
Secured funding
CRM software firm InsideView has raised USD19m in a funding round led by Split Rock Partners, with participation coming from Emergence Capital, Foundation Capital and Rembrandt Venture Partners. InsideView is a business intelligence tool that aggregates sources including Facebook, Twitter and SEC filings.
InsideView claims it accesses more than 30,000 sources and is used by 13,000 companies to power their CRM. The San Francisco-based firm was founded in 2005 and is designed to use social media to boost sales figures. It informs businesses about past and potential customers, with data passed through APIs into the client’s data stream.
“This investment further validates the market opportunity for CRM Intelligence and provides us with the capital required to accelerate our market leadership in the space,” said Umberto Milletti, CEO of InsideView. “We received tremendous interest from investors who realize CRM Intelligence is required to drive results at every stage of the buying lifecycle — from the first marketing touch, through the sales process and through the account management and growth stage. The addition of Split Rock to our team brings additional cloud-based software expertise, and a long-term perspective. We welcome Jim to our board, and look forward to his contribution.”
Whitepapers
Related reading
Central banks best suited to issue digital currencies
By Aaran Fronda A recent report by the Official Monetary and Financial Institutions Forum (OMFIF) said that central banks rather than private ... read more
Instant payments: innovations inbound for corporates
In 2020, instant payments look set to continue their current trajectory to become the biggest trend in payments. While these schemes already offer numerous benefits to corporates, leveraging innovations such as APIs and request to pay will go some way to unlocking their full potential, argues Michael Knetsch
Obstacles exist for banks to meet ECB’s instant payments goal
The cost of joining instant payment platforms will be one of many hurdles banks and payment services providers must overcome to meet ... read more
Banks must be aware of “biases” in data used to train ML models
Financial institutions need to be conscious of biases in the historical data that is being used to train machine learning (ML) models, ... read more