The Software Pricing Quadrant with Daniel Barber (Datanyze)

This week, the Bowery Capital team hosted Daniel Barber, SVP of Sales & Customer Success at Datanyze, to discuss “the Software Pricing Quadrant.” Datanyze is a sales intelligence platform that arms customers with deep "technographic" data: information regarding companies' technology stacks and changes in its composition over time. Datanyze's insights are leveraged by any type of role in a variety of ways, but they are valued particularly highly by B2B marketers & salespeople seeking the right timing to approach new leads or an edge to help close their best accounts. In this podcast episode, Daniel joins us to discuss the Software Pricing Quadrant, a logical framework he has developed that one can use to weigh various pricing models, and the key factors at play when considering each. Having held a variety of sales leadership roles, he has dedicated an impressive amount of time thinking about the costs and benefits of different software pricing methodologies, and shares with us today his thoughts on how best to understand and apply the Quadrant in the real world.

Daniel Barber is the SVP of Sales & Customer Success at Datanyze, a role he took on after serving as VP of Sales at the company for 7 months. Prior to Datanyze, he was VP of Revenue at Node.io (an account-based sales intelligence platform) and served in various sales leadership roles at ToutApp, including Senior Director of Pipeline Development. Daniel began his career in software customer acquisition at Responsys, which was acquired by Oracle in 2013, about a year into his joining the company. He has also served as an advisor to many startups, including Chorus.ai, a sales call analytics & intelligence tool that has raised over $20MM to "open up the black box of sales calls" using AI and NLP. Daniel's deep experience across a range of SaaS companies and his particular specialization in sales data & intelligence, make him a perfect guide to software pricing considerations, the topic of today's podcast.