Using data to make better decisions faster helps startups improve product development in the crowded SaaS space, identify hidden market opportunities, and get things done with fewer false steps, important priorities because These startups want a piece of the booming SaaS market, which is forecast to grow by 19.7%. % over the next six years.
Singapore- and California-based startup Houseware has built a platform that ingests data to help startups in those endeavors. Today Housewares is emerging from stealth with $2.2M led by Tanglin Ventures Partners with participation from GTMund and Better Capital, as well as execs from some of the most iconic, scaled-up SaaS companies around, including Snowflake, Superhuman, Stripe Angel investors. , Zendesk and others.
When Housewares co-founder and CEO Divyansh Saini was at data analytics company Atlan, he had the opportunity to work directly with companies like WeWork, Postman and Plaid. Saini looked at how data teams talked about, say, metrics and what revenue teams demanded from those numbers.
,[Traditionally,] The data team sits away from the problems and treats it as a service task,” said Saini, who spends weeks modeling data for particular use cases.
HouseWare was founded in 2021 by Shubhankar Srivastava and Saini with a simple question: “What will it take to flip the value of the data warehouse from data and engineering teams to the revenue function inside organizations?”
Houseware, which provides an easy-to-use, no-code interface for operations and revenue teams, wants to bring SaaS companies closer to using data more efficiently across their daily use cases across businesses.
Houseware allows users, for example, in the customer success team, to provide insights on product pricing on the go, which in turn can be used by finance teams as they consider how to change those prices. Yes, Saini explained.
This is important because while products like Snowflake have made it easier to work with massive amounts of data over the past half-decade, the revenue teams of most companies are still untouched by that paradigm shift, according to Saini.
Houseware’s target customers are SaaS enterprises with more than 1,000 employees. The company says its end users are revenue, marketing and sales groups as well as marketing and finance analysts. Housewares tracks the percentage of active employees at companies using its platform as a key metric.
Saini, who likes to speak about “democratic access,” said, “We’ve seen 30% of employees in the organization be regular users of housewares.” This has included users from public SaaS companies, and the fastest growing edtech and SaaS companies over the past few quarters.
Saini told TechCrunch that Housewares considers Clari and People.AI as its closest competitors, along with some horizontal platforms like ThoughtSpot. He also pointed out that companies like Retool, which raised $45 million last year at a $3.2 billion valuation, and Streamlit, which acquired Snowfac for $800 million, have made the space popular for developers and data scientists, respectively; Houseware aims to do the same for non-technical users.
Saini told TechCrunch that it is building a layer of intelligence on top of customer data using machine learning (ML) and artificial intelligence (AI) algorithms to solve use cases such as identifying the risk of churn. Has been” and “Creating Intelligent Account Health Score” at the top of the customer data. Saini said that the startup is looking to roll these out for its customers in the second and third quarter of 2023.
The company also plans to grow its team, hire for go-to-market roles in the US, and double down on its partnerships with Snowflake and DBT Labs.
“There is immense pressure on the revenue functionaries to find avenues for development,” Saini said in a statement. “Investors are focused on solid unit economics and a path to profitability, so a lot will depend on hard-core, disciplined, top-notch business execution.”
“The focus has been on data and metrics over the past six months in SaaS businesses, with board meetings now demanding answers to customer acquisition costs, which lead channels are working best,” Saini said in his statement. or how the product churns usage links.” statement.