Show all categories
Interpretation of data to choose the best location

The choice of the sweet spot It's not just limited to saying:

We need 100,000 people in the target region.

It is essential to conduct an in-depth analysis, decomposing the main variables that influence the performance of a unit.

Let's imagine the case of a network where A store considered 'good' earns R$ 100,000 a month.

How many sales are needed to reach that number?

Imagining an average ticket of R$100, it will be a thousand monthly sales;

Considering 26 days of operation, that's around 38 sales per day.

In this scenario, the ideal location must have the potential to deliver this volume, taking into account the penetration of the offer, the purchase frequency, and the target population necessary to enable the expected billing.

Let's dissect each part, transforming it into variables and understanding the factors that influence the result.

Basic variables

Desired monthly billing

R$ 100,000.00 per month

Average ticket (average price per sale)

R$ 100.00

Operating days per month

26 days - closed on Sundays

Number of monthly sales required

Desired Billing/Average Ticket = 1,000 sales

Number of daily sales required

Number of monthly sales/business days in the month = 1,000/26 = 38 daily sales

Market and location factors

For attain The 38 customers/day (which convert into 1,000 sales/month and R$ 100 thousand/month), we must consider:

Target population (potential market)

It is the group of people that the store can reach within its area of influence (for example, neighborhood, city, or region).

Penetration of supply

It represents the fraction/percentage of that target population that will actually shop at the establishment.

Example: If there are 10,000 people in the area of influence and the store manages to reach 10% of them, then the total number of potential customers would be 10,000×0.10 = 1,000 people.

Purchase frequency

Average number of purchases per person in a given period, for example, per month.

Even if there are 1,000 people willing to buy, it is relevant to know How many times each purchase in the month.

Example: If each person buys twice a month, this doubles the monthly amount of sales for the same group of people.

Effective conversion

Finally, there is the actual conversion rate, which may be less than 100% within the interested audience.

However, in the context of physical stores, penetration is often taken as a simplified form of estimated conversion.

Relationship between market variables and revenue

We can assemble a simplified model, where:

  • PT= Total target population
  • α\ alpha = Supply penetration (percentage of people who actually buy)
  • FC = Purchase Frequency (average amount of purchases per person within the month)
  • TM = Average Ticket (average amount of each purchase)

PT x α x FF x TM = R$ 100,000

That is, the combination of Number of people (PT), pervasiveness (α\ alpha) and frequency (FC) must result in 1,000 purchases per month to generate the desired revenue (since each purchase is worth R$ 100.00).

Evaluating the commercial point

Population density in the catchment area

Are there enough people to generate that traffic of 38 buyers a day?

Socioeconomic profile

These people Do they have purchasing power compatible with the average ticket of R$ 100.00?

Competition

Are there many competitors offering similar products?

The presence of competition decreases the probability of penetration (α\ alpha) if the market is saturated.

Consumption habits and frequency

Fast consumer products may have more frequent purchases (higher HR).

High-value products with low recurrence require a larger population (PT) or a larger penetration (α\ alpha).

Accessibility and convenience

The location must be easy to access and visible for the target audience, increasing the likelihood of attraction and purchase.

Practical application

Breaking Billing Invoicing Into Sales:

  1. Revenue target (R$ 100 thousand) → Converted into monthly sales (1,000) for the average ticket (R$ 100).
  2. Number of daily sales (about 38) → depends on the number of open days (26 in the example).
  3. Ideal location → requires analysis of the target population, penetration, and purchase frequency, in addition to competition and accessibility.

R$ 100 thousand/month → Average ticket R$ 100 → 1,000 sales/month → 38 sales/day (within 26 business days).

Feasibility assessment

To make 38 daily sales, we need to check if there is a sufficient flow of people or if the business model can attract that amount of buyers, taking into account penetration and purchase frequency.

Local market sizing:

How many people can potentially buy?

What% will actually be converted into customers (penetration)?

How many times a month will each customer buy (frequency)?

Location decision:

It must be in line with consumption habits, flow intensity in the area, and income profile from the public.

Places with high traffic but disinterested audiences or without adequate purchasing power may not meet their billing goals.

Example of applying the equation

  1. Target population (PT): 5,000 people in the catchment area.
  2. Penetration (α\ alpha): 10% (500 people will buy in the month).
  3. Frequency (FC): 2 purchases per month per person.
  4. Ticket (TM): R$ 100.00.

PT×α×FC=5,000×0.1×2=1,000

In this example, the variables “matched” exactly the sales/revenue goal.

If the reality is different (for example, penetration of only 5% or the frequency of 1 purchase per month), there will be a sales deficit.

This type of reasoning follows an advanced logic for the assessment of viability in each location.

Did you like the material but were too lazy to assemble all that logic?

Talk to Expanda AI

Did this article help you?