Understanding everything about retail panels

In mass retail, brands are constantly looking for tools and methods to optimize their performance and market positioning.‍

Among these tools, distributor panels stand out as key instruments for manufacturers and brands keen to decipher the sales and distribution dynamics of their products.

What is a retail panel?

A retail panel is a marketing research tool that collects data systematically and continuously from a representative group of retail outlets. This data is then analyzed and provided back to manufacturers and brands in the mass retail sector.

This information offers valuable insights into sales, inventory, pricing, and other aspects related to product distribution within mass retail networks. The main objective is to understand the performance of products sold in supermarkets, track market and sales trends, and measure the effectiveness of marketing and sales strategies.

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The different types of panels

Depending on the type of product, market segment, or geographic area, retail panels vary. Here are 7 types commonly used in the industry:

1. Food retail panel: Focused on sales and consumption trends in supermarkets, hypermarkets, and other food retail outlets.

2. Non-food retail panel: Focused on non-food products, such as consumer electronics, household appliances, clothing, etc.

3. Specialized retail panel: Targets specific market segments such as pharmacies, DIY stores, garden centers, bookstores, etc.

4. Online retail panel: Focuses on sales made through e-commerce platforms, allowing for the analysis of online product performance.

5. International retail panel: Aggregates data from several countries to provide a global perspective on product performance on an international scale.

6. Regional retail panel: Provides detailed information on sales and distribution in specific regions, enabling finer analysis at a local or regional scale.

7. Retail panel by channel: Segmented by distribution channels (mass retail, specialized retail, direct sales, etc.), this type of panel helps to understand the unique dynamics of each channel.

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The main panel providers

These panels are often managed by specialized market research companies. In the mass retail sector, the main ones include:

1. NielsenIQ: One of the world's largest data analysis and performance measurement companies, offering insights into consumers and product performance in mass retail.

2. IRI (Information Resources, Inc.): Specializing in market data, analytics, and predictive solutions for the consumer goods, healthcare, and retail sectors.

3. Kantar: Provides a comprehensive range of market research services, including retail panels, and offers deep insights into consumer behavior.

4. GfK (Growth from Knowledge): A market research company offering detailed analysis of purchasing behavior and consumption trends across various sectors.

5. Dunnhumby: Specializing in customer data analysis for retail, Dunnhumby uses retail panels to help brands understand purchasing habits and optimize their marketing strategies.

6. Nielsen Brandbank: Focused on digital and e-commerce, Nielsen Brandbank provides solutions to optimize online product presence based on accurate data from retail panels.

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Retail panels vs. consumer panels

Retail panels and consumer panels serve complementary purposes in marketing research. While retail panels provide a macroscopic view of product performance and distribution, consumer panels offer a microscopic understanding of consumer behaviors and attitudes.

Unlike consumer data, retail panel data does not provide information about buyer profiles. This is why it is often necessary to use both to get a complete view of the market.

Together, they enable FMCG brands to make strategic decisions.

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What indicators are available in retail panels?

Retail panels offer a wide range of indicators to help understand product performance in stores and major consumer trends:

1. Market share: Percentage of sales of a product or brand compared to total category sales.

2. Sales in volume: Quantity of products sold over a given period, often expressed in units or physical volume.

3. Sales in value: Total sales value of a product or brand over a given period.

4. Numeric distribution: Percentage of retail outlets stocking a specific product compared to all retail outlets in the panel.

5. Weighted distribution: Percentage of total sales coming from stores stocking the product, taking into account store size or importance.

6. Average price: Average selling price of a product during a given period.

7. Price index: Comparison of the average price of a product or brand against a benchmark or the category average.

8. Penetration rate: Percentage of households or consumers who purchased the product or brand at least once during the observed period.

9. Purchase frequency: Average number of times a product or brand is purchased by consumers during a given period.

10. Average basket: Average value of the shopping basket when a specific product is purchased.

11. Value of purchases per visit: Average amount spent on a specific product per store visit.

12. Growth in volume and value sales: Evolution of a product or product category's sales in volume or value over a given period compared to a previous period.

13. Inventory turnover: Speed at which a product is sold and replenished in retail outlets.

14. Out-of-stock rate: Percentage of times a product was requested but not available in-store.

15. Promotional effectiveness: Impact of promotions on sales in volume and value compared to a non-promotional period.

16. Cannibalization: Impact of sales of a new product on the sales of other products of the same brand or category.

17. Marginal contribution: Impact of a product on the overall growth of the category in terms of volume and value.

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How is panel data collected?

To guarantee data reliability and ensure strong representativeness of results, panel providers use several data collection methods, which they then cross-reference and consolidate. This data is collected from a representative sample of the market, which can vary depending on the research institutes or the sectors analyzed.

For fast-moving consumer goods (FMCG):

• Nielsen collects data from 5,500 supermarkets and hypermarkets in France, covering 97% of FMCG revenue.

• IRI tracks all hypermarkets and supermarkets, as well as a representative panel of hard discount stores, totaling around 5,800 retail outlets in France.

• For durable goods, i.e., electronics, home appliances, etc., GfK operates on a panel of 6,000 retail outlets in France, covering 33 distribution channels and more than 300 product families.

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To better reflect the diversity and structural changes of the market, panel sizes have increased over the years, growing from 500 hypermarkets and supermarkets analyzed (for Nielsen and IRI) to over 6,000 today.

To select the retail outlets that will make up the panel, institutes follow several criteria:

• Store type: supermarket, hypermarket, convenience store...

• Retail chains: E.Leclerc, Carrefour, Intermarché...

• Geographic region, to ensure a balanced distribution across the territory

• Store size and revenue, to reflect the economic weight of the retail outlets.

Once collected, the data is of course anonymized. Panel providers commit to protecting distributors' information and treating it confidentially.

