What your BI already does
It ranks SKUs by revenue, margin, and volume. The loss-making ones are easy to see.
Ask Sena which low-margin SKUs are real entry points and what happens to the rest of your sales if you cut one.
A SKU shows negative margin, so you want to cut it. The customer ripple stays hidden.
Which low-margin SKUs are worth keeping as entry points, territory by territory.
FMCGBeveragesSnack FoodsSpiritsTelecom
Sena decision AI by Rwazi
Decision AI with access to real-world dataLarge portfolios carry hundreds of SKUs, and some lose money on their own. Your BI already flags them. Cutting one is the part it leaves you guessing.
Removing a loss-making SKU can collapse sales of the profitable products next to it. Answering that needs financial data, co-purchase patterns, consumer activity, and coverage read together. A standalone margin report holds one of the four.
So teams do one of two things. They keep the SKU forever out of fear. They cut on standalone margin and lose the customers who came in through it. An SKU profitability analysis that stops at the margin line leads to both.
Upload SKU-level P&L, cost structure, trade spend, and pricing by territory and channel. Sena reads your ERP exports and your CSVs.
It looks for SKUs that keep appearing together in the same outlets, territories, and baskets. A low-margin SKU that always travels with your high-margin lines is an entry-point candidate.
Strong volume on a low-margin SKU points to a portfolio role its own economics hide.
Ask what cutting a SKU in a territory does to adjacent product sales. Sena returns a directional simulation built on your historical patterns.
Some relationships appear only when financial, coverage, and demand data are read together. Those are the SKUs your team would have missed.
Identify which SKUs are net positive at the portfolio level
See how Sena works →Teams also apply these strategies for SKU management in e-commerce, where basket data shows the same entry-point pattern.
| Capability | Role in this use case |
|---|---|
| Sena (Decision AI) | Core engine. It reads your financial and ERP data, finds the co-purchase patterns, and returns entry-point candidates with what-if simulations. |
| Sena Connect and Integrations | Brings your data in by CSV or Excel upload. A direct ERP integration follows once you validate the POC. |
| Sena Consumer Activity | Optional. Commission a targeted read to confirm whether consumers treat a flagged SKU as their entry to the brand. |
| Sena Computer Vision | Optional. Verify shelf presence and store coverage for entry-point SKUs. Low coverage on a real entry point is a growth opening. |
Both optional layers validate what the financial analysis already surfaced. The core answer comes from your own data.
It ranks SKUs by revenue, margin, and volume. The loss-making ones are easy to see.
Sena models the second-order effect. Cut this SKU in this territory, and here is the estimated hit to everything sold beside it.
Commission a consumer read or a coverage check to confirm the call before you act on it.
Sena
Illustrative interface. Numbers are an example, not a Rwazi result.
Model profitability at the portfolio level, and justify the SKUs worth keeping despite negative individual margin.
Decide which products to keep, cut, or reposition by their true portfolio role.
Strategy solutions →Know which entry-point products matter in which markets.
Sales solutions →Protect store coverage for the entry-point products that pull the rest of the category.
Price entry-point SKUs low enough to acquire and high enough that margin holds.
A demo takes about 20 minutes; first decisions are made days after kickoff.
Every signal comes from a real person, with consent, back to a named source.
Sena adds what people actually buy beyond your four walls.
Model what happens before you cut, add, or reposition a SKU.
See the use case → UC · Marketing EffectivenessSee which promotions bring profitable volume and which give margin away.
See the use case → UC · Coverage & ComplianceUnderstand why the same product wins in one territory and lags in another.
See the use case →Tell us the decision you are weighing, and we will bring the market read to the conversation.
Bring the decision in front of you and we will run the first read against it on the call.