Segmentation Study Framework Builder

Example output

Segmentation study framework — Fortivo RTD protein beverages

Recommended approach
A needs-and-occasion-based segmentation, not a purely attitudinal or demographic one. Your business question — one positioning versus distinct sub-lines — is fundamentally a question about whether different consumers want the product to do different jobs. A needs-based approach directly answers that; a purely demographic segmentation (age, income) would tell you who buys but not why, which won't resolve the sub-line decision.

Candidate variables to measure
1. Primary need driving purchase: muscle-building/performance vs. general protein top-up vs. meal replacement vs. weight management. This is the core variable your business question hinges on; build the survey around it first.
2. Consumption occasion: post-workout, meal replacement, mid-day snack, on-the-go. Occasion often predicts sub-line fit better than stated identity ("I'm a fitness person") does.
3. Category involvement: how many protein/RTD brands they buy, how they discover new ones. Distinguishes category-engaged experimenters from low-involvement convenience buyers.
4. Price sensitivity and format preference (bottle vs. can vs. powder-adjacent). A likely differentiator between the two consumer types you suspect exist.
5. Attitudinal statements on fitness identity and nutrition beliefs, included but secondary to need and occasion; attitudes alone tend to produce segments people don't recognize themselves in.

Target segment count
Aim for 3-5 segments. Given your working hypothesis of two broad types (hardcore fitness vs. casual snacker), the data will very likely split further once occasion and need are measured properly; two segments is usually too coarse to be commercially actionable, and more than five becomes hard for a brand team to design against. Treat 3-5 as the target range to solve for, not a fixed number decided in advance; let the data decide within that range rather than forcing a preset structure.

Data collection plan
Quantitative (primary): your planned n=1,200 survey, structured around the five variables above, with segmentation-specific analysis (cluster analysis or latent class analysis) run on the need, occasion, and behavioral variables; treat the attitudinal statements as descriptive overlays on the resulting clusters, not primary segmentation inputs.
Qualitative (secondary): use your planned follow-up interviews AFTER an initial quant segmentation solution exists, not before; the goal is to sanity-check whether the statistical segments actually sound like real people your team recognizes, and to pull the language each segment uses to describe their own needs.

Validation criteria
A segmentation solution should only be adopted if it passes all of these:
1. Actionable — your marketing and innovation teams can design a genuinely different message, product, or channel plan for each segment; if two segments would get the same plan anyway, merge them.
2. Sizeable — each segment is large enough within your addressable market to be worth building against; a statistically distinct 4% segment may not justify a sub-line.
3. Stable — re-running the cluster solution on a held-out portion of the sample produces materially similar segments, not a fragile split.
4. Recognizable — when you read the qualitative interviews back against each segment's profile, someone on your team says "yes, I know that person," not "this sounds like a spreadsheet."
5. Reachable — you can identify or target this segment through media, retail, or CRM in the real world, not just in survey data.

Methodology brief summary
Fortivo should field a needs-and-occasion-led quantitative segmentation (n=1,200) with cluster analysis on five core variable groups, targeting a 3-5 segment solution, validated by qualitative follow-ups and the five criteria above before any sub-line decision is made. This directly answers the one-positioning-versus-multiple-sub-lines question rather than producing an interesting but unusable typology.

Note: exact cluster counts, fit statistics, and segment sizes cannot be determined until the data is collected; this framework sets up the study to produce a decision-ready answer, but the number and shape of Fortivo's actual segments is a finding, not an assumption to state in advance.

Want this turned into a full research vendor brief, or a draft questionnaire covering the five variable groups?