When Your Customers Buy Wine: Identifying Patterns in The Timing of Their Purchases
Let me begin this final Enolytics 101 of 2020 with a note of gratitude for your ongoing engagement and curiosity about this work of wine + data. Enolytics continues to evolve and reflect the needs and interests of the industry. We look to you for input on that, and appreciate very much the role that you play in our development. Thank you.
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Earlier this week I was a guest speaker on data and tourism for a conference in Spain called Wine Land. A major theme of my talk was the COVID-motivated migration of people out of the US’ major cities, and the impact that migration will have on the demographic profile of wine consumers as a result.
Some less-trafficked wine tourism destinations are poised to benefit from this migratory shift of “newly ex” urbanites in the New Year and beyond, particularly with their dollars (that will go farther outside of major cities like New York and San Francisco) and affinity for experiencing wineries and vineyards in a local environment.
That brings me to the topic of WHEN consumers purchase wine, which is data we can analyze under the umbrella of ecommerce transactions since that data includes tasting room purchases, wine club subscriptions and online. (WHEN is our final installment of our “ecommerce storytelling” series, which also explored WHO consumers are, WHAT they purchase, HOW MUCH they spend, and WHERE they purchase.)
If one word can capture 2020’s wine consumer behavior, “shift” is a pretty good candidate. We’ve seen shifts in consumer preferences, shifts in demographics (see above), shifts in the availability of wines, and shifts in priorities. We’re also seeing shifts in how, where and when people buy wine.
This week we’re considering the shifts in WHEN consumers buy wine within the ecommerce ecosystem. Here are a few examples from a sample winery client. You can find each of these images linked below and in the WHEN lookbook on our website.
· Year in Review: Heatmap of the entire year’s activity, day by day, in terms of the number of orders per day
· Web Purchases: Days of the Week and Times of the Day when activity is highest
· Tasting Room Purchases: Days of the Week and Times of the Day when activity is highest
· Performance Indicators (such as Net Sales, Margin, AOV), tracked by day of the week
· Net Sales by Channel, shown month by month
The idea with these WHEN examples is to visualize patterns – day by day, month by month, year by year, and any segment of time you choose in between. You can see the value and relevance of this I’m sure, from staffing decisions to the timing of email campaigns, especially as we’re turning the corner on a new year and you’re trying to anticipate what’s coming next.
Does that make sense? Naturally, I hope you’ll let me know if you have questions or ideas.
Thank you again for reading, today and every Friday of 2020. I look forward to seeing you again in the New Year.
Warm regards,
Cathy