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The ultimate marketing technology stack for 2019

Intercom, Inc.

Known as the Martech 5000 — nicknamed after the 5,000 companies that were competing in the global marketing technology space in 2017, it’s said to be the most frequently shared slide of all time. The reasons for this growth – high-velocity economics of software innovation, the migration of money from old media to new media, etc.

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What Google’s and SalesForce’s respective acquisition of Looker and Tableau Software means for…

Piyanka Jain

What Google’s and Salesforce’s respective acquisition of Looker and Tableau Software means for CIO’s The BI analytics tool space is consolidating to compete against Microsoft’s ensemble of Business Analytics(BA) products which promises to solve for the entire workflow?—?data last week and Salesforce’s $15.3b

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How to Build Your Dream Analytics Stack

Indicative

A strong analytics stack is foundational to being able to make sense of it all. Investing in a robust and efficient analytics stack is a necessity for a modern business in order to compete. What Technology Do You Need in Your Stack? What Technology Do You Need in Your Stack? Data Tracking and Collection. Major Players.

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SaaS Reporting Guide: Tools & Metrics

Userpilot

With companies relying entirely on data, it’s common sense to carry out SaaS reporting. TL;DR SaaS reporting helps to track key metrics and inform the right decisions backed up with data. TL;DR SaaS reporting helps to track key metrics and inform the right decisions backed up with data.

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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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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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Cross-Platform Analytics Guide for SaaS Companies

Userpilot

Tracking cross-platform analytics is essential for product teams to see a complete view of customer behavior. TL;DR Cross-platform analytics is the activity of tracking and analyzing user behavior across multiple platforms or devices. What is cross-platform analytics?

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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.