Wine Intelligence Provides Interesting Case Study During Recession

I was glancing through the headlines of my BI RSS feed when I came to a sudden stop at the headline “Wine Intelligence”. Now anyone who knows me will acknowledge that my passion for BI is only equalled by my passion for fine wines and chocolate. So this headline was brewing up to a perfect storm pour moi.

When I am investing in real estate, one of the demographic markers I use for the area is gained by visiting the local supermarket and checking out what wines they stock, and the balance between different price points. So I was intrigued as to what wine intelligence was all about.

Clicking through to the site I found an array of interesting market data extracted from Vinitrac Global consumer survey, due for launch in March 2009. Insights such as:

“lot of turbulence in the middle of the Wine Wall ($4-$10)”.

“Buyers really are trading down from $7.99 to $5.99”

Following 9/11, it was proposed that wine sales were “recession proof”. The New York Times recently reported that consumers are trading down, but buying more. The argument given was that there was “even more of a reason to drink,” ….I’m with you on that one buddy! Whilst the price dropped 17%, the volume increased 15%. But what about the impact on the producer side. Since the cost of distributing a $5.99 wine is not $2 less than a $7.99 wine, trading down has a big effect on producer and retailer profits… one can expect revenues and profits to take a hammering. In markets such as China, where wine is still considered a luxury item, it is more easily deleted off the shopping list without substitution.

All this data is harvested from grocery store loyalty card programs…there is a reason they are willing to give you all those airpoints and free homewares. The article represents a great example of how important it is to understanding the desires and thought processes behind consumer behaviour. In any market condition!! It also illustrates how modelling a current scenario, aligning to common elements in past scenarios can help companies predict with reasonable certainty how the market will react to certain products and services.

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