In this episode of In-Ear Insights, Katie and Chris review a case study of a client who was missing attribution data on more than 75% of their website visitors. When your data is that dirty, making good, data-driven decisions is all but impossible. Watch or listen as they talk through what happened and some ways […]
Read More… from {PODCAST} In-Ear Insights: Google Analytics Audit Case Study Review
In this week’s In-Ear Insights, Katie and Chris answer a question from the MarketingProfs B2B Forum on how YouTube analytics data can be used for B2B marketing – and how YouTube itself fits into your B2B marketing strategy. Watch and listen for tips on how to do YouTube research to inform your YouTube strategy as […]
Read More… from {PODCAST} In-Ear Insights: YouTube Analytics for B2B Marketers
In this week’s In-Ear Insights, Katie and Chris answer a very popular question: what do you do when the numbers don’t add up? When your Facebook results conflict with the data in Google Analytics, when your CRM doesn’t match your marketing automation, when accounting asks you why your forecasts were wrong – what do you […]
Read More… from {PODCAST} In-Ear Insights: Dealing With Conflicting Results in Marketing Analytics
In this episode of In-Ear Insights, Katie and Chris tackle a listener question: what do you do when a key stakeholder asks for metrics that don’t exist? How do you come up with answers that satisfy the intent of the question, and how do you present to the stakeholder when something just isn’t possible? Tune […]
Read More… from {PODCAST} In-Ear Insights: Asking for Numbers That Don’t Exist
In this episode of In-Ear Insights, Katie and Chris discuss recent privacy changes, iOS 14.5, why Google wasn’t freaking out like Facebook was, and how Google can promise to intelligently append/fill in missing third-party data where other adtech platforms cannot. Find out why you’ll be spending more money in Google Ads in the coming years, […]
Read More… from {PODCAST} In-Ear Insights: Google Analytics and Third Party Data
In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the similarities and differences between A/B testing and clinical trials. What aspects should marketers keep from the life or death world of healthcare, and what aspects don’t apply to the realm of marketing? Learn some best practices for A/B testing when […]
Read More… from {PODCAST} In-Ear Insights: Best Practices for A/B Testing for Marketers
In this episode of In-Ear Insights, Katie and Chris tackle the disconnect between what marketers think is hot versus what customers actually want. Do people really want more time on their screens? Do people need more meetings on their calendars? Watch or listen to find out the results of a survey and how content strategy […]
Read More… from {PODCAST} In-Ear Insights: Content Formats and Reducing Friction
In this week’s In-Ear Insights, Katie and Chris evaluate what marketing tactics are worth doing and not doing, based on data, experience, and company values. Learn how we decide what events to speak at, what podcasts to guest on, and more. You’ll see a practical use for attribution analysis when it comes to making very […]
Read More… from {PODCAST} In-Ear Insights: Data-Driven Marketing Tactics
In this episode of In-Ear Insights, Katie and Chris talk about the devil that is viewthrough conversions. What are they? Why do advertising networks rely on them so heavily? Do they have a place in your marketing analytics? Learn why viewthrough conversions can be greatly misleading and what alternatives exist for robust, real measurement of […]
Read More… from {PODCAST} In-Ear Insights: Viewthrough Conversions and Attribution Analysis
In this week’s In-Ear Insights, Katie and Chris tackle an unusual situation. What happens when data doesn’t have answers? What happens when data simply doesn’t provide any useful insights beyond confirmation of what you already knew? We review what your options are, and what might have gone wrong that led to the situation. If you’ve […]
Read More… from {PODCAST} In-Ear Insights: What to Do When Data Doesn’t Have Answers
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