Transforming your syndicated data into business insight
Let’s start with stating the obvious: Shoppers cannot buy your products if they are not available where they shop. Even though your brand may have 12 different items in its product line, not every retailer carries every item. You can identify which retailers sell which items using a relatively straightforward data pull from IRI or […]
We analysts love nothing better than digging through piles of data. But, when it comes to communicating our insights, less is more. Note: In this article, I focus on charts in the form of slides but many of my design recommendations would also apply to dashboards or more complex visualizations. To increase the odds of […]
It’s a pleasure to feature this guest post from our colleague and fellow consultant Dan Wasser. Dan’s data expertise and savvy insights derive from long experience with syndicated data and category management in a variety of roles. You can learn more about Dan (and how to contact him) at the end of this article. Robin […]
This is the second in a series of posts on how to quantify the impact of improving the various elements of consumers’ purchase behavior. These purchase behavior analyses are based on household panel/shopper data (not POS/store data). Take a look at these posts if you need a refresher on this type of data: Overview of […]
This is the first in a series of posts on how to quantify the impact of improving the various elements of purchase behavior among consumers. Some posts will focus on increasing sales for a manufacturer (probably more useful if you are in Marketing) and others will focus on increasing sales for a retailer (more useful […]
In my previous blog post, I described two ways to customize your Nielsen/IRI product data by renaming and grouping product values. In a continuation of that post, I’ll now describe a third way of customizing your data—by creating new attributes. 3. Create New Attributes We’re all accustomed to creating new measures, like dividing dollars by units […]
