メイクキープミスト

01At a glance

19,038

Monthly situation search volume

1

CEPs · 5 situations without link evidence listed separately

5

Unclaimed situations

100.0%

Largest CEP share · マスクをしていてもメイクが崩れないよ

Start here

1マスクをしていてもメイクが崩れないようにしたいときUnclaimed situation volume 2,216Brands already show up here (leader: Kose) → challenge with differentiated content & search; defend if it's yours
2夏の暑さで汗が止まらないときUnclaimed situation volume 0No search evidence that this situation leads to メイクキープミスト → don't count it as existing demand; treat it as a category-expansion task (make メイクキープミスト a candidate in this situation)
3結婚式でメイクが崩れないようにしたいときUnclaimed situation volume 0No search evidence that this situation leads to メイクキープミスト → don't count it as existing demand; treat it as a category-expansion task (make メイクキープミスト a candidate in this situation)

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	マスクをしていてもメイクが崩れないようにしたいとき	100.0%	2,216	contested	Brands already show up here (leader: Kose) → challenge with differentiated content & search; defend if it's yours evidence weak

5 situations with no search evidence linking to メイクキープミスト (category-expansion candidates)

No searches or mentions leading from these situations to メイクキープミスト were found. They are not counted as existing demand (power 0%); treat them as a separate category-expansion task: getting people to think of メイクキープミスト in these moments.

Entry situation (CEP)	Monthly situation searches
夏の暑さで汗が止まらないとき	11,758
結婚式でメイクが崩れないようにしたいとき	3,866
フェスでメイクが崩れないようにしたいとき	779
卒業式でメイクが崩れないようにしたいとき	386
メイクを長持ちさせたいとき	33

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)

03Content opportunityderived

big needs the category does not reach yet

Three numbers per situation: how big the situation is (a ceiling), how strongly it already leads to the category (connection signal), and the difference (unconnected searches). The bigger the difference, the sooner content should make the connection.

19,038Situation searches (monthly, ceiling)

0.08Average connection (search-weighted)

17,553Unconnected searches (monthly, content opportunity)92% of situation searches

Content opportunity · big, weakly connectedDefend / compete · big, strongly connectedSecure the niche · small, strongly connectedHold · small, weakly connected

Situation	Situation searches (mo)	Connection	Unconnected	Group	What AI recommends instead	Bridging message
夏の暑さで汗が止まらないとき	11,758	0.00 search 0.00 · AI answers not measured	11,758	Content opportunity		“夏の汗によるメイク崩れには、メイクキープミストが汗に強いメイクをサポートし、口コミで高評価のアイテムとして一日中きれいな状態を保ちます。”Where they meet: メイクキープミストは、汗によるメイク崩れを防ぎ、一日中きれいな状態を保ちたいという夏のニーズに応えます。
結婚式でメイクが崩れないようにしたいとき	3,866	0.00 search 0.00 · AI answers not measured	3,866	Content opportunity	メイク直し用スプレー	“メイク直し用スプレーが崩れた後の対策であるのに対し、メイクキープミストは結婚式当日のメイクをプロのメイクアーティスト推奨の崩れにくさで、大切な一日中美しい状態を保ちます。”Where they meet: メイクキープミストは、結婚式のような大切な一日において、プロのメイクアーティストも推奨する崩れにくいメイクをサポートし、長時間美しい状態を保ちたいというニーズに応えます。
フェスでメイクが崩れないようにしたいとき	779	0.00 search 0.00 · AI answers not measured	779	Hold		“フェスやイベントで汗や動きによるメイク崩れが気になる時、メイクキープミストはメイクをしっかり固定し、楽しい時間をメイクの心配なく過ごせるようサポートします。”Where they meet: メイクキープミストは、フェスやイベントでの汗や動きによるメイク崩れを防ぎ、楽しい時間をメイクの心配なく過ごしたいというニーズに応えます。
マスクをしていてもメイクが崩れないようにしたいとき	2,216	0.67 search 0.67 · AI answers not measured	731	Defend / compete
卒業式でメイクが崩れないようにしたいとき	386	0.00 search 0.00 · AI answers not measured	386	Hold		“卒業式や発表会といった大切な日に、メイクキープミストは長時間メイクを崩れにくく保ち、思い出に残る一日を美しい表情で過ごせるようサポートします。”Where they meet: メイクキープミストは、卒業式や発表会のような大切な日に、長時間メイクが崩れずきれいな状態を保ち、思い出に残る一日を過ごしたいというニーズに応えます。
メイクを長持ちさせたいとき	33	0.00 search 0.00 · AI answers not measured	33	Hold		“朝の完璧なメイクを一日中長持ちさせたいなら、メイクキープミストがメイク崩れを防ぎ、美しい仕上がりをキープします。”Where they meet: メイクキープミストは、朝仕上げたメイクが時間が経っても崩れにくく、一日中メイクを長持ちさせたいという根本的なニーズに応えます。

