Category: Marketing automation

  • You Ask, I Answer: Prioritizing Your MarTech Stack?

    Ted asks, “How do you prioritize building an organization’s MarTech stack? How do you build a foundation that you can add to over time?” One of the biggest pieces is going to be your database environment, followed by your overall tech platform. Many companies have a major tech provider, and that puts some constraints on…

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  • You Ask, I Answer: Digital Ecommerce Platform Recommendations?

    Summary In today's episode, I walk through recommendations for e-commerce platforms tailored to selling digital goods, comparing options like Gumroad, Stripe, PayPal, and LearnDash along with marketing and CRM tools that complement them. Here's what this means for you. You can pick the right platform for what you're actually selling without overpaying in transaction fees…

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  • You Ask, I Answer: Why Not to Buy Email Lists?

    Kim asks, “What advice would you give to persuade my CEO NOT to buy an email list?” Buying a third party list is a bad idea in today’s environment because your deliverability is contingent on how many people report your email as junk. The moment you use a third party list, your reputation gets trashed…

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  • You Ask, I Answer: Marketing Data Science Hypothesis Formation?

    Jessica asks, “I struggle with forming hypotheses. Do I need more data to get better?” Data probably isn’t the problem. A well-defined question you want the answer to is probably the problem. Consider what a valid hypothesis is, within the domain of marketing data science: a testable, verifiably true or false statement about a single…

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  • You Ask, I Answer: Choosing Marketing Data Science Variables?

    Jessica asks, “As a Data Scientist for marketing, how do you decide which variables are important?” Generally speaking, feature selection or variable/predictor importance is the technique you’d use to make that determination – with the understanding that what you’ll likely get is correlative in nature. You then have to use the scientific method to prove…

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  • You Ask, I Answer: New Insights from Old Data with Marketing Data Science?

    Balabhaskar asks, “How can we use marketing data science to get more insights from the same old data or the few data points available because of privacy laws?” Blending of new data with old data, especially credible third party data is one solution. The second solution is feature engineering. Both are vital parts of exploratory…

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  • You Ask, I Answer: Removing Dead Emails from Email Marketing?

    Emily asks, “I have a list of emails that haven’t opened a single email in 2 years. I want to ask said subscribers if they want to stay before deleting them. How do I go about that?” There’s a four step process here to improve your email marketing. First, scrub with software. Second, check your…

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  • You Ask, I Answer: Removing Dead Emails from Email Marketing?

    Summary In today's episode, I walk through a four-step process for cleaning dormant subscribers from your email marketing list and re-engaging the ones worth saving. Here's what this means for you. You'll boost deliverability, lower your email service costs, and reclaim a small slice of disengaged contacts by routing them through validation, diagnostics, and retargeting…

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  • You Ask, I Answer: B2B Marketing Lead Tracking with Google Analytics?

    Anonymous asks, “In B2B marketing, how do I track a lead from a paid ad to a conversion?” The process requires great Google Analytics setup and tagging, nothing more, at least to the point of conversion. To the point of sale, that requires a good CRM and potentially a marketing automation system. Can’t see anything?…

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