때”

Questions this situation's consumers may ask an AI; used to track AI-response exposure

Reference block needed only when managing AI (AI Overview / chatbot) exposure. The blocks above cover situation understanding and marketing decisions.

CEP 2purpose CEP

아침 출근길에 간편하게 에너지를 보충하고 싶을 때

Microexplicit CEP

power 6.7% derived · avg monthly volume 6,673 · trend (3M) +2%

W-axis Whystructure open YoY (12M) -22%decliningnon-seasonal

The situationassumption

출근 준비로 바쁜 아침에 에너지를 보충해야 할 때가 있습니다. 이때 빠르게 에너지를 보충하고 싶고, 간편하게 마실 수 있는 음료를 찾게 됩니다. 출근길에 편의점 음료나 아침 대용을 검색합니다.

Next actionLow search volume → deprioritize for now (start with the big situations above) evidence medium

Investment priority derived

Investment candidate #2Unclaimed situation volume up to 6,673/mo

Market size 8 · Brand fit – · Provability 33, highest-priority investment on this 3-axis combination

Combines the 3 selection axes + power/volume via a fixed rule; a new calculation only, no new data

Scenes: micro-CEPs within this situation

출근 준비로 바쁜 아침에 빠르게 에너지를 보충하고 싶을 때 assumption ‹아침 대용…›6,673 · 100% derived

출근길에 간편하게 마실 수 있는 음료를 찾을 때 assumption ‹아침 대용…›size unmeasured no data

Scene names are [assumption] bonded to quoted evidence · volume is the measured sum of scene-attributed queries [derived] · evidence-less scenes are discarded by code

Message angle assumption

Core message“바쁜 아침 출근길, 간편하게 에너지를 채워 편리하게 하루를 시작하세요.”

Content ideas출근길 5분 에너지 충전 챌린지 · 편의점에서 만나는 나만의 아침 루틴 · 바쁜 아침, 한 손으로 즐기는 간편 에너지 부스터

활기찬간편한실용적인상쾌한

Synthesized from KBF, reasons to believe, emotion & style, and the 6W1H scene

Show 8 evidence blocksHide evidence

Evidence queries measured

아침 대용 3,560measured편의점 음료 3,113measured

Nano intents (fine context)

빠르게 마실 수 있는 음료 ‹아침 대용›assumption

Context (7W)

why: 에너지를 보충하기 위해 assumptionwhen: 아침 출근길 assumptionwhere: 편의점 assumptionwhile: 출근 준비 assumption

KBF (choice criteria)

간편함 ‹편의점 음료›assumption

Emotion & style

편리함 ‹same evidence ↑›assumption

Alternatives (outside category)

커피 ‹search '바나나우유 커피' +10 · 7,028/mo›measured

Selection axes (market · fit · provability)

Market size8

Brand fit–

Provability33

Searcher profile

Appendix: AI search exposure

AI tracking questions assumption

1“아침 출근길에 간편하게 마실 수 있는 음료 추천해줘.”existing prompt

2“출근 준비로 바쁜 아침에 빠르게 에너지를 보충할 방법이 있을까?”

3“편의점에서 아침 대용으로 마실 수 있는 음료가 뭐가 있을까?”

4“아침에 간편하게 마실 수 있는 음료 추천해줘.”

Questions this situation's consumers may ask an AI; used to track AI-response exposure

Reference block needed only when managing AI (AI Overview / chatbot) exposure. The blocks above cover situation understanding and marketing decisions.

CEP 3purpose CEP

공부할 때 집중력을 높이고 싶을 때

Microexplicit CEP

power 1.7% derived · avg monthly volume 1,656 · trend (3M) +13%

W-axis Whystructure open YoY (12M) -25% · Peak 3·4mo.decliningseasonal

The situationassumption

장시간 공부할 때 집중력을 높여야 하는 상황이 생깁니다. 시험 공부 중에 에너지를 보충하고 싶고, 집중력을 높이는 간식을 원하게 됩니다. 이때 공부 간식, 수험생 간식, 또는 시험 간식을 검색합니다.

