A housekeeping startup, the data science introduction

Sajjad Hussain
Mar 13 · 4 min read
Photo by Toa Heftiba on Unsplash

Problem statement

A startup wants to provide housekeeping services, in order to find out the profitability many questions raise

  1. How we determine the workload of the family.
  2. The area of ​​the house and the income of the home.
  3. The bathroom cleaning, cloakroom tidying, and other useful services required in a family
  4. The carpets and range hoods and other stuff
  5. Time-specific, for example before a festival or any family event.
  6. How many people have to need these services
  7. How many customers are willing to pay for your services

Research and Development

Especially for these types of services, there are some customary practices in its subdivisions like confinement, nanny, part-time labor, and elderly care. There are corresponding market prices in a city, these basic tasks can be solved through preliminary research. Detail research must be carried out in the early stages of designing housekeeping services for example

  • Services already available
  • What are the common user searches on the internet?
  • What are products domestic industry offers according to your services
  • How you test your own services
  • What impact of price on your offered services

There are trade-offs between service grade and popularization in order to stand out in market competition, and specific types have specific operating methods. You need to find out the current market situation directly from users and competing services. There is no need to wait for the business to go online before letting users fill in, this kind of track selection tests the service and operational business capabilities.

In fact, in the competition, satisfying the basic needs of users is the first priority. After satisfying the basic needs, some special services can be provided according to the supply capacity of the platform such as nanny credit and price concessions.

What you must avoid

If you start up not have enough supply, and your startup has no ability to provide large-scale, high-quality, personalized, and low-cost services then there is no need to do data exploration, particularly for any specific service because it is useless for your startup. The startup has its own upper limit of supply capacity and its own service positioning. There is no need to meet particularly tricky user needs.

What you have to follow

The first thing to be solved is not the problem of personalized demand, but the problem of regional coverage, if there are not enough services in the user demand area, then you can consider that area is absolutely important, and you need to collect all of such user searches and the most common sales of housekeeping items in this particular region, users will compromise, either because there are no more services to choose from on your target region, or because the price is very favorable, or because the demand is very high.

In housekeeping services, cleaning services are quite standardized, and there is an opportunity to make low-price strategies, do some additional services, and increase the volume without increasing the price, at this time, there is no need to study the details of the user’s house area, furniture, etc., but provide an upper limit that does not increase the price is enough.

Promotion strategies

If you can find sales channels with intensive niche users, you can directly and accurately push personalized services that meet the niche, in this case, you can directly use the marketing channel as a label to identify the niche user group, and further analysis can be done later

If you use mass advertising, you first attract users to consume once, get users in, and then consider pushing for second purchases, incremental sales, or cross-selling, after the first consumption record, not only is the database but also leaves a follow-up opportunity for secondary consumption.

In the case of the referral method, the referrer can directly guide the user to purchase a certain main product for the first time and the referrer’s behavior is to redirected + product+ activity.

Data does not fall from the sudden airplane, but data is generated from business processes. If business processes are not well-designed, services are not attractive, promotion is not focused, operations are not planned, therefore data is not generated. Do not expect data to be formed at one time, but in cooperation with operational activities, the range of data available will be greatly increased.

How you make your own big data

  • Search key information (address, type of needs, whether to live in) when the user first contacts, and first make the first match.
  • Search slightly more personalized information, and match products
  • Search user language requirements and house area.
  • Summarizes the regions and salary of those e users who have many repeated purchases

Data Prophet

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