Sephora Transforms
Its Market Intelligence Capabilitie
with Competitive Data Solution
Discover how Sephora, a global luxury beauty leader, streamlined its
competitive intelligence across 13 countries using Competera's Competitive
Data solution, processing over 10.9 million data points monthly.
Executive Summary
Sephora, a multinational beauty retailer with 2,700 stores across 35 countries, required a scalable and centralized competitive intelligence solution to strengthen
its market position. Previously, fragmented local providers led to inconsistent
and unreliable data, complicating efforts to maintain unified insights across markets. A critical challenge was accurately and consistently monitoring competitors' coupon usage — a significant sales driver, particularly in the fragrance category.
Challenges
- Fragmented competitive data from local providers, causing inconsistent insights across markets
- Difficulty accurately tracking competitor coupon usage and promotional discounts, especially in high-impact categories like fragrances
- Complex operational requirements managing pricing across diverse online and offline sales channels
- Limited analytics on customer responses to pricing changes, restricting strategic decision-making
Solution
Sephora adopted Competera’s Competitive Data solution, featuring:
-
Centralized market intelligence across all countries
-
Comprehensive coupon and promotional tracking at the product, brand, and category level
- Historical analytics on stock availability and competitor brand presence
- Detailed product availability and delivery terms analysis
- Robust customer sentiment insights
Implementation
Sephora strategically executed a successful pilot in Germany and Poland (1,000 SKUs per market), which rapidly scaled to 13 countries.
Key Results
98%
match quality and 99% data accuracy
10.9
million data points delivered monthly
98%
SLA compliance across markets
CONTINUED PARTNERSHIP
Building on this success, Sephora continues to expand the Competitive Data solution across additional markets, maintaining high standards of data quality while scaling operations globally.
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Decreased time for manual assortment analysis
Decreased time for manual assortment analysis
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