Situation searches = how often the situation occurs (monthly average): the largest size the category could serve, not the number of people solving it with the category. Connection signal = the average of search connection (direct 1 · linked 0.67 · weak 0.33 · none 0) and AI-answer connection (share of the situation's representative results that name the category; AI Overview or citation 1, other results 0.5), measured parts only. Unconnected = situation searches × (1 − connection). Quadrant cut-offs: median situation searches 1,498 · connection 0.5. 'Not measured' means no results were fetched for that situation; 0 means measured with no mention.

04CEP occurrence over timederived

when it grew and when it fell

Total entry demand (all CEPs)YoY (12M)-27%Last 3M YoY-23%Peak3·6·7mo.48 months · CEP 6decliningseasonal

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)	-27%	-23%	3·6·7	decliningseasonal
マスクメイク↗	-24%	-26%	–	decliningnon-seasonal	2/2
夏の汗対策↗	-30%	-16%	5·6·7·8	decliningseasonal	5/5
結婚式メイク↗	-21%	-26%	10	decliningseasonal	1/1
フェスでメイク↗	-43%	-53%	5·7·8·9	decliningseasonal	2/2
卒業式メイク↗	-30%	-38%	2·3	decliningseasonal	2/2
長持ち↗	-43%	-47%	3	decliningnon-seasonal	1/1

Peak calendar: CEP × calendar-month index

	1	2	3	4	5	6	7	8	9	10	11	12
マスクメイク	0.9	0.9	1.1	1.2	1.2	1.2	1.2	0.9	0.8	0.8	0.8	0.8
夏の汗対策	0.1	0.1	0.3	0.8	1.5	2.5	4.1	1.6	0.7	0.2	0.1	0.1
結婚式メイク	0.9	1.1	1.1	0.9	1.1	0.8	0.8	0.8	1.2	1.4	1.3	0.7
フェスでメイク	0.5	0.4	0.6	0.8	1.3	1.0	1.9	2.2	1.4	0.9	0.5	0.5
卒業式メイク	1.1	2.9	6.2	0.1	0.1	0.1	0.2	0.2	0.2	0.2	0.3	0.3
長持ち	0.9	1.0	1.3	1.2	0.9	0.9	0.9	1.1	0.9	1.0	0.9	1.0

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.

05Defend, 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) (1)

マスクメイク 100.0% · leader Kose 92% · ours 0% core

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

Open (no brand mentions or unmeasured) (5)

夏の汗対策 no link evidence core
結婚式メイク no link evidence core
フェスでメイク no link evidence core
卒業式メイク no link evidence core
長持ち no link evidence core

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).

06CEP power

each situation's share of all situation searches

total 1 CEP · [derived] power = the CEP's search volume ÷ total volume of all CEPs

5 situations with no evidence linking to the category are left out of this chart (power 0%).

07Brand × entry situation

claimed vs. open (all CEPs)

Brand links measured for 1 of 6 entry situations · the other 5 are graded as opportunities. Small k/m in a cell = brand-mention sample (small m = low confidence).

