Category: Marketing Data Science

  • You Ask, I Answer: Impressions as a PR Measurement?

    Summary In today's episode, I break down whether impressions are a valid metric for measuring public relations performance. Here's what this means for you. You'll discover why a single metric never tells the whole story and how combining top-of-funnel data with revenue-linked outcomes gives you a clearer picture of PR's true value. You'll also learn…

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  • You Ask, I Answer: PR’s Value to Non-PR Stakeholders?

    Del asks, “Which metric will be most important to communicate PR’s value to a non-PR audience?” Can’t see anything? Watch it on YouTube here. Listen to the audio here: Download the MP3 audio here. Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the…

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  • You Ask, I Answer: Primary Research vs. Secondary Data?

    Eric asks, “Under what circumstances would you support primary research vs using imperfect secondary data?” Can’t see anything? Watch it on YouTube here. Listen to the audio here: Download the MP3 audio here. Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.…

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  • You Ask, I Answer: Unifying Marketing Data?

    Jose asks, “What is your best advice about collecting data from different platforms? How to unified data for better reading? Is there any recommended tool?” Can’t see anything? Watch it on YouTube here. Listen to the audio here: Download the MP3 audio here. Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain…

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  • You Ask, I Answer: Marketing Reporting Frequency?

    Monica asks, “What frequency should our reporting be?” Can’t see anything? Watch it on YouTube here. Listen to the audio here: Download the MP3 audio here. Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video. In today’s episode, Monica asks, “What frequency…

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  • Almost Timely News: How Large Language Models Are Changing Everything

    Almost Timely News: How Large Language Models Are Changing Everything (2023-03-19) :: View in Browser 👉 Take my new free course on how to improve your LinkedIn profile and make yourself more appealing to hiring companies ➡️ Watch This Newsletter On YouTube 📺 Click here for the video 📺 version of this newsletter on YouTube…

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  • Mind Readings: Establishing Thought Leadership With Speed

    In this episode, we talk about the four factors of memory by Dr. Wendy Suzuki and how speed and agility lend themselves to thought leadership. Can’t see anything? Watch it on YouTube here. Listen to the audio here: Download the MP3 audio here. Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain…

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  • Almost Timely News, February 19, 2023: The Buyer’s Guide to Expertise

    Almost Timely News: The Buyer’s Guide to Expertise (2023-02-19) :: View in Browser 👉 Take my new free course on how to improve your LinkedIn profile and make yourself more appealing to hiring companies ➡️ Watch This Newsletter On YouTube 📺 Click here for the video 📺 version of this newsletter on YouTube » Click…

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  • You Ask, I Answer: Action Steps After Algorithmic Understanding?

    In this video, Christopher Penn explains the importance of having a clear hypothesis to test when analyzing data for social media algorithms. He provides examples of how testing a hypothesis can help determine whether or not to take certain actions, such as what days to post on Instagram or which hashtags to use on TikTok.…

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  • You Ask, I Answer: Proving Algorithmic Understanding?

    Christopher Penn discusses the importance of testing assumptions in social media algorithms, using machine learning and data science tools. To understand the impact of hashtags on reach and engagement, for example, one would download all of their Twitter data and run a statistical analysis to determine if there is a significant effect. Penn emphasizes the…

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