Libnanews logoConsumer Price Index

Consumer Price Index Methodology

How prices are collected, normalized, matched, and published on Libnanews.

Real-time data quality

Operational indicators computed automatically from the pipeline.

Active sources

5

Last run status: ok

Last run at

09 May 2026, 03:37

Connector failures (24h): 1

Open anomalies

24

Needs review queue: 2351

Confirmed rate (7d)

43.18%

Avg score: 0.876

Matching quality by source (7d)

  • Metro Market Lebanon: 207/447 confirmed (46.31%) | Avg score: 0.876
  • Carrefour Lebanon: 122/340 confirmed (35.88%) | Avg score: 0.875
  • Spinneys Lebanon: 27/82 confirmed (32.93%) | Avg score: 0.859
  • Le Charcutier: 32/35 confirmed (91.43%) | Avg score: 0.950
  • SuperDokan Lebanon: 17/34 confirmed (50.00%) | Avg score: 0.847

1) Sources and frequency

  • Data comes from automated connectors per supermarket source.
  • The target pipeline is: scrape -> normalize -> match -> publish.
  • Collection runs daily, with manual trigger available in admin.

2) Product and price normalization

  • Each price keeps its original value and currency (USD, LBP, others).
  • A USD pivot is computed to compare chains on a common basis.
  • Formats are standardized: sizes (ml/l/g/kg), packs xN, and unit price.

3) Product matching

  • Raw listings are linked to canonical products with a similarity score.
  • Matching combines multilingual tokens, brand, size, unit, and category consistency.
  • Ambiguous cases are either provisional or sent to validation queue.

4) Publishing and confidence

  • Publishing states: published, provisional, or quarantined based on confidence.
  • Displayed confidence mixes scrape quality, matching quality, and unit consistency.
  • User validations can raise confidence for edge cases.

5) CPI and basket inflation

  • Libnanews CPI is calculated from a weighted Lebanon reference basket.
  • Monthly and yearly indicators are provided in USD and LBP.
  • If history is insufficient, the inflation section stays in data collection mode.

6) Known limitations

  • Some sources change HTML structure and may temporarily reduce coverage.
  • Classification errors may still happen on close variants (size/flavor/format).
  • In-store prices may differ from online prices depending on availability and local promotions.