This is a debate we actually have. All the time. 

Is this a product ad OR a brand ad?

Is this rational OR emotional?

Is this about features OR about lifestyle?

Like, how many points of distribution can a brand lose and still recover?

Michael Kruger & IRI crunched 6 years of scanner data to find out. It covered all food, drug & mass outlets (not Walmart) for 298 categories and 10,818 brands. They only looked at brands with >30% distribution in year 1.I mean, we’re all creatures of habit, right? And brand loyalty is what we’re all after, right?

Well, The Hartman Group asked 2,000 Americans where they bought their groceries in the past month. In particular, which channels they shopped. (Grocery, mass, dollar, club, natural, etc.)

I mean, we’re all creatures of habit, right? And brand loyalty is what we’re all after, right?

Well, The Hartman Group asked 2,000 Americans where they bought their groceries in the past month. In particular, which channels they shopped. (Grocery, mass, dollar, club, natural, etc.)

Well, one stat you should absolutely positively track is consecutive repeat purchase rate (CRPR).

It shows how often people pick your brand on back-to-back purchases of the category. E.g., how often you get bought twice in a row.

In 2020, Planters killed off their 104-year-old mascot, Mr. Peanut. 

10 days before the game, Planters dropped an ad online where Mr. Peanut sacrifices himself to save his buddies in a fiery crash.

In marketing, we talk about “brand love” all the time — well, some people do. 

But what’s the State of Brand Love in America?

A couple years ago, Upland Localytics did a simple survey of 1,000 adults to find out. Turns out, there’s no time for love, Dr. Jones.

Nielsen crunched a whole lot of data to see the pattern — at least in terms of distribution — for CPG (consumer packaged goods).

They found that for the first 6 months, all launches grow distribution equally well. (% ACV is a measure of how many stores a product is sold in out of all the possible stores. Roughly-ish.) Good sell-in and retailer excitement helps most brands ramp up quickly.

Analytic Partners has just put a heaping mound of data on this question. They looked at the effectiveness of over 50,000 ads in 2020 to see if their impact was wearing out.

They found that 14 of them — FOURTEEN — showed signs of wearing out.

That’s 1 in 3600. That’s 0.03%. In other words, 99.97% of ads were going strong, doing fine, and didn’t need to be replaced.

Let’s start with the best. Here are the top 3 Most Interesting Posts as voted by you, The Public:

Like, is the Net Promoter Score (NPS) some kinda magic number for predicting sales growth and tracking your brand health and measuring customer loyalty?

Not really, no.

A team led by Sven Baehre at the University of Limerick has been doing lots of work on the NPS.

Like, does it hurt a brand’s likability if the logo is too big?

Turns out no. It doesn’t. 

Clear Channel UK did a nifty study on an outdoor ad for Müller, a €4.6Bn yogurt & dairy maker in Europe.

When does one of the world’s most famous, most iconic, and most successful marketing campaigns “wear out”?

“A Diamond Is Forever” launched in 1948 by De Beers, and it helped the diamond engagement ring become a default part of betrothal. It’s so ubiquitous it feels more like a colloquialism than an ad campaign.

Like, should you work with small, “niche” influencers, or big (and probably expensive) superstars?

Wies, Bleier, & Edeling did a nice analysis of Instagram campaigns to try and figure it out. It was a meaty study.

It's one of those words like “love” or “art” that means lots of things.

Here's a super-simple way to clarify it for those in the trenches.

BIG B BRAND is your reputation.

LITTLE B BRAND is how people know it’s you.

Ok ok ok, first of all: caveats galore. This stuff is complicated. And multifaceted.

But Bruce Clark of Northeastern University did an elegant study recently that gives us some clarity. 

18,000 shoppers. 112 brands, 36 countries, 1 FMCG category. (Pretend it’s snacks. Or soda.) One nice set of year-over-year data.