Smart Home Scenario Research

Client Work User ResearchPersonaNeeds AnalysisScenario Research
Smart Home Scenario Research

About

Haier Smart Home is a leading home appliance manufacturer in China, expanding aggressively into connected living — they commissioned this project to identify which smart home scenarios were actually worth building. Spanning 7 cities and 224 participants, the project enumerated 149 candidate scenarios through a 7+1 daily activity framework, and filtered through 4 progressive rounds to land on 20 high-priority scenarios that balanced real user demand with commercial viability.

Client
Haier Smart Home
Identify the highest-value smart home scenarios for the next product generation
My Role
Research Analyst
Persona synthesis, needs analysis, scenario filtering — full analysis phase
Output
140-page Research Report
Personas, needs matrix, journey maps, scenario scoring

Challenge

Users surface all kinds of needs. Filtering them down required more than asking users to rate each one. The challenge was building a multi-round filtering system, and a scoring framework that weighed demand intensity against commercial viability. Every cut had to be traceable back to evidence.

Solution

20

high-priority scenarios

Covering bedroom, kitchen, living room, bathroom, and entrance — each scenario has clear user needs behind it, defined trigger moments, and enough commercial headroom to justify building.

Research Process

I inherited a full dataset with no first-hand field experience — which meant reconstructing the research intent from raw transcripts while simultaneously executing the full analysis deliverable set.

01
Industry Analysis
landscape & trend review
02
Field Interviews
7 cities
joined
03
Persona Synthesis
segmentation · behavioral clustering
04
Needs Analysis
7+1 framework · shared & differentiated needs
05
Scenario Filtering
Kano model · scoring framework · prioritization

Research Subject

36
Depth Interviews
smart enthusiasts 10 & general users 26
150
Survey
new middle-class 120 & middle-aged 30
32
Co-creation Workshop
new middle-class 26 & middle-aged 6
6
Expert Evaluation
flagship store sales experts

Personas

Based on field interviews, I synthesised 5 user archetypes reflecting distinct living situations, smart home attitudes, and lifestyle patterns. Each persona captures not just demographics but the underlying values and tensions that shape smart home adoption.

Solo
Newlyweds
Nuclear Family
& Two-child
Three-gen
Empty-nesters
High
Home Security
Housekeeping
Home Security
Sleep & Rest
Housekeeping
Housekeeping
Home Security
Home Security
Sleep & Rest
Housekeeping
Home Security
Housekeeping
Sleep & Rest
Mid
Sleep & Rest
Fitness
Entertainment
Food & Cooking
Entertainment
Food & Cooking
Entertainment
Fitness
Sleep & Rest
Entertainment
Food & Cooking
Food & Cooking
Entertainment
Low
Personal Bathing
Food & Cooking
Fitness
Personal Bathing
Personal Bathing
Fitness
Personal Bathing
Personal Bathing
Fitness
Taking the Solo as an example
Full User Persona
Solo User
Tutu
”Laziness peak — smart home makes solo life so much easier”
Age24
EducationBachelor
CityChengdu
JobPublic sector
Home75㎡, solo
Income¥150k/yr
Tags
HomebodyLeisure ConsumerNiche CommunitiesHigh IoT Adoption
Life Attitudes
  • ·Hedonic, leisure-driven — happy to pay for hobbies and self-indulgence
  • ·“Work harder = happier” coexists with “lie flat, reject hustle culture”
  • ·Beauty-first; actively builds personal aesthetic through novelty
Interests
  • ·Hobby spending is about gaining “style” — interests are a vehicle for self-expression and identity
  • ·Diverse: beauty, pets, gaming, tech, collectibles and art toys
  • ·Niche “circles” define spiritual life and social connection
Media Habits
  • ·Drawn to diverse PGC content: news, entertainment, food, fashion, tech
  • ·Has favourite creators; actively follows their updates
  • ·Prefers short video and social platforms; niche platforms rank above mainstream for engagement
Smart Home Attitudes
  • ·High adoption — automation feels instinctive, not novel
  • ·Prefers young, trendy brands; value-for-money focus
  • ·Core functions must work; standout appearance is a real differentiator
Typical Behaviour Patterns
Home Security
  • ·Living alone drives strong self-protection instincts; prioritises personal privacy and avoiding information leaks
  • ·Relies on property security, access control, and indoor surveillance to protect home and belongings
  • ·Pet owners are concerned about pets’ safety and health while home alone
  • ·Safety concerns when ordering food alone, commuting late, or running at night
Cleaning & Hygiene
  • ·Prefers simple and efficient cleaning through smart appliances that free up hands
  • ·Personal cleanliness matters for social impression management; at home, basic hygiene is enough
  • ·Clothes are mostly cotton/blended; values time-saving and clean results
Sleep & Rest
  • ·Rich pre-sleep rituals — chatting, music/audiobooks, gaming, skincare, late-night snacks
  • ·Poor sleep habits: “up late, won’t get up in the morning”
  • ·Some experience anxiety-related insomnia; open to sleep aids (aromatherapy, melatonin)
Exercise & Health
  • ·Values exercise but limited by work schedule
  • ·Some are gym-goers pursuing body goals through personal trainers
  • ·Generally young; low need for health monitoring or disease prevention
Leisure & Entertainment
  • ·Homebodies who live on their phones — streaming shows, browsing, gaming, and shopping online dominate home time
Food & Cooking
  • ·Default to takeout — avoids the hassle of going out and the awkwardness of solo dining
  • ·Buys pre-cut ingredients and meal kits for quick cooking
  • ·Some enjoy cooking with small kitchen appliances and sharing dishes on social media