Next actionLow search volume → deprioritize for now (start with the big situations above) evidence medium

Investment priority derived

Investment candidate #3Unclaimed situation volume up to 1,656/mo

Market size 2 · Brand fit – · Provability 33, highest-priority investment on this 3-axis combination

Combines the 3 selection axes + power/volume via a fixed rule; a new calculation only, no new data

Scenes: micro-CEPs within this situation

시험 공부 중에 집중력을 높이고 싶을 때 assumption ‹공부 간식…›1,316 · 80% derived

장시간 공부할 때 에너지를 보충하고 싶을 때 assumption ‹공부 간식…›size unmeasured no data

Scene names are [assumption] bonded to quoted evidence · volume is the measured sum of scene-attributed queries [derived] · evidence-less scenes are discarded by code

Message angle assumption

Core message“공부할 때 흐트러진 집중력을 다시 잡아, 몰입의 순간을 경험하세요.”

Content ideas집중력 UP! 스터디 메이트 간식 · 시험 기간 필수템, 집중력을 깨우는 한 입 · 나만의 집중존, 방해받지 않는 몰입의 시간

차분한몰입하는명료한생산적인

Synthesized from KBF, reasons to believe, emotion & style, and the 6W1H scene

Show 8 evidence blocksHide evidence

Evidence queries measured

수험생 간식 910measured공부 간식 406measured시험 간식 340measured

Nano intents (fine context)

집중력을 높이는 간식 ‹공부 간식›assumption

Context (7W)

why: 집중력을 높이기 위해 assumptionwhen: 공부할 때 assumptionwhile: 공부 assumptionfeeling: 집중 assumption

KBF (choice criteria)

집중력 강화 ‹수험생 간식›assumption

Emotion & style

집중 ‹same evidence ↑›assumption

Alternatives (outside category)

초콜릿 ‹search '초코 바나나우유' · 221/mo›measured

Selection axes (market · fit · provability)

Market size2

Brand fit–

Provability33

Searcher profile

Appendix: AI search exposure

AI tracking questions assumption

1“공부할 때 집중력을 높일 수 있는 간식 추천해줘.”existing prompt

2“시험 공부 중에 에너지를 보충할 수 있는 간식이 뭐가 있을까?”

3“장시간 공부할 때 도움이 되는 간식 추천해줘.”

4“집중력을 높이는 간식이 필요해.”

Questions this situation's consumers may ask an AI; used to track AI-response exposure

Reference block needed only when managing AI (AI Overview / chatbot) exposure. The blocks above cover situation understanding and marketing decisions.

CEP 4purchase CEP

아이 간식으로 적합한 것을 찾을 때

Macroexplicit CEP

power 3.1% derived · avg monthly volume 3,086 · trend (3M) -5%

structure open YoY (12M) -22% · Peak 4·10mo.decliningseasonal

The situationassumption

아이에게 줄 간식을 준비해야 할 때가 있습니다. 특히 소풍 간식처럼 아이에게 적합한 간식을 찾게 됩니다. 이때 아이 간식이나 소풍 간식을 검색합니다.

Next actionLow search volume → deprioritize for now (start with the big situations above) evidence weak

Investment priority derived

Investment candidate #4Unclaimed situation volume up to 3,086/mo

Market size 4 · Brand fit – · Provability 0(evidence thin), highest-priority investment on this 3-axis combination

Combines the 3 selection axes + power/volume via a fixed rule; a new calculation only, no new data

Show 3 evidence blocksHide evidence

Evidence queries measured

아이 간식 2,803measured소풍 간식 283measured

Selection axes (market · fit · provability)

Market size4

Brand fit–

Provability0

Searcher profile

Appendix: AI search exposure

AI tracking questions assumption

1“아이 간식으로 바나나우유를 찾을 때”existing prompt

2“소풍 간식으로 바나나우유를 고를 때”

Questions this situation's consumers may ask an AI; used to track AI-response exposure

Reference block needed only when managing AI (AI Overview / chatbot) exposure. The blocks above cover situation understanding and marketing decisions.

