Data Science, Strategy

Strategy for machine learning products in CMS Wire

I spoke with Kaya Ismail of CMS Wire about the need for large data sets and real customer problems to drive successful machine learning (ML) products for his coverage of Hubspot’s acquisition of Kemvi. Here’s an excerpt:

Holly Hester-Reilly of H2R Product Science believes HubSpot’s acquisition of Kemvi is a, “smart move for both teams.”

Hester-Reilly continued, “[By] combining DeepGraph’s algorithm and process for processing publicly available data with HubSpot’s data on real sales looks like a great opportunity to develop real-world machine learning solutions to solve real problems for HubSpot’s sales customers.

Check out the full piece over at CMS Wire for more details on why Hubspot’s acquisition of Kemvi is exciting news for artificial intelligence, machine learning, and big data product practitioners.

HubSpot Broadens AI Reach With Kemvi Acquisition

Data Science, Stakeholders

How to kill a bad product idea on Alpha blog

I talked with Mike Fishbein about techniques to identify bad product ideas and convince stakeholders when it’s time to end an initiative. Here’s an excerpt:

When working on a product that’s already launched, Holly emphasized the importance of looking beyond “vanity metrics”, such as page views and user counts, to truly understand if the product is valuable to customers.

Read the full article on the Alpha blog for more insights, including advice from Tami Reiss and Beth Temple:

How do you kill a bad product idea?