Tag Archives: Pineapple Consulting

4 Ways Analytics Will Improve Your Brewery or Winery Sales

4 Ways Analytics Will Improve Your Brewery or Winery Sales

By Jack Tompkins

Avoid poor performance with some pour analytics!

In the brewery/cidery/wine world, analytics can increase sales, improve customer insights, and most importantly, support and refine your gut instincts!

Whether you sell through a taproom or you have the full restaurant feel with the best beverages in town, analytics can help improve your day to day and leave you time to enjoy some of your very own hard work.

For brewers, if you get creative and dedicated enough (plus some extra equipment), analytics can even have a meaningful impact on the brewing process (shortening the time by a few hours).

For now, though, we’ll focus on making your top sellers even better, building loyalty with customers, and selling the amazing product you’ve already perfected.

#1 Further Identifying Top Performers… and What To Do With Them

You most likely have a pretty good sense of what your top performing drink is, regardless of the analytical power you have available. There’s a good chance that some further analytics could help enhance your top performer’s sales though.

Are those high sellers typically sold at a certain time of day or day of the week? Are they the highlight of the tour? What is typically ordered with them? How do they perform when on sale? Is the top seller also the most profitable?

Getting data supported answers to those kinds of questions can really help you lean into your top sellers and make it the top seller in the state, not just your taproom.

Running promos for your top performer

Using analytics, you can determine how top performers sell on certain nights, days, or times of day. Using this data, you can create promos that target times when the drink sells well and see if it sells phenomenally during the promo (more of a good thing is great, right?). On the flip side, you could try offering the promo when sales are typically a bit down, thus evening out the sales and using your top performers to bolster weaker sales periods.

If either promo works particularly well, you could then try it on some second-tier drinks and see if it helps their sales as well!

Selling your most profitable drink

You and your accountant potentially boil things down to financial metrics on a “per barrel” basis, but what about expanding that thinking to the pint and individual sale level? Is the breakdown of wholesale to taproom sales optimized for profitability? What is your most profitable drink sold in combination with?

You could always include your most profitable drink in an upsell opportunity, use it in promos since it has a higher margin, and pair it with food options that make sense for the customer’s palate and your business’ bank account.

You could also expand this to general menu profitability, but that’s a piece for another article (still heavily relating to analytics though).

What pairs well with that?

Do your bartenders and waitresses get this question a lot? Of course, the safe answer is for them to disregard their own taste buds and go with the popular answer, but it’s sometimes difficult to know that, let alone upsell another item in that context.

With analytics, you can have the two most frequently ordered food items with that drink at the tip of your fingers for a quick and data supported answer that your customers will likely enjoy the most!

Don’t sell food? Everyone sells flights of beers/ciders/wines, and sometimes a combination of all three! The same math applies here – you can quickly say what typical flight combos are or upsell to suggest the most profitable tastings that go with the rest of the flight.

What sells best after a tour?

Maybe it isn’t your top performer. Maybe something in the sales pitch/historical fun fact/story about the creation made it a top tour seller. Analyzing the data can tell you what the financial results of the tour are and help you leverage that experience in other sales points.

The shortened version of that same story could be put to good use at the bar and increase sales there as well!

 

#2 Put Your Marketing Data to Use

There is a lot of power that can come from your audience. Marketing data can give you insights into not just top sellers, but most popular options (not always the same), most talked about drinks and events, highest return on drink-related campaigns, and many other pieces of analytical gold. Just refer to the folks at WIMS for the power of your marketing data.

Pay attention to your marketing avenue’s data and you can develop strong, loyal connections with local residents. If you’re able to identify people who engage with your material most often, wouldn’t you want to encourage that behavior? Throw them a free sample of a new beer or get their opinion on a recent event. Whatever it is, people love to feel appreciated and will maintain loyalty because of it.

Analyzing your marketing data can help find these individuals who love your brand and you can develop a mutually beneficial relationship with them. They also probably represent your target market so that makes them the perfect test subject for new ideas, and you can extrapolate from their comments/reviews and apply it to the larger population of your target market with some simple statistics.

 

#3 Analyze and Cater To Repeat Business

Similar to your loyal social media followers, it’s important to take note of your repeat customers. You should be able to track this through your POS data. Of course, folks who saddle up to the bar several times a week are going to be easy to identify, but people that come by once a month might be harder to remember, let alone remember their preferences.

Acknowledging these repeat customers goes a long way. Using your data, you can learn their preferences, food they order, favorite style, other options they would enjoy based on their tastes, etc. and it can help give you an additional level of insight that make you and your waitstaff look great.

Repeat business is the key to success. Spending 10 minutes analyzing their data can result in a loyal customer for life.

#4 Put it All Together

Now, let’s combine all of this into a logical, and very effective cycle that can result in significant long term benefits for your business.

