For funds
Category share shifts: how simulated consumer surveys estimate them
TL;DR
- A category share shift is a change in which brands, retailers or formats get the next purchase. Reported share arrives late and says little about why it moved.
- A Neon Blue study rebuilds each buyer's last purchase in the category, then asks about the next one. The gap between the two is the shift.
- The output is a last-versus-next share table by segment, with the flows between brands and the reasons. It is a labeled input for your revenue and share assumptions, not 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 category's buyers, 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. For funds, a share study answers one model question: which brands will win the next purchase in this category, and whose buyers are they taking?
What is a category share shift, and why does it matter to a model?
Most consumer models start from category growth and the company's share of it. When share moves, it usually moves in one of three ways:
- Brand to brand. A rival's launch or price cut pulls buyers. This is the core of brand switching.
- Brand to store brand. Private label gains when budgets tighten. See trade-down behavior.
- Format or channel. Buyers move from one kind of product or store to another, such as from dine-in to delivery, or from grocery to club.
Scanner and card data show the result once it is in the numbers. A survey of buyers shows the intent before it is, and the reason behind it, which tells you whether the shift is likely to last.
How does a Neon Blue study estimate a share shift?
- Define the audience as category buyers, not brand buyers. You need the rival's buyers in the room to see flows in both directions.
- Rebuild the last purchase. Brand, format, where bought and roughly what they paid.
- Ask about the next purchase. Same brand, a different brand, the store brand, or a different format. Ask at today's prices.
- Ask why. Price, a new product, availability, a promotion, a recommendation, or a change in what the household needs.
- Weight by volume. A heavy buyer moving matters more than a light buyer moving. How simulated audiences work explains how each simulated buyer is grounded.
What questions go into a category share study?
| Question | Model input | Why it matters |
|---|---|---|
| Which brand did you buy last time, and where? | Current share by brand and channel | The baseline |
| Which brand do you plan to buy next time? | Next-purchase share | The forward read |
| If different, why are you changing? | Driver of the shift | Separates price from product or availability |
| Have you tried the new product from [brand]? | Launch penetration | Shows whether a launch is the source of the gain |
| Would you go back to your old brand at a lower price? | Durability | A price-led move is easier to reverse |
| How much of the category do you buy each month? | Volume weight | Turns share of buyers into share of volume |
What does a category share study look like?
Hypothetical: a snack maker says its new better-for-you line is taking share. The analyst wants to know whether the gain comes from the company's own core line, from rivals, or from new buyers in the category.
- Study question: "Think about the last time you bought salty snacks. Which brand did you buy? Now think about your next purchase at today's prices. Which brand do you expect to buy, and if it is different, why?"
- Audience: households that bought salty snacks in the last 30 days, split by heavy and light buyers and by whether they have tried the new line.
- Follow-ups: what the new line replaced in their basket, and whether they would keep buying it if it went up in price.
Example output layout (illustrative, not a real result)
The shape of a Neon Blue share read. Cells are blank on purpose; a real study fills them.
| Segment | Last: company core | Last: rival brands | Last: store brand | Next: new line | Next: same as last | Main reason for change |
|---|---|---|---|---|---|---|
| Heavy buyers, tried new line | __% | __% | __% | __% | __% | Coded themes with sample verbatims |
| Heavy buyers, not tried | __% | __% | __% | __% | __% | Coded themes with sample verbatims |
| Light buyers | __% | __% | __% | __% | __% | Coded themes with sample verbatims |
How the analyst reads it: if most of the new line's next-purchase share comes from people who last bought the company's own core, the launch is moving volume between the company's own products. If it comes from rival and store brand buyers, the share gain is real. The flows go into the share line labeled as simulated. Unit demand for a launch covers how to size the new line itself.
Want this run on your own name? Neon Blue's first study is free: start a free first study.
When should a share study run against the reporting calendar?
Run it after a rival launch or price move, before the change shows in scanner data, and again a few weeks later to see whether the next-purchase intent turned into a habit. A steady quarterly read with the same questions gives a trend line you can place next to reported share. The timing logic is the same as in pre-earnings consumer checks.
Which sectors is this most useful in?
- Consumer staples: where launches, promotions and private label move share quarter to quarter. See consumer research for staples analysts.
- Restaurants: where share of visits moves between chains and formats. See consumer research for restaurant analysts.
- Private equity diligence: where a target's share trend decides the growth case. See consumer research for PE commercial due diligence.
What are the limits of a survey-based share read?
- Intent to switch overstates actual switching. Read the direction and the flows, not the headline share.
- It can't see shelf space, distribution gains or out-of-stocks, which move share without any change in what people want.
- Small brands need enough buyers in the audience to read. Define cells around them.
- Neon Blue tests simulated answers against real responses on attitudinal and intent questions, including brand preference. Treat the read as one directional input, not a settled number.
Questions about estimating category share shifts
What is a category share shift?
It is a change in which brands, retailers or formats get buyers' purchases within a category. It shows up in reported market share after the fact.
How is it different from brand switching?
Brand switching looks at one brand's buyers and where they go. A share study looks at the whole category, so it shows flows in every direction, including new buyers and the store brand.
Can a survey tell real share gains from a company taking from itself?
Yes. Rebuild the last purchase, then ask about the next one. If the new product's buyers last bought the same company's older product, the gain is mostly internal.
Does this predict reported market share?
No. It gives the direction of the shift, the flows and the reasons, as an input to your share assumption. Neon Blue doesn't make stock calls or give price targets.
How do I start a free first study?
Bring the category, the brands that matter and the share assumption you trust least. Neon Blue's first study is free. Start a free first study