	Kose	TIRTIR
マスクメイク100.0%	92%12/13	8%1/13
夏の汗対策no link evidence	No search evidence linking to メイクキープミスト: a category-expansion task, not existing demand no link evidence · mo. 11,758
結婚式メイクno link evidence	No search evidence linking to メイクキープミスト: a category-expansion task, not existing demand no link evidence · mo. 3,866
フェスでメイクno link evidence	No search evidence linking to メイクキープミスト: a category-expansion task, not existing demand no link evidence · mo. 779
卒業式メイクno link evidence	No search evidence linking to メイクキープミスト: a category-expansion task, not existing demand no link evidence · mo. 386
長持ちno link evidence	No search evidence linking to メイクキープミスト: a category-expansion task, not existing demand no link evidence · mo. 33

[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): Dior, ケイト, fwee, ダルバ, Kate, vim, Decorte, fixx

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

08Category link rate on search pathsderived

does the situation lead to the category next

夏の汗対策 no link evidence category-growth candidatelink rate 0% · low · 0/200 paths

結婚式メイク no link evidence category-growth candidatelink rate 0% · low · 0/6 paths

Link rate = share of search paths through this situation whose later queries contain a category term (メイクキープミスト) [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.

09W-axis mixassumption

where this map's situations cluster

Why · purpose/benefit2 CEPs · power sum 0%

Who · for whom0 CEPs · power sum 0%

When · timing/trigger2 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 / 6

Empty axes: Who · for whom, 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.

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
Men メンズ	メイクキープミストメンズ		163

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 43%assumption 57%

measured3 · 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

assumption4 · interpretation without direct evidence

Based on the 7 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
Emotion安心感	結婚式でメイクが崩れないようにしたいとき	メイクキープミストアルコールフリー	486	↑+10%
RTB口コミで高評価	夏の暑さで汗が止まらないとき	ケイトメイクキープミスト口コミ	440	↑+2647%
KBF汗に強い	夏の暑さで汗が止まらないとき	メイクキープミスト汗に強い	226	↓-47%

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

RTB口コミで高評価 ↑+2647%

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 0/6 CEPs
Search paths	629 paths (incl. 3 deep-measurement paths)	in the dossiers of 0/6 CEPs
Search clusters	0 clusters · 0 queries	in the dossiers of 0/6 CEPs
SERPs (Google results)	0	in the dossiers of 0/6 CEPs
AI Overview	0	in the dossiers of 0/6 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
マスクをしていてもメイクが崩れないようにしたいとき	–	–	–	–	–	–	·	·	·	·	·	·	·
夏の暑さで汗が止まらないとき	–	100%	–	–	–	–	·	·	·	·	·	·	·
結婚式でメイクが崩れないようにしたいとき	–	100%	–	–	–	–	·	·	·	·	·	·	·
フェスでメイクが崩れないようにしたいとき	–	–	–	–	–	–	·	·	·	·	·	·	·
卒業式でメイクが崩れないようにしたいとき	–	–	–	–	–	–	·	·	·	·	·	·	·

13CEP detail cards

CEP 1purchase CEP

マスクをしていてもメイクが崩れないようにしたいとき

Macroexplicit CEP

power 100.0% derived (whole situation 11.6%) · avg monthly volume 2,216 · trend (3M) -31%

Claim YoY (12M) -24%decliningnon-seasonal

The situationassumption

マスクを着用していると、蒸れや摩擦でメイクが崩れてしまうのが悩みです。マスクをしていても、一日中メイクが崩れないようにしたいと強く願っています。そこで、「マスクメイク崩れ」や「化粧崩れ」の対策を調べています。

Evidence this leads to メイクキープミストlinked

There is measured evidence that searches in this situation lead to メイクキープミスト.

