Interested in Becoming a Brand Manager? Know Your Nielsen Data!

If you are interested in becoming a Brand Manager and want to learn more about the kind of datasets Brand Managers deal with on a daily basis, you have landed at the right place. We also plan to introduce you to a tool that is currently making the life of Brand Managers so much easier than before. How? Well, keep reading!

We have written similar blogs for Kantar and IQVIA datasets as well, so open both in new tabs and explore them once you’re through this one.

Brand Managers are champions. They are multi-taskers, owning multiple responsibilities
like using market research data to formulate brand strategies, managing various stages of the brand life cycle, and performing other tasks such as juggling budgets and building a strong rapport with multiple stakeholders.

As someone interested in becoming a Brand Manager, you should first of all warm yourself up to the fact that strong data handling skills will be the backbone of your career and the key to success. Branding, marketing, sales, SCM – everything is data-based. It’s a highly valued, challenging, and rewarding career path to go down – and we wish you all the luck for it.

DATASETS THAT BRAND MANAGERS DEAL WITH – NIELSEN DATA

Nielsen is one of the most prominent names in data and market measurement. It measures media audiences such as TV, newspapers, radio, etc. Nielsen provides Data as a Service (DaaS) which includes access to 60,000 consumer segments, globally, and 300 media & marketing platforms.

Here are some of the common columns present in Nielsen data:

Market
This Column comprises all the individual and combined market i.e. States, Zones, All India, etc.

Geo Classification
This column contains classifications such as Metro, Zones, States, and All India

Brand
Brand includes one’s own brands as well as competitor brand names. Total rows include the Brand, the Category in which the brand operates, and the company to which the brand belongs

Sales Value & Sales Volume
Value comprises the Market Sales Value, while Volume means the Market Sales Volume in Kg

PDO Val Rs.
PDO stands for Per Dealer Offtake. It is the ratio of sales per outlet/store, or volume, to the total number of dealers handling the product

PDO in Units
This is the same as Per Dealer Offtake with number of units replacing total value

No. of Dealers
This is another metric provided by Nielsen, letting you know the total number of dealers in the market, brand-wise

NumD & WtdD
Numeric Distribution is the percentage of stores where a brand is placed out of ‘n’ total stores. Weighted Distribution is the percentage of stores with a good potential for sales of a brand, out of ‘n’ total stores

SAH Val
Suppose you are present in an outlet. Now, what is your brand’s share within the sales of a particular category in a particular outlet? That share would be called Share Among Handlers. For example, the share of Cadbury within the total sales of chocolates that takes place in an outlet.

STR
Sell-Through Rate is the product inventory sold within a period. It is used to predict the demand for a particular product. One method can be studying the STR of similar products by other sellers. Avoiding spending on unnecessary product listings is another reason to study STR and improve cost efficiency

Stock Volume & Stock Units
These are the available Stock Volume at stores and the available Stock Units at stores

SEPARATE FILE FOR EACH, OR JUST 1 INTEGRATED DATASET?

We’re proposing the second!

Explorazor combines not just Nielsen, but also Kantar (if FMCG industry), IQVIA (Pharma), and your primary sales, secondary sales, and more, into 1 integrated dataset available to you on the Explorazor screen. From there,

  • Ask queries via simple search interface
  • Obtain data pivots as tables, in seconds
  • Choose to customize tables into charts, trend graphs, etc.
  • Choose to download as CSV and transfer to Excel
  • The option to pin a query result to the dashboard is also present

Not only this, Explorazor also directly recognizes time-based filters, has an intuitive search query mechanism, supports time-period comparison (such as Sept 2022 vs Sept 2021, or Nov vs April 2021), and allows drill-down and drill-across to facilitate root-cause analysis, through simple clicks.

Features so good, we had to embolden the entire paragraph.

Related: If you’ve reached here, we’re sure you’re very interested in becoming a Brand Manager. Why not get a glimpse of how Brand Managers work on Excel? Head over to Modeling Basic FMCG KPIs in Excel.

Continuing, we believe that the value of Explorazor is clear for all to see. Instead of working slowly on slow laptops (large files; slow processing), there’s the option to work fast on fast laptops. Users also avoid repetition; the integrated dataset produces the required data pivot in one go. With a cleaner laptop and fresher mental space, Brand Managers test out hypotheses at accelerated speeds, improving the quality of their decision-making.

Which is really the end goal of all this incessant data crunching, wouldn’t you agree?

Explorazor is a product of vPhrase Analytics.

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