  1. Start with identifying your top sellers and most profitable drinks – these will always come into play

  2. Engage with folks through social media, blog posts, and email marketing to further promote those top selling/most profitable options and generate some buzz for them

  3. Take that marketing data that you gather from the campaigns and identify what is most popular, who shares it, who actually comes in to purchase it, etc.

  4. Study the “what pairs best” combinations of food/flight options to satisfy customers when they come in

  5. Pay attention to, acknowledge, and examine the data for your repeat customers to build strong loyalty

  6. Continue nurturing this end to end cycle of satisfied, loyal, and maybe slightly intoxicated customers that you now have supporting you week in and week out

A little bit of analytics goes a long way and can greatly help in every aspect above. You’ll be targeting better customers, be more efficient, save money, and increase revenue all with adding a few key analytical practices to your process that won’t take away from your day to day or your gut instinct.

If you’re interested in seeing how we can help implement these strategies at your brewery/winery please reach out to us here.

Also posted on the Pineapple Consulting blog here.

Data Analytics Dashboard

How Anyone can Build a Custom Data Analytics Dashboard

If you could carve out an hour a month for analysis in order to save a dozen hours of work, the one-hour investment would be worth it, right?

How about if that same hour led to crucial details about your sales trends and customers insights?

On top of all that, what if that same one-hour investment came at no additional cost to you?

Seems like a pretty great deal.

Welcome to the benefits of an Excel-based analytical dashboard.

Benefits of an Analytical Dashboard

You’ve most likely heard of the powers and benefits of data analytics. You’ve probably seen examples from things like POS systems, Tableau, cloud-based software, and many others.

Some of these benefits include the following:

  • Saving you time and money through efficiency and more impactful insights

Spending time looking over your dashboard saves hours of debating anecdotal or piecemeal results and helps guide you towards the best path forward

  • Giving you better insights into your customer to improve marketing campaigns

Campaigns based on hard data are more successful as you can target your intended customer more effectively

  • Taking the guesswork out and make great, data supported, decisions in less time

The high end services all have their merits, but in a small business where you might not have the budget for those services (which are also potentially far beyond the capabilities you actually need), plus a large learning curve, those services don’t always make the most sense.

By learning (on a much faster learning curve) to make a dashboard in Excel, you can get the benefits you want in a completely customized dashboard at no cost (since you already have Excel on your computer).

 

Why use Excel for this

Let’s start with some common business questions.

How did your sales do last month? How does that compare to the same month of the prior year? How about compared to the pace you’ve been running at this year?

Now how about separating those numbers by project, item, or client? How about by distribution channel? Sales rep? What about the specific days you had promotions?

The first set of questions is somewhat easy to have a gut feeling for, if nothing else. You might even have some quick analysis created for you in QuickBooks (or similar software).

However, the second set of questions represents another level deeper. You might feel a bit less confident about your gut feeling. They require you to dive into the data each time you want to look, and maybe even anecdotally piece it together from a few different sources. It’s kind of a hassle, but they’re important insights, so it’s worth the time.

Here’s the good news from Excel – you can answer all of those questions, from top line revenue down to whatever level of detail you need, and have them at your fingertips in one place!

With a simple export of data from whatever source you need, you can populate dozens of custom views that you’ve templated and turn it into your very own analytical dashboard!

The only time intensive piece is building the template and framework for all your custom views.

After you create that, you’re essentially just updating with data each week/month/etc. and looking it over for trends. Making changes to it? Duplicating views with variations? Actually, all pretty easy.

The Excel Dashboard

Here is a very quick sample dashboard that shows that topline sales numbers (black chart) followed by a few, slightly deeper, analytical pieces that help evaluate performance (gray charts).

When I say “very quick” … this dashboard took less than an hour to fully create. Real life dashboards of this level of depth take a similar amount of time. Getting significantly deeper into the data does not necessarily mean significantly more time to create though.

Only a few “next level” type questions are displayed (although these may only be half a level deeper), but they are meant to be representative, and the great feature about the “behind the scenes” of the dashboard is that the building blocks for all levels of analysis can be VERY easily duplicated to get at any question you need.

Take a quick look at the dashboard, follow it along the yellow markers, 1 to 5. Any trends jump out at you?

You can likely see the following in a quick pass:

  • Sales are up in 2019! (Callout #1) – by 22.1% if we want to be specific

  • There seemed to be a change in performance starting in February (Callout #2). Perhaps a new item was released? Or a new marketing campaign?

  • All Sales Reps are selling more this year (Callout #3). Shawn leading the pack with a 28.7% increase over 2018

  • In Store sales have grown by over 60%! (Callout #4). However, Online sales have shrunk a tiny bit.

  • Further diagnosing, it looks like Jennifer and Oliver have really improved their In Store sales, while Shawn has faltered there (Callout #5). Perhaps there was a training that stuck with Jennifer and Oliver? Maybe Shawn has just focused all of his attention on Online sales?