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What is the benefit for consumer goods brands in using panel data?

In mass retail, brands are constantly looking for reliable and accurate data to guide their strategic decisions. Retail panels emerge as indispensable tools, offering a plethora of information on in-store product performance and consumer buying behavior. Here is how brands can leverage this valuable data:‍

Understand the market and competition

Through market share analysis, retail panels allow brands to understand their position relative to the competition, offering a valuable overview of their relative performance across different product categories. This also helps identify consumer trends, allowing brands to adapt their offerings to better meet customer expectations.

Optimize distribution strategy

Determining in which stores and regions products are available helps brands identify opportunities to improve their visibility and accessibility.‍

Evaluate marketing effectiveness

Measuring the impact of promotional campaigns on sales allows for adjusting strategies to maximize return on investment. Furthermore, studies help tailor advertising messages and develop more targeted promotions.

Refine product assortment

By identifying growing categories, panels help recognize expanding market segments and adjust the product assortment to capitalize on these trends. Brands can also evaluate SKU performance to identify underperformers, allowing for a rationalization of the offering and assortment.

Strengthen business relationships

Objective data provided by panels serves as a basis for negotiating commercial terms and developing strategic partnerships. In our article on strata in mass retail, we explain how to use them to better negotiate your picking.

Improve forecasting and inventory management

Use historical and current trends for optimized inventory management and more accurate sales forecasting.

Focus on new innovations

Panel data allows for innovation and development of products that meet customer expectations. They can test interest in new concepts or product innovations before launching, evaluating their market potential, but also identify the optimal time to introduce innovations or withdraw declining products.

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Limitations of distributor panel data

Nobody is perfect, not even retail panels. As the name suggests, a panel remains a panel and therefore cannot cover all distribution channels. E-commerce, specialized channels, or convenience stores may be underrepresented, distorting analyses if these channels are your main sales avenues.

As mentioned at the beginning of the article, retail panels do not provide (or provide very little) data on consumer characteristics (age, gender, buying behavior...). If your product targets a niche buyer group based on socio-demographic or professional criteria, this may limit your analysis. You will know that your product is selling, but not necessarily to whom, and why. The lack of buyer data prevents understanding the motivations for purchase. However, other sources can help you on this specific point. Let's take an example. You sell a protein bar in supermarkets. You notice it sells better near gyms and stadiums. Here, you can get an idea of your typical buyer without resorting to consumer panels.

I'll spare you the suspense: consumer panels are not enough. First, because they provide no information on product availability in stores, their positioning on shelves, or their presence in various retail chains. Without this data, it is difficult to understand the reasons for a decline in sales or performance below expectations.

Also, they do not allow you to analyze and measure your key indicators such as numeric distribution, weighted distribution, or out-of-stock rate. You are navigating in the dark regarding your pricing strategy or the promotions you have implemented (aside from the feedback gathered by your sales reps).

Finally, one factor that counts: humans are biased. Surveys based solely on human responses inevitably will be. Because sometimes, we answer with what we think society will accept most, rather than the truth. Retail panels, on the other hand, rely solely on raw data, collected directly from retail outlets, on which humans have no bias, and therefore, offer increased reliability.

One of the limits most taken into account by manufacturers is price. Having access to panel data represents a cost, which can turn out to be too high for small businesses.‍

Finally, we have barely mentioned it in this article, but no data is delivered to you in real-time. There is a delay between data collection and availability. If you wish (or need) real-time data, relying on other sources like POS (point of sale) data or your sales reps' store audits is a better option.

That is what we will look at now.

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Panel data vs. in-store audits: what to choose?

Choosing between retrieving distributor data or using data from field audits conducted by your sales reps depends on the objectives of your sales management, the resources you have available, the level of detail you need, but above all, the software used by your sales reps.‍

What are the differences and benefits between panel data and visit audits?

What differentiates these two types of data the most is their source. Your field sales reps are the source of the data entered into supermarket visit audits and therefore must be trained and educated on its importance. Panel providers, on their side, are experienced at the task and therefore have a better data structure, which will facilitate your analysis. However, they will never be your eyes and ears on the ground like your sales team can be, and thus will never provide the granularity of analysis that your area managers can offer.‍

To ensure that data collection is efficient, you must optimize your audits and the way they are completed.

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Which ones to choose?

These two data sources are complementary. If you can, we advise you to use both.

Panels will provide you with a basis to define your global objectives and track your performance on a national scale, while field audits allow you to adjust your sales actions based on local specificities and opportunities unique to each of your retail outlets and sales reps. For example, an area manager can use panel data to identify performance gaps in a region, then conduct targeted visits to understand the causes and implement corrective actions.

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Panel data vs. POS sales: what to choose?

Choosing between retrieving your POS (point of sale) data and using data from specialized companies like IRI depends on a brand's specific goals, data needs, and analytical capabilities.

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What are the differences between panel data and datasharing?

IRI data gives average monthly and/or weekly sales in a sector, but not per store (unlike POS sales data). Panel data therefore offers additional demographic notions. Let's look at their differences in detail:

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Which data to choose?

Well, both, captain! Using both allows you to have a 360° view of your commercial strategy.

Panel data makes it possible to understand which stores (in France) are similar and therefore what similar strategies can be put in place.

Let's take an example: you set up a commercial operation in the Carrefour in Aix-en-Provence which worked very well: +50% sales volumes over the period. Thanks to IRI data, you know that the Carrefour stores in Vannes and Pibrac are similar (same type of customer base and buying behavior). You can therefore prospect them to offer the same operation, backed by figures.

As for POS sales, they will allow you to understand the evolution of your actual revenue thanks to this operation but also, its longer-term impact on customer loyalty towards your products.

And with Sidely, you can centralize everything in one place: your CRM.