14Brand summary

behavioral MMS proxy · width×depth

	MMS proxy [derived]	branded volume [measured]	depth (avg rank)
가나디	–	169,170	–
빙그레	–	75,733	–
덴마크	–	70,276	–
서울우유	–	45,386	–
상하목장	–	24,773	–
푸르밀	–	15,186	–
칸타타	–	9,446	–
미노스	–	2,590	–
이도온화	–	2,490	–
산가 리아	–	–	–

15Limits

what this map does not say

Any brand share / response-priority judgment ("how a brand is doing") holds only where brand linkage was actually measured for that CEP; check the measured ratio in Evidence readiness just below. Where many CEPs are unmeasured, treat brand-related conclusions as provisional.
Search reflects familiarity and purchase-consideration more strongly than unaided recall; in person-level validation, recognition alone drove search only 1.22x (near-negligible), while familiarity/consideration were clearly larger, reaching 7.0x (smartphones) / 5.3x (autos) when all 5 positive brand attitudes were held (Dotson et al., Google). This correlation is confounded by brand size (bigger brands move on many metrics at once), and validation was done at brand-total level.
Existing/habitual buyers don't disappear from search; the same study found brand owners searched their brand 2.5-3.5x more than non-owners (Dotson et al., Google). But much of that is non-need-expressing (brand-name/navigational/support queries), so this map's need-type CEP distribution skews toward new-entry/switch-consideration demand.
Brand share is relative within the measured set; an unqueried brand x CEP pair is [no data], not zero.
Paths are aggregate graph flow, not one person's timeline; "transition" is a modeled statistic.
CEP power's denominator is classified queries, not people; it isn't directly comparable to survey-based CEP power (denominator = people); the same person's 10 queries count as 10 votes on this map.
Queries that pick by naming a brand/origin are closer to a search mode than a situation, and differ in kind from other CEPs - they're bucketed separately to avoid contaminating need-type CEPs, so when counting "number of entry situations," we recommend excluding this item and the unclassified long tail.
Before decisions like budget/resource allocation, we recommend pairing this with survey-based recall measurement (person-level CEP power / share of mind).
The code discarded 12 AI-suggested item(s) lacking evidence (evidence is enforced).
Of 8 qualitative attributes: 2 measured (25%), 0 consensus (0%), 0 derived, 6 assumption. Measured means the condition exists as search queries, not that it drives purchase. Consensus is the social common sense Google has organized, not a fact check.

Evidence readiness: partial · 4 of 4 CEPs have measured search queries, brand linkage measured for 0; the rest need the co-query matrix / trigger expansion (deep run)

16Reproducibility

Search volume lookup 7 · Search paths 3 · Related searches 1 · AI synthesis 1

Data retrieval detail

Connector calls	Parameters	Credits spent
Related searches	바나나우유 +3 / kr / limit 250	620
Search paths	바나나우유 / kr / limit 300	6650
Search volume lookup	12 / kr	12
Search volume lookup	8 / kr	8
Search paths	디저트 / kr / limit 200	5570
Search paths	간식 / kr / limit 200	6810
Search volume lookup	267 / kr	267
Search volume lookup	80 / kr	80
Search volume lookup	10 / kr	10
Search volume lookup	4 / kr / all	40
Search volume lookup	14 / kr	14
AI synthesis	gemini-2.5-flash (S0 grounded + S3 synthesis)	0

Credits spent: 20081 [measured]

CEP Finder 2.1 run; input "바나나우유", depth=quick
Volume is the trailing 3-month average monthly searches [measured]. Power's denominator is the set of queries classified into CEPs.
Brand share uses one method per CEP: brand appearance in search paths, measured brand co-searches, or brand mentions in the situation's search results and AI Overviews; never blended.
A CEP is a unit of "situation/scene," not "person"; from a penetration angle: more entry situations means a wider door for non-customers and light users.
4 CEP(s) with unmeasured brand linkage; can be expanded via a deep run

what to do first

when it grew and when it fell

Peak calendar: CEP × calendar-month index

fixed leaders, contested and open situations

each situation&#x27;s share of all situation searches

claimed vs. open (all CEPs)

does the situation lead to the category next

where this map&#x27;s situations cluster

age and gender by situation

Who it is for

What the qualitative attributes rest on

Where each CEP showed up

달콤한 간식이 필요할 때

아침 출근길에 간편하게 에너지를 보충하고 싶을 때

공부할 때 집중력을 높이고 싶을 때

아이 간식으로 적합한 것을 찾을 때

behavioral MMS proxy · width×depth

what this map does not say

CEP Finder at a glance

each situation's share of all situation searches

where this map's situations cluster