#1 moment for ‘포카리스웨트’: "탈수 증상이 나타나기 시작할 때" 57.2%

01At a glance

28,643

Monthly situation search volume

2

CEPs

2

Unclaimed situations

57.2%

Largest CEP share · 탈수 증상이 나타나기 시작할 때

Start here

1탈수 증상이 나타나기 시작할 때Unclaimed situation volume 16,373No brand shows up in this big situation yet → plant content & ads on its search terms first
2숙취로 인해 몸이 무거울 때Unclaimed situation volume 12,270No brand shows up in this big situation yet → plant content & ads on its search terms first

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	탈수 증상이 나타나기 시작할 때	57.2%	16,373	unclaimed	No brand shows up in this big situation yet → plant content & ads on its search terms first evidence medium
2	숙취로 인해 몸이 무거울 때	42.8%	12,270	unclaimed	No brand shows up in this big situation yet → plant content & ads on its search terms first evidence strong

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)-22%Last 3M YoY-27%Peak–48 months · CEP 2decliningnon-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)	-22%	-27%	–	decliningnon-seasonal
탈수 증상↗	-20%	-25%	7·8	stableseasonal	3/3
숙취 해소↗	-23%	-29%	–	decliningnon-seasonal	3/3

Peak calendar: CEP × calendar-month index

	1	2	3	4	5	6	7	8	9	10	11	12
탈수 증상	1.0	0.9	0.8	0.8	0.9	1.1	1.6	1.5	0.9	0.7	0.7	0.8
숙취 해소	1.1	0.9	1.0	0.8	0.9	0.8	0.8	0.9	1.3	1.1	1.1	1.2

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.

04Defend, grow, claimderived

which situations to hold, build and take

Defend (we lead) (0)

–

We lead here. Keep our presence in this situation's queries and AI answers; if contested, track the runner-up's content.

Grow (present, not leading) (0)

–

Present but behind. Concentrate content and search ads where the gap to the leader is smallest (situations where our share is low have the most room to grow).

Claim (measured, we are absent) (0)

–

Measured, but we are absent. Seed this situation's queries first, largest power first, to create the link.

Open (no brand mentions or unmeasured) (2)

탈수 증상 57.2% core
숙취 해소 42.8% minor

Open has two kinds: measured with no brand mentions is a claim candidate; unmeasured needs a deep run or survey before claiming.

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 2 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 2 entry situations · the other 2 are graded as opportunities. Small k/m in a cell = brand-mention sample (small m = low confidence).

	Brand link
탈수 증상57.2%	Big land-grab: large unclaimed situation 57.2% · mo. 16,373
숙취 해소42.8%	Big land-grab: large unclaimed situation 42.8% · mo. 12,270

[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): 포카리스웨트

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

탈수 증상 57.2% category-growth candidatelink rate 2% · low · 3/200 paths

숙취 해소 42.8%link rate 28% · mid · 56/200 paths

Link rate = share of search paths through this situation whose later queries contain a category term (이온, 음료) [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/benefit1 CEPs · power sum 43%

Who · for whom1 CEPs · power sum 57%

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 / 2

Empty axes: 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
탈수 증상	10	14	15	26	19	16	F 67%
숙취 해소	6	13	16	30	25	10	F 61%

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
Babies 아기 · 유아	아기 이온음료 · 유아 이온음료 · 아기 이온음료 추천		905
Pets 강아지 · 고양이	강아지 이온음료 · 고양이 이온음료		882
Pregnancy 임산부	임산부 이온음료		486
Kids 어린이	어린이 이온음료		183
Seniors 노인	노인 탈수 증상	탈수 증상이 나타나기 시작할 때	61

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 33%assumption 67%

measured4 · 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

assumption8 · interpretation without direct evidence

Based on the 12 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
KBF이온음료 효과	탈수 증상이 나타나기 시작할 때	이온음료 효과 · 이온음료 제로 효과	3,197	↓-18%
Nano intent빠른 숙취 해소	숙취로 인해 몸이 무거울 때	빠른 숙취 해소	59	↓-53%
Avoidance과도한 당분	탈수 증상이 나타나기 시작할 때, 숙취로 인해 몸이 무거울 때	당분 없는 음료 · 당분 적은 이온음료	23	↑+81%

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).

