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Omnichannel Analytics Guide for SaaS Companies

Userpilot

Omnichannel analytics enable teams to get a 360 view of user behavior at different touchpoints of the customer journey. In particular, it covers: What omnichannel analytics are Why it’s important to track How to implement your omnichannel analytics strategy Omnichannel analytics tools Let’s get right into it!

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14 Zendesk Integrations SaaS Companies Need in 2023

Userpilot

The article explores the best Zendesk integrations for: Customer support Customer feedback Productivity Email and social media communication Analytics and reporting Let's get right to it! Zendesk communicates with external apps via API, so creating integrations is easy. How many apps does Zendesk have?

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The difference between product analytics and business intelligence tools — and why you need both

Mixpanel

In 2019, industry-leading Business Intelligence tools (BI tools), Looker and Tableau, were acquired by Google and Salesforce for over $18 billion combined. These massive deals show that BI tools and data warehouses are a powerful combo that companies across the globe are incorporating into their tech stacks.

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The Ultimate Guide to Google Analytics 4 for UX Designers and Business Owners

UX Planet

Master Google Analytics 4 for user behavior analysis, UX design optimization, and enhanced website performance to improve sales. Hi there, I was looking into Google Analytics 4 and found an article by Alice Emma Walker. If you know about Universal Analytics , it’s going away on July 1, 2024. It’s six years old.

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Products for Product People: Best Practices in Analytics

Speaker: Andrew Wynn, Senior Product Manager, Looker

As a product manager, you know how helpful custom tailored data solutions can be to doing your job well. But proper data analytics solutions take work to deliver - it's not as simple as just building a dashboard. Learn product analytics best practices from Andrew Wynn, Product Manager at Looker.

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Product Love Podcast: Daniel Mintz, Chief Data Evangelist at Looker

ProductCraft

This week on Product Love, I sat down with Daniel Mintz, the chief data evangelist at Looker, a data exploration and discovery business intelligence platform. He’s worked as the head of data and analytics at Upworthy and as a.

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Tristan Handy on the changing face of the data stack

Mixpanel

From early computer systems (basically operating on arithmetic) to the priests of Oracle and IBM. From siloed systems to open source technology that bridges the gap between data engineering and data analysis. That birthed a whole new suite of job titles and tools. From punch cards and filing drawers to early computers.

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Iterate Your Way to a Top Analytics Product Experience

Speaker: Richard Cheng, Associate Product Manager, Mark43

Tune in to this webinar to hear how Mark43 Product Manager Richard Cheng went about researching, prototyping, and iterating to deliver analytics and business intelligence tools to police departments, emergency call centers, and other public safety agencies, bringing Mark43 users a positive and effective product experience.

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How Product Managers Can Learn to Love Reporting

Speaker: Eric Feinstein, Professional Services Manager, Looker

Eric Feinstein, Professional Services Manager at Looker, has done workshops with product managers who are looking to add effective reporting. He will use the example of a product manager of a learning management software system and how she would go through the process of defining reporting for users of the product.

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How and Why: Embedded Analytics Interfaces For Your SaaS Product

Speaker: Sam Owens, Product Management Lead, Namely Platform

Sam and Jessica faced a problem that many product managers face: their customers wanted better analytics and reporting, but analytics wasn’t the core function of the SaaS product Sam and Jessica manage. Evaluated their options for building a solution themselves or buying something.

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The Practical Guide to Using a Semantic Layer for Data & Analytics

How to achieve speed of thought query performance and consistent KPIs across any BI/AI tool, such as Excel, Power BI, Tableau, Looker, DataRobot, Databricks and more. How to enable data teams to model and deliver a semantic layer on data in the cloud.