User Needs

During the structured needs elicitation phase, we used a 7+1 daily activity framework (wake up, leave home, away, return home, meals, leisure, pre-sleep, plus whole-home universal scenarios) to systematically enumerate user behaviour paths, pain points, and smart home demands across each sub-scenario
— surfacing 149 need scenarios in total.
Needs were mapped across two dimensions — shared (cross-persona) and differentiated (by family structure).

We found pain points concentrated at behavioural transition points — leaving home, returning home, pre-sleep — not spread evenly through the day. Security, sleep, and meal scenarios recurred across all user groups.

Taking the Home Security scenario as an example
Shared Needs
Type
Pain Points & Expectations
Basic
Needs
1. Smart lock battery drains fast
”Scared of missing the low-battery alert”
2. Unstable camera connection
”Camera disconnects on its own sometimes”
3. No way to know if sensors are working
”Smoke sensors feel like a placebo — I don’t actually know if they work”
Expected
Needs
1. Indiscriminate motion alerts are annoying
”No need to alert when parents or the cleaner visit”
2. Alerts alone can’t resolve danger
”Gas leak needs the valve shut first, not just an alarm”
3. No early-warning capability
”I want prevention, not notification after a pipe has burst”
Delight
Needs
1. Want camera access from any room
”Big house — want to check cameras on the TV too”
2. Want proactive anomaly detection
”Besides checking manually, want it to detect crying and alert parents”
3. Want personalised lock feedback
”My lock sounds identical to the neighbours’ — I always think theirs is mine”
Differentiated Needs — by Family Structure
Solo / Individual
Anti-tailgating, anti-break-in
Privacy protection (address / calls)
Emergency alert & rescue
Intrusion prevention
Monitoring utility safety
Newly married
Radiation protection during pregnancy
Anti-slip, fall prevention (bathroom / kitchen)
Nuclear / two-child family
Child monitoring with anomaly alerts
Keep utilities away from children
Prevent falls and collisions
Monitor children’s movements outside
Elderly household
Device monitoring with anomaly alerts
Long-range accessible intercom
Elderly-friendly home design with grab bars
Night lighting to prevent falls
Monitor elderly movements outside
Anti-slip, fall prevention (bathroom / kitchen)
Emergency alert & rescue
User Journey Map
Stage
Before leaving▶
Away from home▶
Returning home▶
Need
Appliances auto-off, only security active · nothing left behind
Stay updated on what’s happening at home
Lights on, security disarmed on entry
Actions
1.Pack everything needed for the day
2.Check doors, windows, gas, appliances
3.Grab keys, put on shoes and jacket at the entrance
4.Check appearance in hallway mirror
5.Confirm everything is packed, head out
1.Check home camera via phone; watch pet activity
2.Check cat’s feeding and litter box via app
3.Check commute time before heading home
4.Pre-turn on AC and water heater before arriving
1.Smart lock or door sensor detects arrival
2.Lights turn on automatically
3.Remove jacket and shoes at the entrance, put on slippers
4.Head to kitchen for a drink
5.Turn on TV, collapse on the sofa
Tools
Smart lockPhone
PhoneSecurity cameraLitter box appACWater heater
Smart lockSmart lights
Mood
😐
😐
😄
Pain Points
1.Tedious to check everything every time you leave
2.Realising you forgot something only after leaving
3.”Away mode” triggers on any door movement, not just actual departures
4.Can’t find the right outfit
5.Wardrobe ends up messy while searching
1.Realising on a rainy day that windows were left open — helpless
2.Frequent motion alerts from outdoor camera become intrusive
3.Worry about whether doors and appliances were properly closed
1.”Home mode” triggers on any door movement, not just actual arrivals

Scenario Filter

Most qualitative research surfaces needs but leaves prioritisation implicit. Here, each cut had to be traceable — not a judgement call, but a documented gate with defined criteria. Four rounds progressively narrowed the field, each one testing a different dimension: internal plausibility, user demand type, real-world scoring, and finally commercial readiness.

