Webinar: 7 Common Analytics Tracking Pitfalls and How to Avoid Them

Written by Indicative Team


The accuracy and usefulness of your organization’s data depends on developing a tracking plan to define and monitor the data you track. Without a solid, well-documented plan, you run the risk of corrupted and confused data—meaning your analytics tools become useless or, worse, you end up making critical business decisions based on bad data.

That problem was the subject of a recent webinar our team put together along with our friends at Iteratively. You can watch the webinar below followed by an expert how-to on building one for your business.

Tracking Plan Quote

What You Can Expect to Take From This Webinar:

  1. How to identify common analytics challenges early on
  2. How to develop a tracking plan and analytics tracking process that can help solve these challenges
  3. How to define who owns the tracking plan, and best practices on how to collaborate among different teams within a single org
  4. How a tracking plan improves analytics
  5. Get set up for success downstream
    • How to build a data set for customer analytics
    • How to analyze your data to get customer insights specific to your use case
    • Why you need customer analytics

For more information on how to build a data tracking plan, we strongly encourage you head over to our support documentation here.

Watch the webinar recording by completing the form below:

Meet the Speakers:

Padric Headshot

Padric Gleason Gonzales – Customer Success Manager, Indicative

Padric works with Indicative’s diverse customers to understand their data requirements and translate customer behavioral data into actionable insights. He has more than 6 years of experience working with high growth technology companies in the U.S. and Europe, and he has an MBA in International Business from St. Mary’s University in London.


Patrick Headshot

Patrick ThompsonCo-founder & CEO, Iteratively
Co-founder and CEO of Iteratively, a SaaS platform for helping teams define, track, and validate their analytics. Previously led teams at Atlassian.