Those types of insights are crucial to running your business and can be seen quickly from the dashboard. On top of that, there are still tons of different ways to cut the data… by product, by product and distribution channel, by sales rep by month, etc. All of these examples are (almost) as easy as copying and pasting.

Creating the Backend of the Dashboard – a General Guide

We start with one of the building blocks of an Excel-based analytical dashboard. Simply, the Pivot Table.

Depending on your level of familiarity with Excel, Pivot Tables might seem like “that complicated next level” or “that tool we use every day”.

The truth is, everyone can easily be at the latter, and if you’re already there, you could probably be using them more even more effectively. Investing just a bit of time can have a very outsized benefit to your business.

Pivot Tables are fantastic, for all levels of users, because of a few main pieces of functionality:

  • Very easy to build, use, and manipulate

Drag and drop methods, no complex formulas, no macros or coding

  • Ability to create charts and dashboards from the Table(s) easily

  • Build automatically updating formulas off the Table to create new data elements

It deserves mentioning that the quality of your data is very important. If the data is wrong to start, then there is no point is doing any analysis.

First… a few tips on how to create a Pivot Table

Feel free to skip this section if you’re already familiar.

For a detailed “how to” build a Pivot Table, I recommend watching from ~2:30 to ~5:30 in this video. The rest of the video has some good explanations as well, but for a quick guide, the 3 minutes is really all you need.

One piece I would highly recommend changing though, is in the data selection piece.

Important – select the entire column in the data, making sure the headers are in row 1. This allows you to add data in the future and have it included in the pivot table without having to change the data range.

The boxed-in range is okay as “ Sample Data!$A$1:$E$13 ”, but would need to be changed if you add more data to the end of it. The better version’s range “ Sample Data!$A:$E” highlights the entire columns.

Onto Creating the Dashboard

Start with creating a Pivot Table, and from there it is really just about dragging and dropping fields, copying and pasting, and picking a layout!

  • Let’s say you begin by creating a simple Pivot Table with sales by month:

  • From there, go up to the ribbon and find the “Pivot Table Analyze” or “Analyze” tab, depending on which version of Excel you’re working with.

  • Select the “Pivot Chart” option, and out pops a variety of options. Select your favorite chart option (bar chart, line graph, multiple types, etc.) and boom! You’ve got a working chart to help you analyze!

  • Any time you change what’s in the Pivot Table that created the Pivot Chart, the Pivot Chart will change accordingly.

Example, if you limited the data to just “Jennifer” (Sales Rep filter), you’ll see only her sales in both the Table and Chart.

Tip for the aesthetics of the Chart

To get rid of the “buttons” or ugly looking gray bubbles polluting your chart, you can right click on any of them and select “Hide All Field Buttons on Chart” and they’ll go away (as shown below).

If you don’t mind their appearance, each button acts as a filter for the Pivot Table. So instead of scrolling over to the Table, you can filter right from the Chart.

  • From there it is just preferences:

You can add a chart title, hide the legend, and a lot of other customization by clicking on the Chart, and then selecting the green “+” button that appears to the right of the Chart (shown below).

Once you’ve got your first chart, you can then start the duplication process!
  • To make another Pivot Table and Chart combo, you can just select the entirety of the Table, then copy and paste it elsewhere on the sheet

Copying the Pivot Table to be replicated
  • Drag and drop the fields (from the Field List on the right) you want to look at in the new Table (ex. Sales Rep in place of Month), and then go through the same quick process to create a Chart

The premise here is that each Table you create is referencing the same data. Each variation is just how you want to cut the data for that particular view.

Note – the formatting you select for one chart will not transfer to a new chart. The easiest method is to pick from Excel’s preset templates, which are normally visually appealing enough – both the black and the gray Charts above are in Excel’s preset templates. You can always customize the look of every chart individually to how you want though.

Best practice is probably to settle on a color scheme and layout after you’ve created all the charts you want, that way you can quickly go through each and select the same layout all at once.

After creating however many variations that get to your necessary level of depth, you’ve now just created yourself a dashboard! Congrats!

Best Way to Create Formulas Based on the Tables to get Additional Metrics in your Dashboard

You may notice that some pieces in the above dashboard (the tables with headers that have blue background and white text) are not Pivot Tables or Pivot Charts. These are created using the same information though.

Enter the GETPIVOTDATA formula. It is one of the most complicated looking formulas, but one of the most effective to use.

Note that it is simply complicated “looking”, but not actually that complicated to use.

Here’s an example. We’re going to walk through the Sales By Month table in the dashboard above (and referenced below).

Let’s say you wanted to get that 41.1% “Growth vs Prior Yr” for Feb from the information in the Pivot Table.