Scenario Input
In-depth interviews & desk research
149candidate scenarios
▼
Round 1 — Internal Expert Rating
Initial screening by Isar and Haier internal evaluators; 4-star and 5-star scenarios selected
61scenarios advanced
▼
Round 2 — Kano Model Classification
The 61 shortlisted scenarios were classified using the Kano model to determine need type
31
Attractive (A)
Absence does not reduce satisfaction; presence significantly increases it
Smart window closeIngredient managementSmart dryingFamily healthAudio-visual bathingHomecoming mode…
10
One-dimensional (O)
Presence increases satisfaction; absence decreases it
Appliance cleaningSeamless device pairingChildren’s TV modeChildren’s dental careWhole-home air filterPost-bath cleaning…
16
Indifferent (I)
Users are neutral regardless of whether this need is met
Morning briefing…
4
Must-be (M)
Improving this need does not raise satisfaction, but its absence causes significant dissatisfaction
Robot vacuum maintenance…
▼
Round 3 — Workshop User Scoring
In-person workshops where participants scored scenarios across frequency, concern, satisfaction, and impact dimensions
36high-demand scenarios
Scoring Dimensions
1. Frequency
How often the pain point occurs in daily life
2. Concern
How much the user cares about this problem
3. Satisfaction
User satisfaction with the proposed scenario solution
4. Impact
Perceived life impact if the scenario is not provided
0. Composite
Weighted average of dimensions 1–4
Scenes to Iterate
Existing scenarios × high demand score
Improve & enhance existing implementations
Scenes to Prioritise
Unimplemented scenarios × high demand score
Key targets for future planning & development
▼
Round 4 — Sales Expert Validation
Sales experts from Haier’s flagship stores assessed the 36 workshop outputs for commercial value and ranked the top scenarios
20high-priority scenarios
20 High-Priority Scenarios
Health Care
  • ·Family health management
  • ·Healthy sleep climate control
  • ·Children’s TV mode
  • ·Children’s dental care
Food & Cooking
  • ·Cooking safety monitoring
Laundry
  • ·Easy laundry for elderly users
Whole-Home Smart
  • ·Smart home interior planning
  • ·Scene library automation
  • ·Effortless device setup
  • ·Family cloud storage
Appliance Cleaning
  • ·Appliance self-cleaning
  • ·Air filter replacement reminder
Bathroom
  • ·Post-bath cleaning
  • ·Warm bath in winter
Air Quality
  • ·Clean air for sleep
  • ·Whole-home air auto-adjustment
  • ·On-demand window open/close
Whole-Home Control
  • ·Homecoming mode
  • ·Away mode
  • ·Forgotten item reminder on leaving
Scenario Deep Dive
Clean Air
for Sleep
SpaceBedroom
ActivitySleep & rest
TimeNight
HouseholdNewlyweds
Layout4-bed
Area90–120 / 180㎡+
Budget¥400k+
Scenario Description
  • ·Before sleep, the air quality detector senses elevated CO₂ and PM2.5 levels. The purifier activates automatically.
  • ·Based on live outdoor air quality data, the smart windows either open for ventilation or stay closed to filter in door air.
  • ·The smartwatch and smart pillow jointly track sleep depth. As the user drifts into deeper sleep stages, the system gently dims the lights, lowers the temperature, and reduces ambient sound.
Products Involved
Sensing
Air quality detectorSmartwatchSmart pillow
Actuation
Air purifierCentral fresh air system
Control
Smart speakerSmart panelSmartphone
Warm Bath
in Winter
SpaceBathroom
ActivityPersonal cleaning
TimeAll day
HouseholdSolo
Layout2-bed
Area60–90㎡
Budget¥60k–100k
Scenario Description
  • ·The user says “I want to shower” to the smart speaker. When the room temperature is low, the bedroom AC and bathroom floor heating activate to pre-warm both spaces. Once the target temperature is reached, the speaker confirms: “All warm — you can shower now.”
  • ·The water heater continuously delivers temperature-controlled hot water, with current temperature displayed on the faucet panel — the user showers in a warm, ready environment with no manual adjustments needed.
Products Involved
Bathing
Smart water heater
Sensing
Temp & humidity sensor
Heating
ACHeating fanSmart bath heater
Control
Smart speaker
Cooking
Safety
SpaceKitchen
ActivityHome safety
TimeAll day
HouseholdAll types
LayoutAll types
AreaAll types
BudgetAll types
Scenario Description
  • ·When overflow, dry-burning, gas leaks, or water leaks are detected, the kitchen safety system — including the range hood and smoke alarms — immediately shuts off gas and water valves and sends alert messages. The security system also factors in problem severity and whether anyone is home to determine if property management should intervene.
  • ·If a fire during cooking spreads beyond the preset area threshold, the ceiling-mounted suppression system activates and sprays foam extinguishing agent.
Products Involved
Kitchen Safety
Smart range hoodSmart cooktop
Sensing
Smoke sensorWater leak sensor
Suppression
Smart fire suppression system

Reflection

What I learned: Working within an existing research structure taught me how to quickly absorb context and add value without duplicating effort. Persona synthesis under real constraints — imperfect data, tight timelines — sharpened my ability to make defensible analytical decisions.

What I’d do differently: I wish I had been involved earlier in interview design. Some of the data gaps I encountered during persona synthesis could have been addressed upstream with better screener criteria.

An honest limitation: As a support contributor, I had limited visibility into how the final 20 scenarios were eventually translated into products. Following up on research outcomes is something I now actively prioritise in subsequent projects.