MARKET SHARE / RETAIL
People choose your product where it is available. How does it reach more baskets?
How we would evaluate market share growth for a beverage brand through distribution, availability, and choice at the shelf.
PLEASE NOTEConceptual scenario. The brand, market, and all demonstration figures are fictional. They are not client results or forecasts.
The situation we would examine
A nonalcoholic beverage brand sells through independent stores and a regional chain. Its team sees larger distributor orders and asks for a national campaign. It does not yet know whether the product reaches more shoppers or whether some growth remains in intermediary inventory.
We assume production can support a limited expansion. We want to learn where demand exists, which distribution can serve it, and whether the product economics justify investment.
Sales rise. What happens to share?
Compare fictional sales values for the same category, store universe, period basis, and currency. Change is shown in percentage points relative to the 4% reference.
Fictional data and situations.A local demonstration, without client results. Your choices do not send data, inquiries, or bookings.
Reference
All values are fictional and expressed in RON.
- Brand sales
- RON 12,000
- Category sales
- RON 300,000
Change from reference: 0 percentage points
The brand accounts for 4% of sales in this defined universe.
What needs checking
Changing market coverage, price basis, or units would make the comparison misleading.
Read all variations
Reference
Sales values: All values are fictional and expressed in RON.
- Brand sales
- RON 12,000
- Category sales
- RON 300,000
Change from reference: 0 percentage points
What we can calculate: The brand accounts for 4% of sales in this defined universe.
Check: Changing market coverage, price basis, or units would make the comparison misleading.
More sales, same share
Sales values: All values are fictional and expressed in RON.
- Brand sales
- RON 15,000
- Category sales
- RON 375,000
Change from reference: 0 percentage points
What we can calculate: Brand sales and category sales both rise by 25%. Share is unchanged.
Check: Changing market coverage, price basis, or units would make the comparison misleading.
Higher share
Sales values: All values are fictional and expressed in RON.
- Brand sales
- RON 18,000
- Category sales
- RON 360,000
Change from reference: +1 percentage point
What we can calculate: The share is 5%, a gain of one percentage point from the reference. This is an arithmetic example, not a forecast.
Check: Changing market coverage, price basis, or units would make the comparison misleading.
Missing market total
Sales values: All values are fictional and expressed in RON.
- Brand sales
- RON 12,000
- Category sales
- Unknown
What we can calculate: Brand revenue is known, but market share cannot be inferred without the comparable category total.
Check: Changing market coverage, price basis, or units would make the comparison misleading.
Zero denominator
Sales values: All values are fictional and expressed in RON.
- Brand sales
- RON 0
- Category sales
- RON 0
What we can calculate: Division by zero does not produce a market-share estimate. Review the period and the underlying data.
Check: Changing market coverage, price basis, or units would make the comparison misleading.
What we would investigate
We would separate distributor sales from consumer sales. We would compare stores, inventory, days out of stock, prices, and sales per store per week. We would check whether promotions, seasonality, and changes in store coverage explain part of the difference.
We would add shelf observation and conversations with retailers and shoppers. The product may be missing from relevant stores, hard to find, or available but rarely chosen. Distribution and sales velocity are also part of the commercial analysis described by NIQ. [1]
Working hypotheses
Our first hypothesis is that some stores show strong sales and comparable demand exists in areas where the brand is unavailable. The second is that some listings produce weak sales because of stock or presentation. The third is that the offer does not provide a sufficient reason to choose it over alternatives.
We would keep these hypotheses separate. More listings do not automatically solve a weak offer, and a campaign can create demand where the product cannot be purchased.
The proposed concept and decision
We would begin with a bounded group of stores and an offer supported by inventory. Expansion would reflect stores’ category sales and replenishment capacity. Advertising would point to actual purchase locations and use demonstrable product attributes.
The pilot could compare similar stores using a phased rollout. If random allocation is impractical, we would document starting differences and treat the conclusion as an estimate. The period would cover enough replenishment and buying cycles for the category under review.
What we would build
We would prepare a distribution opportunity map, the listing case, and a joint plan with the sales team. We would develop messages, shelf materials, a store locator page, and local campaigns. Inventory, sales, and media reporting would use the same market definition.
The client and its partners would decide commercial terms, deliveries, and capacity. NOT MORE. could lead the analysis, positioning, creative, campaigns, and agreed measurement, alongside the people who can implement changes in stores.
How we would measure
| Indicator | Definition and boundary |
|---|---|
| Value and volume share | Brand relative to category in the same store universe and period. |
| Numeric distribution | Stores selling the product divided by eligible stores in the universe. |
| Category-weighted distribution | Category sales in stores selling the brand divided by category sales across the defined store universe, for the same period. |
| Sales velocity | Comparable liters or units per store per week, with stockouts reported separately. |
| Repeat buying | Only when shopper data can track the behavior. |
| Commercial contribution | What remains after product, distribution, promotion, and activation costs under the agreed financial convention. |
If the source covers one chain, we would report share within that chain. Without category sales, we would report distribution and brand sales, leaving market share unknown.
What could change the recommendation
A product with repeat demand but poor availability would make inventory and distribution the priority. Expansion with high returns and weak contribution would require an offer review. A decline in the whole category would change how we interpret sales and the acceptable scale of investment.
Where might people choose your product if it were available and easy to understand?
Methodological source
[1] NIQ, How to use retail data to gain market share. Reference for the role of retail data; it does not supply the fictional figures in this scenario.