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Sena shows what wins the beauty aisle

Sena Decision AI shows beauty and personal care teams which products win the shelf and why shoppers switch. Every figure traces to a shelf photo, a shopper answer, or the team's own files.

  • 190+ countries
  • 5M+ consumer network
  • 250+ integrations
Live readingsExample beauty
Shades confirmed on shelf
1,617 / 1,860
Price gap to the rival shade
+7%
Above the rival in 11 stores
Why shoppers switch shades
Match
Named in 31% of switches
Monthly sales at stake
101,574
243 shade listings missing
every figure opens a shelf photo or a shopper answer
THE BEAUTY AISLE

Shoppers decide in the aisle

Beauty analytics often starts with sell-in and online reviews. Across the beauty and personal care industry, a missing shade, a rival's lower price, or a new launch beside it sends the shopper elsewhere.

Missing shades lose the sale

Sell-in shows which stores bought the line. The shelf shows which shades a shopper can find.

Sena:Sena captures geo-verified shelf photos store by store and matches each shade to its SKU.

Launches chase skincare industry trends

Concept scores shape the launch list. Shoppers judge a new product against the one they already use.

Sena:Sena captures what shoppers would pay for a new product and which one it would replace.

Campaigns report reach before results

Media reports show who saw the campaign. The shelf and the shopper show whether it moved the sale.

Sena:Sena captures shelf photos in the same stores and shopper answers in the same segment, before and after a campaign.

The decisions

Four decisions beauty teams make

Beauty analytics turns beauty consumer trends and shelf photos into four calls on launch, campaign, shelf, and shade range.

Decision 01

Test a new formula before the launch budget

Shoppers in the target market state what they would pay for each variant and which product it would replace. Sena reads shelf photos of the aisle it will join.

Decides:Which shades and formulas launch, at what price, and where first.

See innovation decisions →
Decision 02

Fund the campaigns that move the shelf

Sena captures shelf photos in the same stores and shopper answers in the same segment, before and after a campaign, beside the team's own sales.

Decides:Which campaign earns the next budget, and which step carried the lift.

See marketing effectiveness measurement →
Decision 03

Hold shelf space and price against rivals

Sena reads the products and price tags in each shelf photo, so share of shelf and price gaps show by retailer and store.

Decides:Where to defend space, correct price, or match a rival.

See category decisions →
Decision 04

Trim the shade range and keep the shopper

Sena reads sales files by SKU beside the shades shoppers would buy if one left the shelf.

Decides:Which shades leave the range and which stay to hold the shopper.

See SKU rationalization analysis →
HOW A TEAM CHECKS EACH SHELF

Each beauty figure traces to its capture

Sena ties every figure to the photo or answer behind it, so a team checks each store against its own sell-in.

A geo-verified photo per store

Each shelf reading carries its photo, location, and date. A shade counts as present once a photo confirms it.

Shopper answers, checked first

Each shade reason comes from a shopper who chose to share it. Every capture clears a multi-level QA flow. Sena declines a capture that misses the check, and the decline stays visible.

SHADE GAP

Beauty analytics counts the missing shades

A beauty industry analysis of the shelf starts with two counts: the shade listings the plan puts in each store and the listings a photo confirms. Sena captures the second count and splits the gap by retailer, store type, and shade.

  • Drugstores, beauty specialists, and mass retailers counted separately
  • Each missing shade matched to its SKU
  • Sales at stake, from the team's sales per shade listing
Shade gap calculatorExample figures
ConfirmedMissing
Missing shade listings
243
Monthly sales at stake
101,574

The shade gap calculator shows missing shade listings and monthly sales at stake.

A walkthrough on one beauty category

A walkthrough runs Sena on one beauty category in one market, from shelf photo to the shade decision.

By team

Which beauty team owns the question?

Pick the closest fit, and the walkthrough starts from that team's question.

How it works

How Sena answers a market question

Step 01 · Capture

Capture

Sena captures geo-verified photos and consumer activity in the markets a question names, when the question needs it.

Step 02 · Read

Read

Sena reads those captures beside the files and systems already in use, across 250+ integrations.

Step 03 · Compare

Compare

Sena compares the market against the plan and shows each gap, with every figure traced to its source.

TWO WAYS TO READ BEAUTY

What a photo adds to beauty analytics

AreaCommon methodSena
Shade presenceCosmetics industry data from sell-in and planogram filesGeo-verified photos confirm each shade on the shelf
Launch testsSkincare industry trends and concept scoresShoppers in the launch market state what they would pay and which product the launch would replace
Campaign resultsReach and engagement reportsShelf photos from the same stores and answers from the same segment, before and after
Shelf priceBeauty products industry list prices on paperThe price tag on the shelf, beside the rival
AuditingSell-in and review reports matched by handEach shade figure opens its photo or answer

One beauty category, one market, one decision

Talk to the Rwazi team about one beauty category, one market, and the decision on the table this quarter.

FAQ

Questions the beauty products industry asks

01 What is beauty analytics?
Beauty analytics is the practice of reading sales, shelf, and shopper signals to decide what to launch, where to place it, and at what price. Sena, a Decision AI with access to real-world data, brings decision intelligence to beauty and personal care industry teams by adding geo-verified shelf photos and consented shopper input to a team's sales data, so each figure traces to the photo or answer behind it.
02 Why do beauty industry trends differ by city?
Beauty industry trends shift by category and market, so a product that leads in one city can trail in the next. Sena captures what shoppers choose, compare, and would switch for in the markets a team names, so current trends come from shopper answers and shelf photos.
03 How do health and beauty industry trends differ by market?
Health and beauty industry trends move at different speeds in each market, shaped by local price, local shelves, and what shoppers already use. Sena captures shopper answers and shelf photos market by market, so a team compares the same category across three to five markets.
04 What does a beauty industry analysis cover?
A beauty industry analysis covers category growth, pricing, retail presence, and why shoppers choose one product over another. Sena adds the shelf and shopper parts: geo-verified photos of shade presence and price, and consented answers on what shoppers compared and would switch to.
05 How does Sena confirm each shade across the beauty retail industry?
Sena confirms each shade from a geo-verified photo captured in each store a question covers. Computer vision finds each product, matches the shade to its SKU, and reads the price tag beside it. A multi-level QA flow checks every capture before it counts toward a store's shade figure.
06 Where does Sena's beauty data come from?
Sena's beauty data comes from four sources: the team's uploaded files, its connected systems, consented input from shoppers in Sena's consumer network, and geo-verified shelf photos. A team reads that cosmetics industry data beside its own sales, with every figure traced to its capture or file.
07 Which systems does Sena connect to for beauty teams?
Sena connects to the systems beauty teams already run across 250+ integrations, including Salesforce, HubSpot, and Microsoft Dynamics, and reads uploaded Excel, CSV, and PDF files. Shelf photos and shopper answers join that data, so beauty analytics covers internal sales and the shelf in one answer.