13.1 Case 1: Why is it not recommended to blindly fill villas for high-net-worth households?
13.1 Case 1: Why is it not recommended to blindly fill villas for high-net-worth households?
Customer portrait: Self-owned house in the suburbs of Bangkok, 7 air conditioners, there are elderly people and people working from home during the day, the monthly electricity bill has been historically high, and the visible roof surface is obvious. The first demand of customers is not the lowest price, but beauty, stability and after-sales certainty.
Key judgment: This type of customer has higher spontaneous self-use value, but is also most likely to amplify problems after delivery due to aesthetics, leakage and effect expectations. Therefore, the value of the project is not to install it to the maximum, but to install it to the best match.
Calculation logic: First estimate the conservative spontaneous self-use rate based on the stable load during the day, and then calculate the annual savings under different capacity plans. If continued expansion of the system leads to a rapid increase in the proportion of food delivery, we should not continue to expand just because the roof can still fit in it.
13.2 Case 2: Clinic/dental store, why is it a small commercial entry-level model?
13.2 Case 2: Clinic/dental store, why is it a small commercial entry-level model?
Customer portrait: The business hours are stable, the load is concentrated during the day, the boss makes decisions himself, and the requirements for cleanliness of the venue are high. The bill shows obvious energy consumption during the day, so it is suitable for a self-contained roof system.
Key judgment: This type of project is more suitable for early-stage teams to accumulate small commercial capabilities than complex factories, because it combines stable load, better repayment, and case display value.
Calculation logic: First identify its Schedule category, and then estimate power savings based on business hours and TOU structure; if there is a demand fee, handle it conservatively and do not overstate the demand improvement.
13.3 Case 3: Tourist villa/B&B, why the income must be ranged
13.3 Case 3: Tourist villa/B&B, why the income must be ranged
Customer profile: Living part of the time, renting part of the time for short periods, obvious off-peak and peak seasons, large load fluctuations during the day. Customers often have high electricity bills and are willing to pay for good-looking and low-disruption construction.
Key Judgment: This type of project cannot promise a payback period based on a fixed monthly load because occupancy rates, rental patterns and air conditioning usage intensity will all fluctuate.
Calculation logic: Make at least three income ranges: off-season, mid-season, and peak season, so that customers know the upper and lower limits of the system value.
13.4 Case 4: Light factory/warehousing, why a big roof may not be a good deal
13.4 Case 4: Light factory/warehousing, why a big roof may not be a good deal
Customer portrait: The roof area is large and the bill seems high, but the property rights, lease term, structural life, demand structure and boss's decision-making style are all more complex.
Key judgment: Teams are most likely to be attracted by "large area" and "large total price", but ignore that such projects have higher requirements on structure, demand, electricity price, repayment and contract capabilities.
Calculation logic: In addition to power saving, demand, voltage level, minimum charges, construction impact and payment ability must be taken into consideration.
13.5 Case 5: EaaS pilot, why choose the best customer first?
13.5 Case 5: EaaS pilot, why choose the best customer first?
Customer portrait: stable address, stable billing, clear load, willing to cooperate with information and monitoring, and good payment behavior. The goal is not to pursue short-term contract signings, but to verify the long-term service model.
Key judgment: The value of pilot projects lies in ‘learning to do’, not ‘doing more’. If the most complex customers are selected from the beginning, the team will mix model issues with customer issues and fail to learn real experience.
Calculation logic: In addition to project savings, it also depends on monthly service fees, customer willingness to continue paying, outage response, contract termination and residual value treatment.