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 0/2 CEPs
Search paths	699 paths (incl. 0 deep-measurement paths)	in the dossiers of 0/2 CEPs
Search clusters	0 clusters · 0 queries	in the dossiers of 0/2 CEPs
SERPs (Google results)	0	in the dossiers of 0/2 CEPs
AI Overview	0	in the dossiers of 0/2 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
탈수 증상이 나타나기 시작할 때	–	100%	–	–	–	–	·	·	·	·	·	·	·
숙취로 인해 몸이 무거울 때	–	100%	–	–	–	–	·	·	·	·	·	·	·

13CEP detail cards

CEP 1purpose CEP

탈수 증상이 나타나기 시작할 때

Macroexplicit CEP

power 57.2% derived · avg monthly volume 16,373 · trend (3M) +38%

W-axis WhoOpen YoY (12M) -20% · Peak 7·8mo.stableseasonalcategory link 2%

The situationassumption

장염 환자나 노인에게 탈수 증상이 나타나기 시작할 때, 몸의 수분 균형이 깨져 불편함을 느낍니다. 탈수 예방을 위해 이온음료 효과를 원하며, 특히 장염 예방을 위해 또는 노인에게 적합한 것을 찾습니다. 이때 과도한 당분은 피하고 싶어 합니다. 이에 '탈수 증상', '장염 탈수 증상', '노인 탈수 증상'과 같은 질의로 정보를 찾아봅니다.

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

Investment priority derived

Investment candidate #1Unclaimed situation volume up to 16,373/mo

Market size 100 · Brand fit 0(no competition) · Provability 50, 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

장염으로 탈수 증상이 나타날 때 assumption 16,312 · 100% derived

노인에게 탈수 증상이 나타날 때 assumption 61 · 0% derived

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

Search journey: just before and after derived

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

Message angle assumption

Core message“탈수 증상이 나타나기 시작할 때, 이온음료의 효과로 빠르게 수분을 보충하고 활력을 되찾으세요.”

Content ideas탈수 증상 초기 대처법 가이드 (이온음료 포함) · 노인, 장염 환자를 위한 이온음료 섭취의 중요성 강조 캠페인 · 이온음료 섭취 후 활력을 되찾는 모습의 짧은 영상 콘텐츠

빠른 회복안심활력

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

Show 9 evidence blocksHide evidence

Evidence queries measured

탈수 증상 15,696measured장염 탈수 증상 616measured노인 탈수 증상 61measured

Nano intents (fine context)

장염 예방을 위해 ‹장염 예방법›assumption

Context (7W)

why: 탈수 예방 assumptionwhen: 탈수 증상 발생 시 assumptionwith whom: 노인 assumptionwith whom: 장염 환자 assumption

KBF (choice criteria)

이온음료 효과 ‹search '이온음료 효과' +1 · 3,197/mo›measured

Constraints

노인에게 적합한 ‹노인 탈수 증상›assumption

Avoidances

과도한 당분 ‹search '당분 없는 음료' +1 · 23/mo›measured

Alternatives (outside category)

전해질 음식 ‹전해질 음식›assumption

Selection axes (market · fit · provability)

Market size100

Brand fit0

Provability50

Searcher profile

Appendix: AI search exposure

AI tracking questions assumption

1“탈수 증상이 나타날 때 어떤 음료를 마셔야 할까요?”existing prompt

2“장염으로 탈수 증상이 있을 때 추천하는 음료는?”

3“노인에게 적합한 탈수 예방 음료는 무엇인가요?”

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

숙취로 인해 몸이 무거울 때

Macroexplicit CEP

power 42.8% derived · avg monthly volume 12,270 · trend (3M) -18%

W-axis WhyOpen YoY (12M) -23%decliningnon-seasonalcategory link 28%

The situationassumption

숙취 발생 시 몸이 무거움을 느끼며, 특히 위스키 숙취로 힘든 경우가 있습니다. 빠른 숙취 해소를 위해 숙취 해소 음료 효과를 원하며, 위스키 숙취에 적합한 것을 찾습니다. 사용자 후기를 신뢰하며, 과도한 당분은 피하고 싶어 합니다. 이에 '숙취 해소', '숙취 해소 음료', '위스키 숙취 해소'와 같은 질의로 해결책을 찾아봅니다.