Naturally, you would do the following (referencing picture below) U10 / T10 – 1 = 41.1%

When you go to do that though, this scary looking formula comes out:

Let’s break it down and look at the first piece, before the “/”:

=GETPIVOTDATA(“Sale Amount”,$S$7,”Year”,2019,”Month”,”Feb”)

Translating, it is saying the following:

  • From the Pivot Table

=GETPIVOTDATA(“Sale Amount”,$S$7,”Year”,2019,”Month”,”Feb”)

  • Grab the metric “Sale Amount”

=GETPIVOTDATA(“Sale Amount”,$S$7,”Year”,2019,”Month”,”Feb”)

  • In the Pivot Table located in cell S7

=GETPIVOTDATA(“Sale Amount”,$S$7,”Year”,2019,”Month”,”Feb”)

  • Given the following criteria, Year = 2019

=GETPIVOTDATA(“Sale Amount”,$S$7,“Year”,2019,”Month”,”Feb”)

  • And the second criteria Month = Feb

=GETPIVOTDATA(“Sale Amount”,$S$7,”Year”,2019,“Month”,”Feb”)

You’ll notice the second GETPIVOTDATA (after the “/”) is the same formula, just referencing Year = 2018 instead of 2019.

It is the same formula as the nice and easy U10 / T10 – 1 above, just bringing in the functionality of the Pivot Table.

So why on earth would you actually use the complicated version?

Reason #1: Let’s say you add in another filter and the bulk of the Pivot Table shifts down by one row. The U10 / T10 – 1 will remain but will now be looking at a different month.

Reason #2: What if you changed the Pivot Table to include each Sales Rep’s details in each month (like below)?

Now that “U10 / T10 – 1” formula would be referencing Jennifer’s sales in Jan… not even close to total Feb sales.

If you used the GETPIVOTDATA formula, you would still get the result you want (Total Feb Sales Amount, 2019 over 2018) because you’re telling it what criteria to look at, regardless of what cells the intended data ended up in. It would still do $26,070 / $18,470 – 1, or 41.1%.

Note – in a scenario like the above picture, make sure Subtotals are enabled in the “Design” tab that appears when you click in the Pivot Table

Reason #3: You can completely customize the look of your created table, whereas you have limited aesthetic flexibility in the Pivot Table itself. I choose a blue header with white text.

Reason #4: You retain the copy and paste functionality of the “U10 / T10 – 1” formula but increase the accuracy of the formula.

Notice in our summary chart with each month’s “Growth vs Prior Yr”, we have the month abbreviation in the left column, then the % growth in the right column.

To utilize the copy and paste functionality of formulas in Excel, we just have to reference the month in the formula.

It is the same formula as above in every way except for the P9 in place of “Feb”. This just tells the formula to take the value in cell P9 as the criteria needed to be found in the “Month” section.
You can then copy and paste this formula to each of the months, and the “Growth vs Prior Yr” will fill out for each month, regardless of how many other variables are in the Pivot Table, or where the numbers you want are located (cell-wise).

Summary

So now you’ve learned…

  • The benefits of a dashboard, specifically one in Excel

  • How to make a Pivot Table

  • How to make a Pivot Chart based off it

  • How to duplicate those efforts (for efficiency)

  • How to reference the information in it to get analytical metrics that aren’t directly called out in the Pivot Table

  • (Most importantly) How to build your own fully functional, completely customizable analytical dashboard!

Updating the dashboard is an exercise that takes mere minutes to download the data and add it into your data sheet.

Reasonable time investment to make the dashboard, small time investment to update it, big business benefits.

Pineapple Consulting

WIMS Client Spotlight: Pineapple Consulting

Pineapple Consulting Firm was created with only one goal: to help small businesses succeed. It helps how synergistic that is with WIMS Consulting, as not only is there a client relationship, but it really fits our model of creating partnerships too.

While Pineapple is eager to help however they can, they have a particular specialization centered around analytics and efficiency. Specifically, they are wizards when it comes to Excel, spreadsheets, lead generation, and project management (something we’re really interested in helping businesses with right now at WIMS Consulting too).

Their service offerings include:

  • Data Analytics
    • Inform decisions and strategies for the best results.
    • Data gathering, manipulation, and visualization with expertise in Excel.
  • Financial Analysis
    • Cost benefit analysis, Financial modelling and projections all in customizable Excel tools.
  • Project Management
    • Lead a project from idea development all the way to post-execution monitoring.
  • Lead Generation/Data Scraping
    • Extract leads and data from online and present it in easily manageable files.

They work with a wide variety of industries, but have a niche surrounding professional service firms. Pineapple’s founder has an extensive background in the financial services and wealth management industry. However they also work with startups of all sizes, accounting, banking, insurance, real estate, non-profits, and health care among others.

The company is based in Charlotte, NC but of course is able to work with clients from throughout the country.

Click here to check out their website and let them know that I sent you!