Mktg_Podcast-35: Outputs and Outcomes, Self Organizing Units
– Cartoon of the week: double feature
– Are movies getting longer?
– Self Organizing Units, micro metrics for micro management
– Even the best companies face complexity
Marketing Metrics
Mktg_Podcast-33: NPS, IKEA, Complexity
– Is anything wrong with Net Promoter Score (NPS)?
– Surprising customer reaction to IKEA’s store layout
– Complexity, and why Doug is writing a book about it
Mktg_Podcast-25: Product-Market Fit, Data, Store and Media
The inaugural installment of a new section, Cartoon of the Week, takes us to product-market fit vs just raising more funds. Another recurring subject is marketing data, this time covering “good data” and “same data”. Then it’s time to discuss whether the store really is the media?!
Mktg_Podcast-24: Defining Success, Econometrics, Loyalty
What does marketing success mean? The difficulties in digital attribution, interpreting data, and whether econometrics can be a solution? And going deeper into how the concept of “customer satisfaction” actually correlates to product sales.
Mktg_Podcast-18: Musky Texts, Distinctive, Data, Marketing Mix-It-Up
Twitter deal’s backchannel texts. Is “Distinctive” sufficiently “differentiated”?! Complexities of marketing data. Marketing Mix-it-up!
Mktg_Podcast-15: Lead Generation
Every company spends money on Lead Generation. How do you determine your marketing mix and then match it to the sales cycle and buying behavior? Lots of moving parts, and we go over many.
Mktg_Podcast-5: Logos, Verbal Real Estate, Employment Marketing, Cost of Metrics
A lively discussion about 1) the most effective logos, branding and strategy, and the importance of verbal real estate; 2) recruitment marketing and how employee/employer dynamics are shifting; and 3) the high cost of metrics and how projects can turn into products.
Sales Cycle. Marketing Funnel. Customer Journey.
An in-depth discussion with a panel of experts, this time about the sales cycle, marketing funnel, and customer journey.
Untangling Marketing Metrics
Businesses want to be data-driven because data can provide insight. But bad data does not. So how do we make sure the data is useful? Join an all-star cast for this important discussion. Topics include: Why do you need metrics if your instincts are so good? What needs untangling? What does it cost to measure marketing data? What are the pitfalls in interpretation of data? Metrics and complexity