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

Investment priority derived

Investment candidate #2Unclaimed situation volume up to 12,270/mo

Market size 75 · Brand fit 0(no competition) · Provability 67(evidence easy to substantiate), 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

숙취 해소 음료를 찾을 때 assumption 12,250 · 100% derived

위스키 숙취로 힘들 때 assumption 20 · 0% derived

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

Search journey: just before and after derived

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

Message angle assumption

Core message“숙취로 몸이 무거울 때, 사용자 후기로 검증된 숙취 해소 음료의 효과로 안도감을 느끼고 가벼워지세요.”

Content ideas실제 사용자들의 숙취 해소 경험담을 담은 인터뷰/리뷰 콘텐츠 · 숙취로 무거웠던 몸이 가벼워지는 과정을 시각적으로 보여주는 Before & After 영상 · 숙취 해소 음료 섭취 후 상쾌하게 하루를 시작하는 모습의 캠페인

안도감상쾌함활력

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

Show 11 evidence blocksHide evidence

Evidence queries measured

숙취 해소 7,640measured숙취 해소 음료 4,610measured위스키 숙취 해소 20measured

Nano intents (fine context)

빠른 숙취 해소 ‹search '빠른 숙취 해소' · 59/mo›measured

Context (7W)

why: 숙취 해소 assumptionwhen: 숙취 발생 시 assumptionfeeling: 몸이 무거움 assumption

KBF (choice criteria)

숙취 해소 음료 효과 ‹숙취 해소 음료›assumption

Constraints

위스키 숙취에 적합한 ‹위스키 숙취 해소›assumption

Avoidances

과도한 당분 ‹search '당분 없는 음료' +1 · 23/mo›measured

Reasons to believe

사용자 후기 ‹숙취해소제 추천›assumption

Emotion & style

안도감 ‹숙취 해소›assumption

Alternatives (outside category)

숙취해소제 ‹same evidence ↑›assumption

Selection axes (market · fit · provability)

Market size75

Brand fit0

Provability67

Searcher profile

Appendix: AI search exposure

AI tracking questions assumption

1“숙취로 몸이 무거울 때 어떤 음료가 좋을까요?”existing prompt

2“위스키 숙취 해소에 좋은 음료는?”

3“숙취 해소를 위한 음료 추천 부탁드립니다.”

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]	width (#CEPs linked)	depth (avg rank)
포카리스웨트	–	88,746	0	–

15Focal brand response priority

Strength (rank 1, defend)

–

Chance (small gap, attack)

–

Weakness (big gap, big market)

–

Conceded / hold

–

Rule: strength = #1 among measured CEPs / chance = gap to leader ≤5pt & power ≥ median / weakness = gap >15pt & power ≥ median; an explicit-threshold rule classification (not an algorithmic grade). 2 CEP(s) with unmeasured brand linkage are excluded from judgment: 탈수 증상이 나타나기 시작할 때, 숙취로 인해 몸이 무거울 때

16Limits

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 7 AI-suggested item(s) lacking evidence (evidence is enforced).
Of 12 qualitative attributes: 4 measured (33%), 0 consensus (0%), 0 derived, 8 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 · 2 of 2 CEPs have measured search queries, brand linkage measured for 0; the rest need the co-query matrix / trigger expansion (deep run)

17Reproducibility

Search volume lookup 7 · Search paths 3 · Related searches 2 · AI synthesis 1

Data retrieval detail

Connector calls	Parameters	Credits spent
Related searches	이온 음료 +3 / kr / limit 250	620
Search paths	이온 음료 / kr / limit 300	5890
Search volume lookup	12 / kr	12
Search paths	탈수 증상 / kr / limit 200	6850
Search paths	숙취 해소 / kr / limit 200	5810
Search volume lookup	265 / kr	265
Search volume lookup	4 / kr	4
Related searches	포카리스웨트 +0 / kr / limit 80	190
Search volume lookup	80 / kr	80
Search volume lookup	1 / kr	1
Search volume lookup	2 / kr / all	20
Search volume lookup	24 / kr	24
AI synthesis	gemini-2.5-flash (S0 grounded + S3 synthesis)	0

Credits spent: 19766 [measured]

CEP Finder 2.1 run; input "포카리스웨트" (topic: 구강 케어), 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.
2 CEP(s) with unmeasured brand linkage; can be expanded via a deep run
Recognized input "포카리스웨트" as a product name; analyzed against the "이온 음료" category, with focal brand "센소다인" auto-assigned