GURUFOCUS.COM » STOCK LIST » Technology » Software » DeepSpatial Inc (OTCPK:DSAIF) » Definitions » COGS-to-Revenue

DSAIF (DeepSpatial) COGS-to-Revenue : 0.48 (As of Mar. 2024)


View and export this data going back to 2021. Start your Free Trial

What is DeepSpatial COGS-to-Revenue?

DeepSpatial's Cost of Goods Sold for the three months ended in Mar. 2024 was $0.16 Mil. Its Revenue for the three months ended in Mar. 2024 was $0.33 Mil.

DeepSpatial's COGS to Revenue for the three months ended in Mar. 2024 was 0.48.

Cost of Goods Sold is directly linked to profitability of the company through Gross Margin. DeepSpatial's Gross Margin % for the three months ended in Mar. 2024 was 52.45%.


DeepSpatial COGS-to-Revenue Historical Data

The historical data trend for DeepSpatial's COGS-to-Revenue can be seen below:

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

* Premium members only.

DeepSpatial COGS-to-Revenue Chart

DeepSpatial Annual Data
Trend Jun20 Jun21 Jun22 Jun23
COGS-to-Revenue
- - - -

DeepSpatial Quarterly Data
Dec19 Mar20 Jun20 Sep20 Dec20 Mar21 Jun21 Sep21 Dec21 Mar22 Jun22 Sep22 Dec22 Mar23 Jun23 Sep23 Dec23 Mar24
COGS-to-Revenue Get a 7-Day Free Trial Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only - - - - 0.48

DeepSpatial COGS-to-Revenue Calculation

DeepSpatial's COGS to Revenue for the fiscal year that ended in Jun. 2023 is calculated as

COGS to Revenue=Cost of Goods Sold / Revenue
=0 / 0.014
=0.00

DeepSpatial's COGS to Revenue for the quarter that ended in Mar. 2024 is calculated as

COGS to Revenue=Cost of Goods Sold / Revenue
=0.155 / 0.326
=0.48

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.


DeepSpatial  (OTCPK:DSAIF) COGS-to-Revenue Explanation

Cost of Goods Sold is directly linked to profitability of the company through Gross Margin.

DeepSpatial's Gross Margin % for the three months ended in Mar. 2024 is calculated as:

Gross Margin %=1 - COGS to Revenue
=1 - Cost of Goods Sold / Revenue
=1 - 0.155 / 0.326
=52.45 %

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

A company that has a moat can usually maintain or even expand their Gross Margin. A company can increase its Gross Margin in two ways. It can increase the prices of the goods it sells and keeps its Cost of Goods Sold unchanged. Or it can keep the sales price unchanged and squeeze its suppliers to reduce the Cost of Goods Sold. Warren Buffett believes businesses with the power to raise prices have moats.


DeepSpatial COGS-to-Revenue Related Terms

Thank you for viewing the detailed overview of DeepSpatial's COGS-to-Revenue provided by GuruFocus.com. Please click on the following links to see related term pages.


DeepSpatial Business Description

Traded in Other Exchanges
N/A
Address
77 King Street West, Suite 3000, Toronto, ON, CAN, M5K 1G8
DeepSpatial Inc is an artificial intelligence, technology SaaS company at the forefront of geospatial artificial intelligence and geographic informational systems, specializing in providing robust location intelligence solutions for transforming existing location data into business outcomes. AI powered solutions to businesses by leveraging the power of geospatial data. The company has built products that target four specific customer needs across industry verticals. These are geodemographic customer profiling, price recommendation engine, inventory management and supply chain analytics, and sentiment monitoring to measure and improve brand health.