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5 Machine Learning Lessons for Product Managers

Mind the Product

Artificial intelligence (AI) is probably the biggest commercial opportunity in today’s economy. We all use AI or machine learning (ML)-driven products almost every day, and the number of these products will be growing exponentially over the next couple of years. What does it mean for us as product managers?

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Revenue Goals are Not Company Strategies

Mironov Consulting

  (For fun, let’s call those things strategies.) Pure revenue may be helpful for the Sales organization, since they probably need to hire 35% more account teams each year.  ” And this is usually wrapped around an organizational ownership fistfight about who “owns” company-level strategy

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We Have To Support Every Line of Production Code Forever

Mironov Consulting

  The upside (for the sales team) is huge, and the cost (for product/engineering/support) is diffuse.    Closing this $480k/year license deal is highly visible to the exec team and Board.  Their market strategy team realizes they need one more field mapped.    Far away. 

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The SaaS Manager’s Toolkit: Top Alternatives for Google Analytics for 2024

Userpilot

By tracking specific groups of users based on shared characteristics or behaviors, you can understand how different cohorts interact with your product and improve retention strategies. The platform’s no-code capabilities make it accessible for teams without extensive technical expertise. Shared Spaces for team analysis.

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Product Design: Let’s get Emotional

Mind the Product

Indeed startups are often launching with or driving the development of new technologies. Ripple , for example, is using blockchain technology to disrupt the global payments market and Babylon Health is using artificial intelligence to drive its consumer health proposition. A new Type of Consumer.

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Tempting Thoughts to A/B Test In Trying Times

Split

Personally, my bank has a really helpful process. You might discover that you’re saving time for both your team and your customers. We strongly recommend that you verify the claims of your vendors, or A/B-test on-line what your machine learning team has tested off-line. , “Agent!”, “Speak to a real person!!!”

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Embedded Analytics Examples and Use Cases in 23 Different Industries

Reveal

Banking CRM Crypto Education Finance Healthcare Insurance IT Manufacturing Real Estate Retail Supply chain Telecommunications Security Logistics and delivery Marketing Airlines Hospitality Weather forecast Agriculture SaaS Government Sports. Banking : Deliver great benefits to customers and employees alike. See Reveal in Action.