I agree you are doing great work in a tough environment! I’ve sent you a message on linkedin.
Where I might have ideas is in how to make the communication strategy more data-based. I cannot judge where you are now. But let me give an example of what I mean:
Let’s say you market Beer Z, a typical lager. You know that your beer looks and tastes much the same as 50 other beers to most beer-drinkers. But somehow many of them consider Beer Z to be, say, weak. What do you do?
Multinationals have developed whole ecosystems to work on trivial problems like this, including omline surveys, focus groups, etc.
You have some ideas: you could talk about your alcohol content, you could get an NFL lineman or rugby player spokesman, you could run promotions among groups who might think weak is good, etc.
Basically, they would test these ideas, optimise down to the level of the exact words to use (“tough” or “strong” or “not like the others” …), generate new ideas, test those, and finally design an intervention based on what would sell the most beer, based on statistically significant data.
The challenges you describe may be amenable to some of this. Who might be a great advocate foe EA? How to create a story line that has potential to go viral but focused on care? Etc.
Hi Tess,
I agree you are doing great work in a tough environment! I’ve sent you a message on linkedin.
Where I might have ideas is in how to make the communication strategy more data-based. I cannot judge where you are now. But let me give an example of what I mean:
Let’s say you market Beer Z, a typical lager. You know that your beer looks and tastes much the same as 50 other beers to most beer-drinkers. But somehow many of them consider Beer Z to be, say, weak. What do you do?
Multinationals have developed whole ecosystems to work on trivial problems like this, including omline surveys, focus groups, etc.
You have some ideas: you could talk about your alcohol content, you could get an NFL lineman or rugby player spokesman, you could run promotions among groups who might think weak is good, etc.
Basically, they would test these ideas, optimise down to the level of the exact words to use (“tough” or “strong” or “not like the others” …), generate new ideas, test those, and finally design an intervention based on what would sell the most beer, based on statistically significant data.
The challenges you describe may be amenable to some of this. Who might be a great advocate foe EA? How to create a story line that has potential to go viral but focused on care? Etc.