5.2.4 Product Marketing Analysis Using Data Boutique’s Data: Grocery and Consumer Packaged Goods (CPG)

Updated by Andrea Squatrito

Product Marketing Analysis Using Data Boutique’s Data: Grocery and Consumer Packaged Goods (CPG)

The grocery and CPG industry is highly responsive to price changes, promotions, and seasonal demand fluctuations. This article demonstrates how to leverage Data Boutique’s GROCERY-PLP schema for insights into price sensitivity, targeted promotions, and inventory management within the CPG sector.

Overview of GROCERY-PLP Schema Fields for CPG Marketing

The GROCERY-PLP schema includes the following fields relevant to grocery and CPG analysis:

  • website_name: Name of the website where the product is listed.
  • competence_date: Date of the data capture (YYYY-MM-DD).
  • country_code and currency_code: Country and currency codes (ISO 3-letter format).
  • store_id: Optional identifier for physical store location.
  • product_code and product_std_code: Website and standard product codes (e.g., GTIN, ASIN).
  • std_type: Type of standard code used.
  • brand: Brand of the product.
  • product_title: Product name or title.
  • category1 through category10: Hierarchical category levels for detailed navigation.
  • full_price: Original price, excluding promotions.
  • price: Actual price offered, including any promotions.
  • ppu and unit_type: Price per unit and corresponding unit type.
  • promotion_type: Type of promotion applied.
  • promotion_end_date: End date of the promotion.
  • package_desc: Optional package information.
  • additional_tags and additional_content: Identifying tags and additional product details.
  • itemurl and imageurl: URLs to the product page and image.

1. Targeted Promotion and Price Sensitivity Analysis

Purpose

Understanding price sensitivity in CPG helps marketers plan effective promotions. Analyzing how frequently products are discounted and the depth of discounts provides insights into consumer demand and optimal pricing.

Step 1: Analyzing Discount Frequency and Depth by Country

Track the frequency and depth of discounts across brands and countries to understand consumer price sensitivity.

SELECT
              product_code,
              brand,
              country_code,
              COUNT(CASE WHEN price < full_price THEN 1 END) AS discount_frequency,
              AVG((full_price - price) / full_price * 100) AS avg_discount_percentage
          FROM
              GROCERY_PLP_data
          GROUP BY
              product_code, brand, country_code;

Step 2: Visualizing Price Sensitivity in BI Tools

In a BI tool:

  • Discount Frequency by Country: Track discount frequency across countries to identify regions with higher price sensitivity.
  • Average Discount Depth: Display average discount percentage by brand to gauge consumer demand for discounted items.

2. Seasonal Demand Analysis and Campaign Planning

Purpose

Seasonal demand patterns are key for CPG, particularly during holidays or events. Analyzing monthly pricing and promotions can help marketers time campaigns to maximize impact.

Analyze monthly price trends by product category and country to identify seasonal demand peaks.

SELECT
              product_code,
              brand,
              country_code,
              DATE_TRUNC('month', competence_date) AS month,
              AVG(full_price) AS avg_full_price,
              AVG(price) AS avg_discounted_price
          FROM
              GROCERY_PLP_data
          GROUP BY
              product_code, brand, country_code, month
          ORDER BY
              month;
  • Higher Average Prices: High average prices can indicate peak demand periods, where discounts are less frequent.
  • Discount Frequency in Seasonal Cycles: Analyze discount frequency over time to determine optimal promotion timing.

3. Inventory Management and Stock Availability Analysis

Purpose

Effective inventory management ensures that high-demand items are available in sufficient quantity. Tracking stock levels and promotion effectiveness helps prevent stockouts and better allocate inventory.

Step 1: Tracking Product Stockouts by Country

Use SQL to identify potential stockouts across regions, particularly for essential CPG items.

SELECT
              product_code,
              brand,
              country_code,
              competence_date,
              COUNT(CASE WHEN price IS NULL THEN 1 END) AS stockouts
          FROM
              GROCERY_PLP_data
          GROUP BY
              product_code, brand, country_code, competence_date;

Step 2: Visualizing Inventory Patterns

In a BI tool:

  • Stockout Frequency by Month: Track stockout frequency to identify periods of high demand or inventory strain.
  • Inventory Turnover by Product: Display inventory turnover rates to assess which products require more frequent restocking.

4. Regional Price Comparison and Competitive Positioning

Purpose

Cross-region price comparisons provide insight into regional demand elasticity and help identify opportunities for competitive pricing adjustments.

Step 1: Comparing Regional Prices and Discount Depths

Calculate the average prices and discount levels by region to find opportunities for localized pricing or promotions.

SELECT
              product_code,
              brand,
              country_code,
              AVG(full_price) AS avg_full_price,
              AVG(price) AS avg_discounted_price,
              AVG(CASE WHEN price < full_price THEN 1 ELSE 0 END) * 100 AS discount_frequency
          FROM
              GROCERY_PLP_data
          GROUP BY
              product_code, brand, country_code;

Step 2: Adjusting Pricing Strategies by Region

Visualize price and discount data across regions to inform tailored promotions and identify regions where deeper discounts are likely to increase sales.

Conclusion and Marketing Insights

With Data Boutique’s GROCERY-PLP schema, CPG marketers can gain critical insights into consumer price sensitivity, seasonality, and inventory management. By analyzing discount frequency, regional pricing, and seasonal cycles, brands can optimize their promotional strategies and align them with consumer demand for more impactful campaigns.

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