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Simulated consumer research for beverages and spirits analysts
TL;DR
- Beverage models turn on occasions, brand choice and how much price a brand can take before volume moves to a rival, a store brand or a different drink.
- Neon Blue runs simulated shopper studies on elasticity, brand switching, promotions, occasions and launches across beer, spirits, wine, soft drinks and RTDs.
- Each study returns answers by shopper segment (occasion, frequency, income, channel) as a labeled input to your model, never a stock call.
- Results come as a report. An ongoing data stream and an API are in build. The first study is free.
Neon Blue builds simulated audiences of a beverage brand's drinkers and shoppers, AI models that answer the way a defined group of people would, grounded in Neon Blue's own paid studies and AI-moderated interviews with real people. Beverages and spirits analysts at hedge funds and investment firms use Neon Blue to answer the shopper questions behind a volume and price/mix model while the quarter is still open.
What consumer questions matter most for beverages and spirits stocks?
The same drinker and shopper questions show up on most beverage calls:
- How much volume does the next price increase cost?
- Is share moving between brands, or out of the category?
- Are occasions changing? At-home vs on-premise, weeknight vs weekend.
- What happens when promotions pull back?
- Will a new flavor, pack or RTD earn a repeat?
- Are shoppers trading to value tiers or store brands?
Each of these maps to a variable page with the full method, linked below.
Which Neon Blue studies answer them?
| Analyst question | Study to run | Audience | What comes back |
|---|---|---|---|
| How much volume does a price increase cost? | Price ladder on current packs | Brand buyers by frequency and income | Keep, buy less, trade down, switch or stop |
| Is share moving between brands? | Last-purchase rebuild and next-purchase intent | Category buyers | Next-buy share by brand, with reasons |
| Are occasions changing? | Occasion rebuild | Drinkers by occasion type | Occasion mix and spend per occasion |
| What happens when deals pull back? | Full-price purchase intent | Buyers split by deal use | Buy same, buy less, wait, switch |
| Will the launch repeat? | Trial and repeat intent | Brand buyers, rival buyers, non-buyers | Trial timing, repeat and what it replaces |
| Are shoppers trading down? | Tier and brand choice over time | Category buyers who changed | Trade-down share and stickiness |
How do you read the volume cost of a price increase?
Show brand buyers the pack at today's price and at the new price, and ask keep, buy less, trade to a cheaper tier, switch brands or stop. Weight by volume share. Price increase tolerance has the full method.
How do you tell brand switching from category exit?
Ask what they bought last and what they plan next at today's prices. A move to another brand is switching. A move to a different drink or to "nothing this week" is category exit. Brand switching and category share shifts cover both reads.
How do you test promotions and launches?
For promotions, remove the deal and ask whether shoppers still buy, wait or switch. That is the core of promotion sensitivity. For launches, ask trial timing, repeat and what comes out of the basket. Unit demand for a launch walks through the method. Related staples framing sits on consumer research for consumer staples analysts.
What does a beverages study look like?
Hypothetical: a spirits company has taken price and says premiumization is intact. The analyst wants to know whether heavy at-home buyers still pick the brand's higher tier, or trade to a value label before the next print.
- Study question: "On your next at-home drinks purchase, this bottle is at its current shelf price and a lower-priced option from another brand is next to it. Which would you buy, how many, and would you buy less often than you do now?"
- Audience: adults who bought the brand in the last ninety days, split by occasion (at-home vs on-premise), income and whether their last buy was the premium or standard tier.
- Follow-ups: which occasions they would cut first, and what would bring them back to the higher tier.
Example output layout (illustrative, not a real result)
The shape of a Neon Blue beverage read. Cells are blank on purpose; a real study fills them.
| Segment | Stay with brand tier | Trade to value tier | Switch brand | Buy less often | Occasions cut first |
|---|---|---|---|---|---|
| At-home, premium last buy | __% | __% | __% | __% | Coded themes |
| At-home, standard last buy | __% | __% | __% | __% | Coded themes |
| On-premise heavy | __% | __% | __% | __% | Coded themes |
How the analyst reads it: if premium at-home buyers stay, the mix assumption holds. If they trade to value or cut occasions, volume risk sits in the biggest margin pool. Both lines go into the model labeled as simulated.
Want this run on your own name? Neon Blue's first study is free: start a free first study.
When should beverages analysts run these studies?
After a price increase, a promotional reset, a new pack or flavor launch, or a shift in on-premise traffic, and before the quarter closes. A repeat read with the same questions each quarter gives a trend to line up against reported volume and price/mix. Pre-earnings consumer checks lays out the calendar.
What can't a shopper study see?
- Retailer shelf space, delistings and distributor inventory.
- Excise and tax changes that move shelf prices between reads.
- On-premise staffing and hours, which change occasions without changing at-home intent.
- Treat each read as one directional input, not a settled number.
Questions about consumer research for beverages and spirits analysts
What consumer data do beverages analysts use?
Mostly scanner, distributor and card data for what already sold, plus channel checks. A Neon Blue study adds why drinkers change brands, tiers and occasions. See how simulated consumer data differs from card panel data.
Can a study isolate one brand's buyers?
Yes. The audience is defined as recent buyers of that brand, cut by occasion, frequency, income and channel. You can name the brand in the study.
Can it separate at-home from on-premise?
Yes. Screen on occasion and ask the price and brand questions inside each group. At-home and on-premise often move on different calendars.
Does Neon Blue predict beverage earnings or stock moves?
No. Neon Blue answers the shopper variables in your model, such as volume response or brand share. It doesn't make stock calls or give price targets.
How do I start a free first study?
Bring the brand, the quarter and the volume or mix assumption you trust least. Neon Blue's first study is free. Start a free first study