Marketing Analytics Live Online Library

This is the MALO archive. You can participate by asking your own questions in our upcoming live shows, and you can post questions on any of our previous shows. Note: All questions are moderated.

On this episode of Marketing Analytics Live Online, Jim Sterne is joined by Brett Hurt, who founded Coremetrics, co-founded Bazaarvoice, and is co-founder and CEO at data.world. Brett brings a wealth of knowledge about entrepreneurship, analytics, and the future of data. We discuss his insatiable desire to change the world for the better, and the amazing tech platform he’s created at data.world, that just happens to be in just the right place at just the right time for the Generative AI revolution.
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Valerie Kroll is the Optimization Director at Search Discovery, having started her journey in experimentation by moving merchandise around on the retail shop floor at the mall. She then worked as a qualitative a research analyst, stood up a digital analytics practice at the American Medical Association, and was Director of Digital Analytics and Optimization at UBS. Val also served on the Digital Analytics Association Board of Directors for six years, finishing as Board Chair.



Val and Jim talked about her career growth path, the way quantitative and qualitative analytics naturally blend and bend toward strategy, and the presentation she had prepared for the Marketing Analytics Summit, The Case for Learning Agendas which came out of her interest in Hypothesis Libraries.



Val is high-energy, quick witted, and very engaging.


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Christopher Penn is a Board Member of Social Media Pulse, Co-Founder and Chief Data Scientist at Trust Insights, and cohost with John Wall on Marketing Over Coffee - one of the most popular marketing podcasts - and - he built the marketing for a series of startups with a 100% successful exit rate.



Jim and Chris take a very current look at the impact Generative AI is having on the role of the digital analyst.




  • Building your own Large Language Model

  • Buying vs. building your own Large Language Model

  • Feeding data from Google Analytics into an LLM with JSON L

  • Prompt Engineering as valuable, source code, intellectual property

  • Getting GPT-4 to interpret your Tableau dashboard

  • The never-ending need for R and Python scripts

  • The never-ending need for really good data

  • The never-ending need for domain expertise

  • The never-ending need for Random Forests and Monte Carlo simulations

  • Baby AGI, AutoGPT, Agent GPT

  • Gluing hotel furniture to the ceiling

  • Where to begin in your journey to practical Generative AI wisdom

  • And so much more...


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Dean Abbott, data science and machine learning consultant, a keynote speaker, and author of the book Applied Predictive Analytics talks about the early days of machine learning, what he learned from a dozen years of being Chief Data Scientist at a marketing analytics and automation company, and shares some very astute insights about data in general.




  • Demographics, and psychographics can't hold a candle to behavioral data

  • The diminishing value of time series data

  • Prioritizing data projects

  • Ensemble models explained like I'm five

  • How many trees you need for a decent random forest

  • Periodicity, stationarity, and the naiveté of algorithms

  • The value of spending 80% of your time mucking about in the data

  • And the two things he'd really like to accomplish in the next 10 years in the industry



Dean is an energetic, engaging, enlightening guest!

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Madonna - Bono - Oprah - Lizzo. You know who I mean.



In the world of digital analytics, the same goes for Avinash.



Avinash expounds on his career, his philosophy, his impact on the analytics industry - and just what the heck he's doing now that he's left Google:




  • Where did Avinash Kaushik get his lifelong obsession about customer centricity?


  • How much money has he raised for charity through the sale of his books and newsletter?


  • Where did he develop his data chops?


  • How did he get hired at Google?


  • How did he end up using data to explain the value of marketing to the CFO of Google?


  • How does he manage to crank out such great content for his blog and now his newsletter?


  • And - just what the heck is he working on now?




Lots to learn here, including



Advice from Avinash Kaushik: Never make yourself indispensable



"If you make yourself indispensable, you never get promoted. That was my problem at DHL. I was so good at my job that I was the only person who could do that particular job at DHL. And after a while I could never get promoted, because they were like, 'Oh, if you promote him who's gonna do the job?' And so since then, within the first like, two years, I put in succession planning; invested in growing people, their skill sets, hiring people smarter than me, who can replace me on any day. Because if they can - if there's a replacement for me - that means I can go do other things.



