Phenx

Use Cases · Retail

Every shopper, the right shelf.

Recommendation engines, sales forecasting, review analytics, and location intelligence — built on your transaction data and tuned to margin, not just clicks.

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Real-time

personalization at the decision moment

90 Days

from kickoff to production

30+

projects across pricing, risk, fraud and operations

Bestseller lists aren’t personalization.

Generic engines surface what everyone already bought, forecasts miss the seasonal spike, and thousands of reviews sit unread while the answer to “what should we fix” is inside them.

Retail wins on the non-obvious match — the product this customer takes, the store this neighborhood needs, the demand curve this SKU actually follows.

How it works

Recommend what converts

Engines built on behavior, preference, and purchase history — tailored suggestions that lift basket size and repeat visits.

Forecast the demand curve

SKU-level sales forecasting from your history and market trends — stock the spike, skip the overstock.

Read every review

LLM analytics across customer feedback: sentiment, emerging issues, and the fixes that actually move satisfaction.

Pick the next location

Site selection models on social, review, and demographic signals — where your store format wins before you sign the lease.

What you get

  • A recommendation engine tuned to margin and retention, not just clicks
  • SKU-level demand forecasts for inventory and marketing planning
  • Review-analytics pipeline surfacing sentiment and emerging issues
  • Location scoring for expansion decisions, plus NLP-powered site search

Start with Structure

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20 minutes. We’ll show you where variance is costing you money.

You'll leave with

3 dominant forcesTop noise sourcesPredictability Score90-day plan
Only 4 diagnostic slots available per month.
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