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Banyan, a platform for product purchase data that allows customers such as banks, fintechs, hotels, and other businesses to automate expense management, has raised $43 million in Series A funding—$28 million in equity and $15 million in debt—led by Fin Capital. $100 million.
According to CEO Jehan Luth, Banyan’s headcount will increase from 46 workers to 50 by the end of the year thanks to the fresh capital. Infrastructure development and workforce development will be funded with the capital, as well as product research and development, he said in an interview. Luth mentioned that the funding round puts Banyan in an excellent position to grow, given the company's $53 million in accumulated funds.
Banyan, a software analytics company, is making big strides in its mission to become the standard for item-level purchase data. In fact, just this week Banyan announced $43M in funding led by New Enterprise Associates (NEA) with participation from Lightspeed Venture Partners, GV (formerly Google Ventures), and strategic investor Intel Capital.
This new capital will be used to grow its network of item-level purchase data. CEO Jehan Luth told The Trade that the “new capital will be put toward product research and development, infrastructure growth and hiring talent.” With this new funding, Luth tells
What Banyan Does
Banyan’s solution is a software analytics tool that collects item-level purchase data from retailers and then uses machine learning to segment the data and identify insights, such as what products are being purchased together. This solution allows retailers to tie their item-level purchase data to the products they sell online and then use that data to provide shoppers with personalized recommendations, as well as provide brands with more data to inform their decision-making.
The software collects data from retailers using a network of data collection agents, which are essentially software robots that crawl the websites of retailers. Banyan’s solution, however, is not limited to crawling websites; it can also pull data from apps and mobile websites.
Where Banyan Is Now and Where It’s Going
Banyan has seen significant growth since it was founded in 2015, especially in terms of the number of retailers they’re able to collect data from. In fact, Banyan now collects item-level purchase data from more than 2,000 retailers. In terms of the insights the Banyan tool provides, the company has been focused on their product recommendation functionality.
In fact, Banyan has made product recommendations available to 4,200 retailers globally, with plans to expand product recommendation functionality to 10,000 retailers by the end of the year. Banyan has also recently made headway into the West Coast retail market through partnerships with retailers like Amazon, Kohl’s, and Target.
Why This Matters For Brands And Shoppers
As mentioned above, the data collected by Banyan is item-level data, which tells brands exactly what products are being purchased together, as well as the quantities of each product. This means that brands can now make better data-driven decisions, such as which items to stock and how much of each product to order.
As Banyan expands its network of retailers, it will enable brands to take a more holistic view of what’s happening in the marketplace. For example, Banyan’s data is also used to identify new product categories at retailers and help brands identify new product categories and understand how those product categories are being bought at other retailers.
In addition to enabling brands to make better data-driven decisions, Banyan’s data also allows retailers to provide shoppers with more personalized recommendations, which can help shoppers make more informed buying decisions.
How Banyan Helps Shoppers Make Better Purchasing Decisions
Banyan’s data is also used by retailers to target shoppers with personalized messaging and recommendations based on their purchase history. Banyan leverages its item-level purchase data to help retailers identify the products that certain shoppers have purchased in the past and then use that data to help target shoppers with personalized messaging and recommendations.
This personalized messaging can include product recommendations, special customer rewards, or deals or discounts. For example, if a shopper has purchased a blender, a knife set, and a spatula, Banyan’s solution can suggest additional products that the shopper may want to purchase, such as a cutting board, a spatula holder, or other kitchen tools.
Banyan’s Biggest Takeaway: The Importance Of Having Quality Item-Level Data
Banyan’s biggest takeaway from its new capital raise is the importance of having quality item-level data. Banyan has built its network of retailers on the promise of providing quality data. Banyan ensures the quality of data collected by each of its data collection agents with a series of checks and balances.
For example, Banyan uses a combination of machine learning and human review to ensure that the data collected is accurate. Furthermore, Banyan also makes sure that the data it collects is as current as possible by leveraging its data collection agents to crawl websites in real time. Banyan’s agents also have the ability to “wake up” in the middle of the night to crawl retail websites and update the data Banyan has in its system.
Banyan is a company that is truly making a difference for retailers and brands, as well as shoppers. With its new capital, Banyan will be able to scale its solution to more retailers and further its mission to become the standard for item-level purchase data.
This will allow brands to make better data-driven decisions and provide more personalized recommendations to shoppers. Indeed, Banyan has come a long way since its founding in 2015. With this new capital, Banyan will be able to scale its solution to more retailers and further its mission to become the standard for item-level purchase data.
Many consumers are rethinking brand loyalty and tightening their belts, Luth said, demurring on Banyan's revenue numbers. A key for retailers to offer real savings, according to Luth, is item-level data, which enables retailers to manage inventory levels and drive sales retention.
With financial institutions investing in big data, consumers will see increased digital engagement, and retailers will be able to manage inventories and generate new sales revenue streams.