Linking queries (measured): No query combining the situation and 'メイクキープミスト' (4 candidates measured)
Search paths: No paths pass through this situation's queries
SERP & AI Overview: No SERP was fetched for this situation's queries
Brand linkage: Brands measured in situation + category searches: Kose, TIRTIR

Next actionBrands already show up here (leader: Kose) → challenge with differentiated content & search; defend if it's yours evidence weak

Investment priority derived

Investment candidate #1Unclaimed situation volume up to 2,216/mo

Market size 100 · Brand fit 0(no competition) · 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 192 measured paths; an aggregate graph flow, not one person's timeline

Show 3 evidence blocksHide evidence

Evidence queries measured

化粧崩れ 1,766measuredマスクメイク崩れ 450measured

Selection axes (market · fit · provability)

Market size100

Brand fit0

Provability0

Top of CEP brands

Appendix: AI search exposure

AI tracking questions assumption

1“マスクをしていてもメイクが崩れない方法は？”existing prompt

2“マスク対応のメイクキープミストは？”

3“化粧崩れを防ぐアイテムは？”

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

夏の暑さで汗が止まらないとき

Macroexplicit CEP

power no link evidence derived (whole situation 61.8%) · avg monthly volume 11,758 · trend (3M) -66% possibly seasonal

W-axis WhyOpen YoY (12M) -30% · Peak 5·6·7·8mo.decliningseasonalcategory link 0%

The situationassumption

夏の暑さで汗が止まらないと、メイクが崩れてしまうのが悩みです。汗に強いメイクで、一日中きれいな状態を保ちたいです。そこで、汗対策や口コミで高評価のアイテムを探しています。

Evidence this leads to メイクキープミストno link evidence

No evidence this situation leads to メイクキープミスト. Its total volume could attach to any other category just as well, so it is not counted as existing demand. Making メイクキープミスト a candidate here is a category-expansion task.

Linking queries (measured): No query combining the situation and 'メイクキープミスト' (6 candidates measured)
Search paths: 0 of 200 paths through this situation's queries went on to a メイクキープミスト or brand search
SERP & AI Overview: No SERP was fetched for this situation's queries

Next actionNo search evidence that this situation leads to メイクキープミスト → don't count it as existing demand; treat it as a category-expansion task (make メイクキープミスト a candidate in this situation) evidence weak

Investment priority derived

Investment candidate #2Unclaimed situation volume up to 0/mo

Market size 0 · Brand fit 0(no competition) · 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

Search journey: just before and after derived

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

Bridging message assumption

Where they meetメイクキープミストは、汗によるメイク崩れを防ぎ、一日中きれいな状態を保ちたいという夏のニーズに応えます。

Core message“夏の汗によるメイク崩れには、メイクキープミストが汗に強いメイクをサポートし、口コミで高評価のアイテムとして一日中きれいな状態を保ちます。”

Content ideas夏の汗対策！メイクキープミストで崩れないベースメイク術 · 口コミで選ぶ！汗に強いメイクキープミスト徹底比較 · 夏のレジャーも安心！メイクキープミストで叶える崩れ知らずメイク

安心感信頼爽やか

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

Show 6 evidence blocksHide evidence

Evidence queries measured

汗対策 6,466measured汗対策グッズ 2,106measured汗かき対策 1,740measured滝汗対策 1,240measured汗対策顔 206measured

Context (7W)

why: 汗が止まらない assumption

KBF (choice criteria)

汗に強い ‹search 'メイクキープミスト汗に強い' · 226/mo›measured

Reasons to believe

口コミで高評価 ‹search 'ケイトメイクキープミスト口コミ' · 440/mo›measured

Emotion & style

安心感 ‹汗対策グッズ›assumption

Selection axes (market · fit · provability)

Market size0

Brand fit0

Provability33

Appendix: AI search exposure

AI tracking questions assumption

1“夏の暑さで汗が止まらないときにおすすめのメイクキープミストは？”existing prompt

2“通勤中に汗が気になるときに使えるメイクキープミストを教えて。”

3“汗対策に効果的なメイクキープミストを探しています。”

4“汗を抑えたいときに使えるメイクキープミストはどれですか？”

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

結婚式でメイクが崩れないようにしたいとき

Macroexplicit CEP

power no link evidence derived (whole situation 20.3%) · avg monthly volume 3,866 · trend (3M) +22%

W-axis WhyOpen YoY (12M) -21% · Peak 10mo.decliningseasonalcategory link 0%

The situationassumption

結婚式当日は、特別な一日だからこそメイクが崩れないようにしたいです。大切な場面でメイクが崩れてしまうのは避けたいです。プロのメイクアーティスト推奨の、崩れにくいメイクを求めています。そのため、「結婚式メイク」で情報収集しています。

Evidence this leads to メイクキープミストno link evidence

No evidence this situation leads to メイクキープミスト. Its total volume could attach to any other category just as well, so it is not counted as existing demand. Making メイクキープミスト a candidate here is a category-expansion task.

