Decision intelligence for guided shopping
See what shoppers consider before they buy.
Halytic turns shopping path behavior into decision intelligence. Understand what shoppers considered, which products earned attention, and how paths formed before purchase.
Halytic decision readout
Shopping path & consideration signals
SKU exposure concentration
Top 3 SKUs
44% of recommendation exposure
Multi-item vs single-product paths
2.3x
illustrative path value pattern
Bundle gaps
Serums × Treatments
largest under-paired category path
Illustrative path value
$146
sample median
Routine path mix
Illustrative data
The problem
Analytics show what happened. Decision intelligence explains why it happened.
Teams may see quiz starts, conversions, or basic collection performance. That still leaves the catalog routing story hard to read — and it rarely explains which products shoppers considered before they acted.
Halytic focuses on SKU exposure, routine paths, bundle behavior, and basket construction inside guided experiences. You see which products are surfaced, paired, and built into stronger consideration patterns — not just which metrics moved.
What Halytic analyzes
Turn shopping path behavior into merchandising intelligence.
Across quizzes, bundles, collection navigation, and guided shopping experiences — the behavior inside the experience, not vanity metrics alone.
SKU Distribution
See which products get the most exposure and which products are under-routed.
Routine / Basket Paths
Compare full-routine behavior across multi-item vs single-product paths.
Bundle Performance
Identify which product pairs and categories appear in stronger basket composition patterns.
Path Value Signals
Understand how guided sessions relate to basket composition and next-step intent.
Sample report preview
Decision intelligence readout — not another analytics dashboard.
The example below uses illustrative shopping path behavior to show the type of readout a pilot can produce: what shoppers considered, how paths formed, and where the catalog story breaks down.
Sample data shown for illustration. Live pilots use the brand's actual guided-shopping and catalog behavior.
Sample insight
Recommendation exposure may be too concentrated.
A small set of hero SKUs may be capturing most recommendation exposure. Complementary categories may be under-paired in routine paths — a consideration gap, not just a traffic gap.
Top 3 SKUs
44%
of recommendation exposure
Illustrative path value
$146
sample median
Largest cross-sell gap
Serums × Treatments
under-paired in paths
Routine opportunity
Add one
complementary step
How it works
A focused pilot with a concrete merchandising readout.
Review the shopping path
Map the quiz, product finder, bundle, collection, or routine path shoppers are using today.
Analyze SKU and basket behavior
Read the recommendations, pairings, routine paths, and basket composition patterns behind the experience.
Deliver a merchandising readout with concrete tests
Turn the analysis into clear opportunities your ecommerce or growth team can evaluate quickly.
Pilot
Now accepting a small number of decision intelligence pilots.
For beauty and ecommerce brands using quizzes, product finders, bundles, collections, routine builders, or guided shopping paths — including BoozeButler-powered spirits discovery.
Contact: raymond@halytic.ai