Modeling Viral Growth and Marketing in PowerPivot

A Tale of Two Charts

Let’s say you operate a business that relies heavily on “word of mouth” – customers recommending your product/service to their friends and colleagues. Or at least, you THINK it relies heavily on that sort of thing.

You need to decide how much to spend on traditional advertising – to supplement the social/viral marketing that your customers do on your behalf.  Take a look at each of these two charts – the captions for each attempt to capture the knee-jerk conclusions you might draw:

Modeling Viral Growth versus Traditional Direct Advertising in PowerPivot

“Advertising?  We Don’t Need No Stinking Advertising!
That is SO Yesterday!  We’re Viral Baby!”

Modeling Viral Growth versus Traditional Direct Advertising in PowerPivot

“All These Youngsters and Their ‘Viral This’ and ‘Social Media That’ – That’s All Just Fancy Excuses to Be Lazy – You Clearly Need to BRING Your Message to the Customer”

If chart 1 reflected reality, you may opt to spend very little on traditional advertising.  But in a chart 2 world, you’d be silly to rely on viral growth.  But which one (if either of them) describes your situation?

Back in October, Rahul Vohra (CEO of Rapportive) wrote a two-part blog series on this topic, posted here on LinkedIn.  I took a note, at the time, to revisit his work and “convert” it to PowerPivot.

It’s a very different kind of problem from what I normally do in PowerPivot – this isn’t about analyzing data I already have, but about calculating future outcomes based on a handful of parameters.  And that leads to some different kinds of thinking, as you will see.


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Conditional Formatting with Different Thresholds per Test, per Product, per Store, per Division, etc.

After a long hiatus, David Hager has returned with a new guest post.  He has a clever Excel trick/formula for applying different conditional formatting “acceptable ranges” depending on the context of the current row.  In his work, different Tests have different acceptable ranges of values that qualify as Pass/Fail/Warning.


Each Test Has a Different “Pass Range” and “Safe Range” –
David Hager’s Technique Translates This Table Quickly into CF Rules

I think this technique can be extended to basically anything:  an acceptable sales growth figure for Store A may be different than that for Store B (or Product A vs. Product B, etc.)

His post also got me thinking about the new “KPI” feature in PowerPivot V2, so I will return later today with a brief follow-on post.

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