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Blog » Miscellaneous » What article do you wish we would write?

What article do you wish we would write?

October 20, 2014 By Sally Martin 4 Comments

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Dear Blog Readers,

Wow, it’s been almost 2 years since we started CPG Data Tip Sheet! As we think about where to go next with this project, we wanted to get some feedback from you.  We’ll share the results of this mini survey in a future post:

  1. Which article has helped you the most?
  2. What article do you wish we would write?
  3. What are the biggest challenges you face in getting value from the syndicated data you are buying?

If you are getting this survey via email, you can simple “reply” to respond to our questions.   Or leave a comment on the blog.  Or reach out to us through our contact form.

Thanks for your input!

Robin Simon & Sally Martin

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Filed Under: Miscellaneous

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Comments

  1. NESTOR TORO says

    October 24, 2014 at 2:13 pm

    Dear Sally & Robin,

    Your blog has been invaluable to my understanding of syndicated data analysis. I honestly think you two should consider writing a book on the subject (if not already in the works). Thank you for continuing to share knowledge and tips gained from years of experience in the industry.

    As for potential topics for future posts:

    – What about a post on new item / brand tracking? How do you determine if a new item/brand is doing well compared to competitive brands, or even compared to your more established brands? What metrics would you focus on? I have found this type of analysis difficult because you generally don’t have a lot of historical data to work and the data you do have can be misleading.

    – Maybe some more posts on cross-measure analysis. For example, once you’ve identified distributions voids (using some of the techniques you’ve discussed on this site) how do you determine which voids to fill? What other measures could you use to determine which void presents the greatest opportunity? In general, types of analyses you could do using multiple facts/measures. E.g., if measure-X is up and measure-Y is down, that could mean something. You’ve done a little bit of this when comparing SppD vs SpM and I thought that was helpful.

    One suggestion for site enhancement: I’d love to see a high-level overview (table of contents) page which organizes the blog posts not only by category but also in a logical progression. In other words, read post-A, then post-B, then post-C. Now that you’ve reach 50+ articles, I find that the blog roll navigation is a bit cumbersome — especially for new readers. An overview page might be a better for navigation.

    Keep up the great work! And, thanks again for your contributions to the community.

    Sincerely,
    Nestor

    Reply
  2. Nipa Mehta says

    December 16, 2014 at 3:35 am

    Dear Sally & Robin,

    Thanks for writing about all the concepts of Syndicated data. It will be helpful if you can write some articles about other CPG data types like survey data,media data etc.

    Reply
  3. Ellen Idler says

    January 10, 2015 at 11:02 am

    As a Buyer / Category Specialist, I’m interested in the art of forecasting. and understanding the various strategic levers to pull for maximizing sales and GP through promotion, assortment, trade spend buckets, etc.

    Reply
  4. LT says

    March 4, 2015 at 6:37 pm

    Pricing. Pricing. Pricing.

    Not just measuring price gaps, but zeroing in on optimal gaps and target price points.

    Simplified elasticity analysis would be incredibly helpful.

    Reply

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About CPG Data Tip Sheet

We (Sally Martin and Robin Simon) first met in business school and bonded over our interest in geeky marketing stuff. Eventually we both started independent consulting practices. Now we’ve reunited to share with you some of what we’ve learned in our decades of experience working with syndicated CPG data.

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Categories

  • Glossary (79)
  • How To Answer Business Questions (42)
  • How To Communicate Insights (17)
  • How To Get Started with Nielsen/IRI (22)
  • How To Understand Your Database (12)
  • Know Your Measures: Distribution (24)
  • Know Your Measures: Pricing and Promotion (45)
  • Know Your Measures: Sales (21)
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Search CPG Data Tip Sheet

Tags

ACV analysis examples analytic skills attributes average items base base weighted weeks career development category management channels characteristics coronavirus coverage factor covid-19 Database distribution due-to Excel tips Facts incremental markets Measures merchandising new items panel data periods pricing pricing strategy products promoted price quantify opportunity retailer direct data retailer markets shopper data store data Syndicated TDP the basics trade promotion trading areas velocity visualization visualizations volume bridge volume decomposition

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