Linking queries (measured): No query combining the situation and 'メイクキープミスト' (7 candidates measured)
Search paths: 0 of 6 paths through this situation's queries went on to a メイクキープミスト or brand search
SERP & AI Overview: No SERP was fetched for this situation's queries

Next actionNo search evidence that this situation leads to メイクキープミスト → don't count it as existing demand; treat it as a category-expansion task (make メイクキープミスト a candidate in this situation) evidence weak

Investment priority derived

Investment candidate #3Unclaimed situation volume up to 0/mo

Market size 0 · Brand fit 0(no competition) · 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

結婚式当日にメイクが崩れないようにしたいとき assumption 3,866 · 100% derived

ブライダルメイクのリハーサルで確認したいとき assumption 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

Search journey: just before and after derived

Adjacent transitions aggregated from 6 measured paths; an aggregate graph flow, not one person's timeline

Bridging message assumption

Where they meetメイクキープミストは、結婚式のような大切な一日において、プロのメイクアーティストも推奨する崩れにくいメイクをサポートし、長時間美しい状態を保ちたいというニーズに応えます。

Core message“メイク直し用スプレーが崩れた後の対策であるのに対し、メイクキープミストは結婚式当日のメイクをプロのメイクアーティスト推奨の崩れにくさで、大切な一日中美しい状態を保ちます。”

Content ideas結婚式メイクの最終兵器！プロが教えるメイクキープミスト活用術 · 感動の涙も汗も怖くない！メイクキープミストで叶えるブライダルメイク · 花嫁さんの必需品！メイクキープミストで一日中完璧なウェディングメイク

信頼上質安心感

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

Show 8 evidence blocksHide evidence

Evidence queries measured

結婚式メイク 3,866measured結婚式メイク当日変更 –no dataブライダルメイク後悔 –no data

Nano intents (fine context)

メイクが崩れないようにしたい ‹結婚式メイク当日変更›assumption

Context (7W)

why: メイクが崩れないようにしたい assumption

Reasons to believe

プロのメイクアーティスト推奨 ‹ブライダルメイク後悔›assumption

Emotion & style

安心感 ‹search 'メイクキープミストアルコールフリー' · 486/mo›measured

Alternatives (outside category)

メイク直し用スプレー ‹same evidence ↑›assumption

Selection axes (market · fit · provability)

Market size0

Brand fit0

Provability33

Top of CEP brands

not queried: Dior

Appendix: AI search exposure

AI tracking questions assumption

1“結婚式でメイクが崩れないようにするためのメイクキープミストは？”existing prompt

2“ブライダルメイクのリハーサルで確認したいメイクキープミストを教えて。”

3“結婚式当日にメイクが崩れないようにするためのおすすめは？”

4“プロのメイクアーティストが推奨するメイクキープミストはどれですか？”

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

フェスでメイクが崩れないようにしたいとき

Macroexplicit CEP

power no link evidence derived (whole situation 4.1%) · avg monthly volume 779 · trend (3M) +15%

W-axis WhenOpen YoY (12M) -43% · Peak 5·7·8·9mo.decliningseasonal

The situationassumption

フェスやイベントに参加する際、汗や動きでメイクが崩れてしまうのが気になります。楽しい時間を過ごすためにも、メイクが崩れないようにしたいと願っています。そこで、「フェスメイク」や「イベントメイク」で対策を探しています。

Evidence this leads to メイクキープミストno link evidence

No evidence this situation leads to メイクキープミスト. Its total volume could attach to any other category just as well, so it is not counted as existing demand. Making メイクキープミスト a candidate here is a category-expansion task.

