Above the Line – US Food Producers: Deep Dive into Key Numerator Trends for Food Manufacturers (July 2026)

Research evidence excerpt

J P M O R G A N

North America Equity Research

19 August 2026

Above the Line – US Food

Producers

Deep Dive into Key Numerator Trends for Food

Manufacturers (July 2026)

In this monthly note, we analyze important trends for US food producers via

Numerator, an alternative data provider that sources first-party consumer

information. We have found Numerator to be helpful in demonstrating the “why”

behind key trends (for example, it can break down projected sales growth into

household penetration, purchase frequency, etc.). Below, please find charts and tables

that illustrate many deep dive, Numerator-generated statistics.

Food Producers & Retailers

Highlights

Taya Lindner

In terms of projected units, all departments were down Y/Y this month,

but the relative outperformers were: Breakfast and Alcohol. The following

were the softest: Pasta & Noodles and Candy. See Figure 4.

(1-212) 622-9424

J.P. Morgan Securities LLC

SNAP exposure appears to be down Y-Y for most of the food producers

tracked in this publication (in the 13 weeks through the end of July 2026).

The producers most exposed to SNAP LTM were TSN, LW, and BYND. The

least exposed producers were FRPT, SMPL, and BRBR (Figures 54 and 55).

Buy rates decelerated for all income buckets in July (a continuation of

trends in May and June). Buy rates for middle income consumers slightly

outpaced low and high income (from late 2024 through early 2026, low income

was growing fastest). See Figure 6.

For the median producer we track, Numerator’s projected sales Y/Y were

2.9% lower than Circana’s $ takeaway Y/Y over a similar period

(essentially the 13 weeks through the end of July 2026). Numerator growth

rates were lower than Circana with the largest gaps for HAIN, OTLY, and

OFRM in the 13 weeks ending July 2026. Numerator was higher than Circana

for only BYND over the same period. Readers should interpret these gaps as

informational rather than precise given differing methodologies, etc., between

the two data providers and other factors (Figure 15).

In terms of household growth, OFRM leads the pack (by far), followed by

FRPT and BRBR. In contrast, HAIN, LW, and SMPL are shedding the most

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