Avinash Kaushik's view forward is Algorithmic Intelligence and Intelligent Automation.



"We go into a tool and write reports and the KPIs and segment and find assisted conversions and go down user journeys. All that is such a waste of time, because for the most time we're playing in the known known space. We're not so good at the known unknowns, and definitely, completely not good at the unknown unknowns. (Using AI), I can find the unknown unknowns a lot better... Let these algorithms go in and parse data, find patterns, and discover patterns that a human doesn't even know to ask for, right? 



But then you run into this problem... you still rely on humans and fragmented platforms to activate the insight and find value... so, the second part is Intelligent Automation. Spend a lot of time figuring out how to build connectors and pipes and take advantage of API's... so the decision can skip the human. Humans are the problem.

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Wizard of Moz, cofounder of Inbound, star of Whiteboard Fridays, author of Lost and Founder, and CEO of Spark Toro, Rand Fishkin joins Jim to talk about his latest ventures, entrepreneurial finances, and the bone he has to pick with the incentives that drive analytics work and internal politics. They also cover where ChatGPT is useful (and where not), the new video game Rand is working on, and how to not worry so much about the latest, massive number of layoffs in tech.
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Jennifer Kunz is Principal Architect at 33 Sticks and a 20 digital analytics veteran. In this episode of Marketing Analytics Live Online, she describes her love of detailed problem solving, her focus on Twitter and MeasureSlack, and her three best pieces of advice for anybody struggling with an Adobe Analytics implementation. We discuss data democratization, the struggle with data infrastructure, and the beacon parser she's updating (digitaldatatactics.com). Jenn also offers some details about the presentation she's planning for the Marketing Analytics Summit in June on how to stop investing in the wrong analytics tools.
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Lee Feinberg is Chief Data Officer at Decision Viz, a Tableau authority, and a management consultant specializing in visualization. We talk about charts, graphs, the tyranny of visualization software, and why people need to stop caring so much about the data. Lee thinks of visualization as another language that requires one to understand how people perceive information, what patterns the brain expects to see, and how to bend size, shape, hue, and intensity to your will. At heart, Lee is a business management consultant and visualization is the vehicle he uses to get the job done; improve the business. On, and if you think Tim Wilson hates pie charts. wait until you hear Lee Feinberg go after stacked bar charts! Then, stick around for a bird's eye view of his Design To Act framework that changes the creation of dashboard and such from a project to a product.

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Wil Reynolds is VP of Innovation (ok - founder and CEO as well) at SEER Interactive - and yes, we talk about his title. We also cover how he cut his teeth as a portal strategist back in 1999, his stint at an insurance company, and his corporate culture philosophy. He also shared his dedication to giving back to the community. Then, we dove into the trials and tribulations of selling services beyond just SEO and the complexity of working across multiple business functions for large clients. More topics include data literacy, getting dirt under the fingernails, analytics audits, and, of course, ChatGPT.



Wil is quick to reveal his frustrations, loves, and superpowers in this fast-paced conversation. It was by far the most difficult to edit because of how passionate he is about - well - everything.

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Sharon Flynn on CDP's and so much more



Sharon Flynn, Associate Director of Data Strategy at Publicis Sapient has been a hands-on analyst for twenty-five years. In this conversation, we cover what life is like on the consultancy side of the table, being an un-biased force for business improvement, a bit about data governance and change management strategy, and the fact that she keeps the dev tab open when shopping online. I also got to ask her to compare and contrast Adobe with Google Analytics. Her favorite topic? The value of implementing a CDP as an excuse for a strategy overhaul. Best quote, "Everyone who joins my teams, I always tell them, and we will post a note over their computer, which says You're Not Stupid, It's Hard."

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