Linking queries (measured): No query combining the situation and 'メイクキープミスト' (4 candidates measured)
Search paths: No paths pass through this situation's queries
SERP & AI Overview: No SERP was fetched for this situation's queries

Next actionNo search evidence that this situation leads to メイクキープミスト → don't count it as existing demand; treat it as a category-expansion task (make メイクキープミスト a candidate in this situation) evidence weak

Investment priority derived

Investment candidate #4Unclaimed situation volume up to 0/mo

Market size 0 · Brand fit 0(no competition) · 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

Bridging message assumption

Where they meetメイクキープミストは、フェスやイベントでの汗や動きによるメイク崩れを防ぎ、楽しい時間をメイクの心配なく過ごしたいというニーズに応えます。

Core message“フェスやイベントで汗や動きによるメイク崩れが気になる時、メイクキープミストはメイクをしっかり固定し、楽しい時間をメイクの心配なく過ごせるようサポートします。”

Content ideasフェスで踊りまくっても崩れない！メイクキープミストで最強フェスメイク · 汗と動きに強い！メイクキープミストで叶えるイベントメイク術 · メイク崩れを気にせず楽しむ！メイクキープミストでフェスを攻略

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

Show 3 evidence blocksHide evidence

Evidence queries measured

フェスメイク 566measuredイベントメイク 213measured

Context (7W)

when: フェス assumptionwhen: イベント assumption

Selection axes (market · fit · provability)

Market size0

Brand fit0

Provability0

Appendix: AI search exposure

AI tracking questions assumption

1“フェスでメイクが崩れない方法は？”existing prompt

2“イベント中にメイクをキープするには？”

3“汗をかいてもメイクが崩れないアイテムは？”

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 5purchase CEP

卒業式でメイクが崩れないようにしたいとき

Macroexplicit CEP

power no link evidence derived (whole situation 2.0%) · avg monthly volume 386 · trend (3M) +56% possibly seasonal

W-axis WhenOpen YoY (12M) -30% · Peak 2·3mo.decliningseasonal

The situationassumption

卒業式や発表会といった大切な日に、メイクが崩れてしまうのは避けたいです。長時間きれいな状態を保ち、思い出に残る一日を過ごしたいと願っています。そのため、「卒業式メイク」や「発表会メイク」で崩れにくいメイクを探しています。

Evidence this leads to メイクキープミストno link evidence

No evidence this situation leads to メイクキープミスト. Its total volume could attach to any other category just as well, so it is not counted as existing demand. Making メイクキープミスト a candidate here is a category-expansion task.

Linking queries (measured): No query combining the situation and 'メイクキープミスト' (5 candidates measured)
Search paths: No paths pass through this situation's queries
SERP & AI Overview: No SERP was fetched for this situation's queries

Next actionNo search evidence that this situation leads to メイクキープミスト → don't count it as existing demand; treat it as a category-expansion task (make メイクキープミスト a candidate in this situation) evidence weak

Investment priority derived

Investment candidate #5Unclaimed situation volume up to 0/mo

Market size 0 · Brand fit 0(no competition) · 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

Bridging message assumption

Where they meetメイクキープミストは、卒業式や発表会のような大切な日に、長時間メイクが崩れずきれいな状態を保ち、思い出に残る一日を過ごしたいというニーズに応えます。

Core message“卒業式や発表会といった大切な日に、メイクキープミストは長時間メイクを崩れにくく保ち、思い出に残る一日を美しい表情で過ごせるようサポートします。”

Content ideas卒業式の感動を美しく！メイクキープミストで叶える崩れ知らずメイク · 発表会の舞台でも自信！メイクキープミストで長時間キープメイク術 · 大切な日のメイク崩れ対策！メイクキープミストで完璧な一日を

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

Show 3 evidence blocksHide evidence

Evidence queries measured

卒業式メイク 303measured発表会メイク 83measured

Context (7W)

when: 卒業式 assumptionwhen: 発表会 assumption

Selection axes (market · fit · provability)

Market size0

Brand fit0

Provability0

Appendix: AI search exposure

AI tracking questions assumption

1“卒業式でメイクをキープする方法は？”existing prompt

2“発表会でメイクが崩れないアイテムは？”

