Wine

Happy Holidays from Enolytics! Here's Why We're Grateful.

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It has been an amazing year to be in the wine + data space.

Every week, with these Enolytics 101 posts, we've been describing that amazing journey. Hopefully they've been useful to you, as they have been to us, as we continue to learn what's possible when it comes to wine companies engaging better with consumers.

Thank you for your emails in response.

Thank you for your interest and questions.

Thank you for your support and encouragement.

Thank you for challenging us to do better.

Thank you for your business.

Thank you, as always, for reading.

See you in the New Year. We've got lots to do together.

Cathy Huyghe, Co-Founder, Enolytics

Direct To Consumer Dashboard Drivethrough, Part Two: SKUs

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Last week we took a first look at an interactive dashboard for the big data that a wine business already has, specifically from its Direct To Consumer (DTC) program.

The DTC program is top-of-mind for just about every winery I know. We wanted to demonstrate how interactive dashboards can help to identify problem areas and work toward optimizing DTC's profitability.

We looked at the value that is released when data is visualized, accessed, and "sliced and diced" in real time. We started with KPIs -- things like cases sold and month-to-date and year-to-date comparisons -- and how clicking on any one of the KPIs presents a fresh, detailed visualization of variables that matter most to the winery.

This week we're turning to a different set of visualizations, namely underperforming SKUs based on low margins and/or low sales. When you have hundreds of SKUs, how do you compare their performance relative to each other and in an absolute way, while also still allowing to slice and dice by channel, wine type, etc.?

One visualization option is to use a scatter plot (above). It displays all the SKUs, using your selected filters, on a chart by margin and by revenue. This makes it easy to identify your top performers -- those with high margins and high revenue -- and the bottom performers, with low margins and low revenue. Those are the SKUs that need attention and, possibly, a plan of action. With Enolytics' interactive dashboard, it is simple to filter out the bottom performers that are not meeting your revenue and/or margin targets by using a simple lasso tool.

The lasso zooms in on a target area, which results in a focused data set that is useful to further analyze. The list of bottom performers is also displayed in table form for easy understanding and selection.

Enolytics' dashboard enables you to immediately investigate, based on objective insights, in order to facilitate business decisions to correct performance.

Bottom line: improving your understanding multi-fold, particularly of your biggest challenges, weaknesses, and opportunities. 

Can we help you with this? I'd be very glad to talk it through. Give me a call (+1.702.528.3717) or send me an email (cathy@enolytics.com) anytime.

Thank you as always for reading --

What Does Data Mean to ME?

When we launched Enolytics a few weeks ago, we asked prospective partners and clients what interests them most when it comes to big data and wine.

Here was the most common answer (by far): the interactive dashboards.

Which we totally get. The data that’s already loaded into the dashboards makes them dynamic and engaging, and you can derive answers “live” to questions that concern your business now.

As we’ve demonstrated the dashboards to more and more wine businesses who see the powerful potential of the model, one question has surfaced again and again:

"How does MY data relate?" 

And, “What happens if we integrate my own company’s data into this model?”

And, “What can I learn from seeing my data overlaid with third party data sources, especially when those sources are relevant to the goals that I’m trying to accomplish?”

And, “Is it even possible to overlay my data, even though it only exists right now as spreadsheets?”

The answer is Yes. It’s possible. In fact, it’s a fantastic idea and it’s an even better USE of the model and its capabilities.

So here’s the plan.

We’ll continue to add third party data sources. We’ll continue to listen to how we can best service your needs, and identify data sources accordingly. Now, we also invite you to consider your own data — in whatever format it currently exists — as a source to be visualized, packaged, and MINED, particularly within the context of other sources that are directly relevant to your goals.

Not everyone geeks out about data overall. But everyone does geek out about getting their own job done better, faster, and more effectively.

That’s the lesson for this week’s Enolytics 101: what data means for YOU.

Thank you for being interested and please, reach out with any questions or suggestions or to set up a live demo (cathy@enolytics.com). I’d love to hear what you have to say.

Micro-Moments, and What I Learned from Google

This week it's all about the moment.

It's about the moments -- what marketers call the "decision tree" -- when consumers choose their wines. Our sense at Enolytics is that it's less about which wine we choose, and more about why we're drinking it.

Why we drink wine is about the moment, and that's where we're diving deep.

Here's what I learned this week from Google's Seema Vashi (Brand Activation specialist) and Justin Mann (Brand Team member) on why the moments matter:

  • Browsers have sessions. People have moments.
  • "Micro-moments" are intent-rich, when decisions are being made and preferences are being shaped. A moment is, "We're having dinner at 6 pm." An intent-rich micro-moment is, "We're having dinner at 6 pm and I need to find take-out menus of restaurants nearby."
  • Micro-moments are at the sweet spot where intent, context, and immediacy intersect.
  • Customers today are, for the most part, not brand loyal. Unscripted decisions happen in the micro-moments.

Those micro-moments are what's recorded in the data, and that's our focus at Enolytics.

(This week was also about lightbulb moments -- and there were many -- that went off during the MobileX Festival in Atlanta, where I listened and learned from Vashi, Mann and a stellar lineup of other speakers. I was lucky to go. Even though it wasn't about wine and it wasn't about data per se, the content helped me to see both of those things with fresh eyes. Please read more about the MobileX Festival here.)

What Is De-Identification?

Here's the one topic that comes up most often during conversations we've had with potential data partners so far: PRIVACY.

It's a very big deal these days, to our data partners and to us. Companies who have data about their customers — whether they’re wineries or internet-driven businesses or app developers — worked very hard to get it, and they're extraordinarily protective about it.

As they should be.

So why would they share it with us?

Because they aren't giving us things like names, email addresses, or any other personal information that can identify specific consumers. They aren't giving it to us, nor do we want it.

Yes, we do group "cohorts" (or clusters of consumers) based on unique internal device IDs. But we do not know that "This device belongs to Jane Smith or John Doe."

That process is called de-identification. That means we know the ID, but we do not know the individual person behind the ID.

It keeps the data objective, anonymous, and empirical. Which is our goal.