Forwrd
Financials
Estimates*
USD | 2022 | 2023 |
---|---|---|
Revenues | <1m | 1.1m |
% growth | - | 110 % |
Date | Investors | Amount | Round |
---|---|---|---|
- | N/A | - | |
* | $3.5m | Seed | |
Total Funding | AUD5.4m |
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Recent News about Forwrd
EditForwrd.ai is a startup that offers a no-code predictive scoring software. This software is designed to help businesses prioritize their sales-ready prospects and identify customers who are at risk of leaving. The software uses artificial intelligence (AI) to analyze a company's data and build an accurate scoring model, which can then be used to identify high-value prospects and at-risk customers.
The company's software is primarily targeted at go-to-market teams, which are teams within a company that are responsible for bringing a product or service to market. These teams can use Forwrd.ai's software to identify and prioritize leads more quickly and accurately, detect product-qualified leads to improve sales efficiency, and prevent customer churn by identifying and understanding the factors that drive customers to leave.
Forwrd.ai operates in the predictive analytics market, which is a sector of the broader business intelligence market. The company's business model is based on a software-as-a-service (SaaS) model, where customers pay a recurring fee to use the software.
The software integrates with a wide range of data sources, including Salesforce, HubSpot, Outreach, Snowflake, and Redshift. This cross-cloud integration allows the software to analyze data from a wide range of sources, providing a more comprehensive and accurate scoring model.
In summary, Forwrd.ai offers a no-code predictive scoring software that uses AI to help go-to-market teams identify high-value prospects and at-risk customers. The company operates in the predictive analytics market and makes money through a SaaS business model.
Keywords: Predictive Scoring, No-Code Software, Artificial Intelligence, Go-to-Market Teams, Lead Prioritization, Customer Churn Prevention, Predictive Analytics, SaaS Business Model, Cross-Cloud Integration, Data Analysis.