3“写真撮影に適したメイクキープミストは？”

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 6purpose CEP

メイクを長持ちさせたいとき

Macroexplicit CEP

power no link evidence derived (whole situation 0.2%) · avg monthly volume 33 · trend (3M) +150% possibly seasonal

Open YoY (12M) -43% · Peak 3mo.decliningnon-seasonal

The situationassumption

朝に完璧に仕上げたメイクも、時間が経つと崩れてしまうのが悩みです。一日中、メイクを長持ちさせたいと強く願っています。そこで、「メイク長持ち」のコツやアイテムを探しています。

Evidence this leads to メイクキープミストno link evidence

No evidence this situation leads to メイクキープミスト. Its total volume could attach to any other category just as well, so it is not counted as existing demand. Making メイクキープミスト a candidate here is a category-expansion task.

Linking queries (measured): No query combining the situation and 'メイクキープミスト' (2 candidates measured)
Search paths: No paths pass through this situation's queries
SERP & AI Overview: No SERP was fetched for this situation's queries

Next actionNo search evidence that this situation leads to メイクキープミスト → don't count it as existing demand; treat it as a category-expansion task (make メイクキープミスト a candidate in this situation) evidence weak

Investment priority derived

Investment candidate #6Unclaimed situation volume up to 0/mo

Market size 0 · Brand fit 0(no competition) · 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

Bridging message assumption

Where they meetメイクキープミストは、朝仕上げたメイクが時間が経っても崩れにくく、一日中メイクを長持ちさせたいという根本的なニーズに応えます。

Core message“朝の完璧なメイクを一日中長持ちさせたいなら、メイクキープミストがメイク崩れを防ぎ、美しい仕上がりをキープします。”

Content ideas朝のメイクを夜までキープ！メイクキープミストで叶える長持ちメイク術 · もうメイク直し不要？メイクキープミストで一日中美しい私 · メイク崩れのお悩み解決！メイクキープミストで長持ちメイクの秘訣

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

Show 2 evidence blocksHide evidence

Evidence queries measured

メイク長持ち 33measured

Selection axes (market · fit · provability)

Market size0

Brand fit0

Provability0

14Brand summary

behavioral MMS proxy · width×depth

	MMS proxy [derived]	branded volume [measured]	width (#CEPs linked)	depth (avg rank)
Dior	–	345,666	0	–
ケイト	–	136,666	0	–
fwee	–	47,166	0	–
ダルバ	–	35,566	0	–
Kate	–	29,100	0	–
vim	–	19,733	0	–
Kose	–	19,466	1	1.0
TIRTIR	–	17,266	1	2.0
Decorte	–	14,800	0	–
fixx	–	2,733	0	–

15Mental availability metrics (search version)derived

MMS · MPen · NS · SOM

	MMS	MPen	NS	SOM	brand-name volume share	expected MMS	mental advantage	size	KPI
Kose	92.0%	100.0%	1 / 1	92.0%	2.9%	2.9%	+89.1pt	small	MPEN
TIRTIR	8.0%	100.0%	1 / 1	8.0%	2.6%	2.6%	+5.4pt	small	MPEN
Dior	0.0%	0.0%	0 / 1	–	51.7%	51.7%	-51.7pt	large	SOM
ケイト	0.0%	0.0%	0 / 1	–	20.4%	20.4%	-20.4pt	medium	NS
fwee	0.0%	0.0%	0 / 1	–	7.1%	7.1%	-7.1pt	small	MPEN
ダルバ	0.0%	0.0%	0 / 1	–	5.3%	5.3%	-5.3pt	small	MPEN
Kate	0.0%	0.0%	0 / 1	–	4.4%	4.4%	-4.4pt	small	MPEN
vim	0.0%	0.0%	0 / 1	–	2.9%	2.9%	-2.9pt	small	MPEN
Decorte	0.0%	0.0%	0 / 1	–	2.2%	2.2%	-2.2pt	small	MPEN
fixx	0.0%	0.0%	0 / 1	–	0.4%	0.4%	-0.4pt	small	MPEN

MMS = Σ(CEP power × share) ÷ measured CEP power (brands sum to 1) · MPen = power share of CEPs where the brand appears · NS = number of linked CEPs · SOM = power-weighted mean share within linked CEPs. Identity MMS = MPen × SOM. Expected MMS = brand-name volume share; advantage = MMS − expected.

