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The Merchant23 Blog

The People Bringing Big Data to Wine

Nov 17, 2017 10:56:21 AM / by Jacob Moynihan

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The wine industry has an annual $220 billion economic impact in the United States. The Big Data Analytics Market is worth $203 billion. Yet the terms "big data" and "wine industry" are rarely used in the same paragraphs, let alone the same sentences. Why is that? This is the question that Don White and John Lawlor set out to answer when they founded Label Analytics. In just three short years they've done something seemingly impossible; brought big data to wine.


Wine is different

Here's a statistic from Nielsen's Consumer Packaging ReportsIn the grocery category, improved consumer packaging translates to an average of 5% increase in grocery sales. However, in the wine category, being in the top quintile of labels translates to a 500% increase in shelf attention over bottom quintile labels.  Grabbing shopper attention is the first and most crucial step in the wine purchase process.  

Why is wine so reliant on packaging? Blame diversity. In any store there are approximately four to five different types of products (5 types of eggs, 5 types of paper towels). In the wine section there are approximately 900 different types of products. Suddenly the packaging is the only way (aside from price and varietal) that a consumer can make a purchasing decision. According to CF Napa, 80% of the consumer purchase decision is made off of the label. So, how do you create a good label? You gather data.

Label Analytics is a data company that uses patented methodologies and algorithms to test wine labels. Their tests not only decipher which wines are going to sell, but at what price point, to which gender, and to what age demographic. Using hyper-specific buyer testing, Label Analytics gives wineries something they haven't previously had access to; raw data. Here's an example of a Label Analytics report:

  

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The hypothesis of the test was; will adding the 'Dot' (Awards sticker) increase shelf attention, elevate the price impression, make the product more memorable, and generate higher purchase interest? The data, however, find the opposite to be true in every category. Are you warming up to data yet?

Price is equally as important

It's not just design of the label that Label Analytics tests are interested in. Go ahead and ask yourself, are you selling your wine at the right price point? How do you know? As a winery, is your SRP representative of what your target market would pay for it? As a retailer, are you offering your wines at the best retail price point? Do you have data to support your answer, or do you just 'think' so? 

Check out the graph below that measured price effects on a brand's sparkling rosé;

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The producer wanted to retail the sparkling rosé at $17.99 a bottle. They felt that this was a great deal for consumers. However, the data (Top Picks by Price Point) showed that more customers would buy it for $19.99 a bottle, and the same number of customers would buy it for $21.99 a bottle - a whole $4.00 more than the current retail price!

The winery has two choices when a test rates the bottle higher than the current retail price (especially when the retailer or the existing competition doesn’t offer the opportunity of selling at the higher price point). They can raise the SRP, or they can use the higher price from the test results as a marketing tool for retailers. Wineries can show that a benefit to selling their brand is that it's “perceived value” is higher than it's retail price. It's this kind of information - the big data- that has huge implication for the industry at large. 

Retailers are getting on board too

Surprisingly, it's not just producers taking advantage of Label Analytics services. Many of Label Analytics largest clients are retailers looking to create their private label or brand exclusive products. Retailers are much more receptive to big data and research, and have found Label Analytics' comprehensive testing to be the answer for their needs.

To appeal to all clients, Label Anayltics offers different levels of testing and pricing. Tests can be segmented to all consumers*, or broken down by gender and generation to more accurately identify a target market. *Label Analytics tests a minimum of 500 people per price point, per label. They test with people who are interested in wine, over 21 years of age, and do not participate in surveys often. For more information about Label Analytics Price Sensivity Testing, click here

Label Analytics Test Levels

In the age of technology, the divide between what we think and what we know can be the difference between a good business and a great one. The great businesses understand that the customer is always right, and those businesses work to understand their needs through data and testing. Thanks to Label Analytics, the wine industry can now do the same!

Download Free Guide to Label Analytics

Topics: Wine Data Industry

Written by Jacob Moynihan