Computed on 1/6 measured CEPs (power sum 100%). Size: brand-name volume share ≥30% large · <10% small · else medium. KPI (EBMI): small=MPen · medium=NS · large=SOM; MMS is everyone's KGI. Brand-name volume is the bare brand query, so multi-category brands (Samsung, LG) include demand outside this category and may be oversized.

Strategy by brand size · ダルバ
Small: the shortest path is taking share in the leader's prototypical CEPs (top power); do not cling to niche CEPs (EBMI). Targets: マスクメイク

16Focal brand response priority

Strength (rank 1, defend)

–

Chance (small gap, attack)

–

Weakness (big gap, big market)

マスクをしていてもメイクが崩れないようにしたいとき · gap to leader 92.0pt · leader Kose 92%, no measured link for ours

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). 5 CEP(s) with no evidence of leading to the category are not judged for brands (夏の暑さで汗が止まらないとき, 結婚式でメイクが崩れないようにしたいとき, フェスでメイクが崩れないようにしたいとき, 卒業式でメイクが崩れないようにしたいとき, メイクを長持ちさせたいとき).

17Limits

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 37 AI-suggested item(s) lacking evidence (evidence is enforced).
Of 7 qualitative attributes: 3 measured (43%), 0 consensus (0%), 0 derived, 4 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 · 6 of 6 CEPs have measured search queries, brand linkage measured for 1; the rest need the co-query matrix / trigger expansion (deep run)

18Reproducibility

Search volume lookup 10 · Search paths 6 · Search results (SERP, AI Overview) 5 · Related searches 1 · AI synthesis 1

Data retrieval detail

Connector calls	Parameters	Credits spent
Related searches	メイクキープミスト +3 / jp / limit 250	620
Search paths	メイクキープミスト / jp / limit 300	7970
Search volume lookup	12 / jp	12
Search volume lookup	15 / jp	15
Search paths	汗対策 / jp / limit 200	4690
Search paths	結婚式メイク / jp / limit 200	450
Search volume lookup	261 / jp	261
Search volume lookup	6 / jp	6
Search volume lookup	80 / jp	80
Search volume lookup	12 / jp	12
Search volume lookup	66 / jp	66
Search volume lookup	60 / jp	60
Search paths	汗対策メイクキープミスト / jp / limit 200	0
Search results (SERP, AI Overview)	serp '汗対策メイクキープミスト' / jp	0
Search paths	結婚式メイクキープミスト / jp / limit 200	0
Search results (SERP, AI Overview)	serp '結婚式メイクキープミスト' / jp	0
Search paths	マスクメイクキープミスト / jp / limit 200	6810
Search results (SERP, AI Overview)	serp 'フェスメイクキープミスト' / jp	0
Search results (SERP, AI Overview)	serp '卒業式メイクキープミスト' / jp	0
Search results (SERP, AI Overview)	serp 'メイクメイクキープミスト' / jp	0
Search volume lookup	28 / jp	28
Search volume lookup	13 / jp	13
AI synthesis	gemini-2.5-flash (S0 grounded + S3 synthesis)	0

Credits spent: 21093 [measured]

CEP Finder 2.1 run; input "メイクキープミスト" (topic: ミスト、スキンケア), 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.

what to do first

big needs the category does not reach yet

when it grew and when it fell

Peak calendar: CEP × calendar-month index

which situations to hold, build and take

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

Who it is for

What the qualitative attributes rest on

Where each CEP showed up

マスクをしていてもメイクが崩れないようにしたいとき

夏の暑さで汗が止まらないとき

結婚式でメイクが崩れないようにしたいとき

フェスでメイクが崩れないようにしたいとき

卒業式でメイクが崩れないようにしたいとき

メイクを長持ちさせたいとき

behavioral MMS proxy · width×depth

MMS · MPen · NS · SOM

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