Case Study
How OCM Used Charter data to Win Shelf Space in the Toy Category
A growing brand in Walmart's toy category was performing well but couldn't prove it deserved more distribution. OCM used Charter data to build the category case, and turned a productivity story into a placement conversation the buyer could act on.
Updated: September 2026
The Problem
The brand was newer to Walmart and carried in a fraction of the chain, a few thousand stores against a much larger toy footprint. Sales were healthy, but every conversation about expanding distribution ran into the same wall: from the buyer's side, the brand looked like a small share player in a category dominated by two legacy toy brands.
Three specific problems sat underneath that:
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The share number worked against them. Ranked by total dollars, the brand sat fifth in the category. That's the metric that gets looked at first, and it made the brand look like a marginal player rather than a growth engine.
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Seasonality raised doubts. Toy spikes hard at Christmas and collapses afterward. A brand that looks like a gift purchase is a hard argument for permanent modular space.
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A new placement has been launched badly. Hundreds of stores recorded no sales in the first weeks of a trend pod rollout, and nobody could tell whether that was a demand problem or an execution problem.
Without category-level data, the brand had no way to answer any of it. They could show their own sales and nothing else.
The Solution
OCM used Charter data to build a category review from Walmart's own data, the same data the merchant sees. Rather than leading with share, we built the argument around productivity, incrementality, and retention.
Reframing the competitive picture
Charter's competitive benchmarking showed that ranking by total dollars was the wrong lens. On dollars per customer, the brand ranked first in the toy category. On dollars per store, third. The brand wasn't small, it was under-distributed. Every store it wasn't in was leaving category dollars on the table.
Killing the seasonality objection
We pulled post-holiday decline for every major brand in the category. The brand fell less after Christmas than any competitor, by a wide margin. That reframed it from a seasonal gift item to a brand building a repeat-purchase base supported by a brand repeat rate roughly 5 points above the next-highest brand in the category, and a retailer loyalty index near the top of the category.
Proving it grew the category rather than shifting it
The most important question a buyer asks about expanding a brand is whether the sales are incremental or stolen from existing items. Charter answered it directly: the overwhelming majority of the brand's year-over-year dollar growth was incremental to the toy category, and cross-shop data showed its customers were almost never buying other items in the category. New shoppers, not traded-down ones.
Finding specific stores and specific items
Store-level reporting revealed a real distribution mismatch: hundreds of the category's top-performing stores didn't carry the brand at all, while a large block of its existing stores sat in the bottom half of the category. At the same time, roughly half the items from each of the two largest competitors were turning less than $5 per store per week, a concrete, defensible list of what the brand could replace.
Separating execution problems from demand problems
The trend pod launch turned out to be a setup issue, not a demand issue. No-sales stores fell from several hundred in week one to a couple dozen within a few weeks, with only a single store never recording a sale. That let the brand stop defending the launch and start using it.
The Result
The category review gave the brand a merchant-facing argument built entirely on Walmart's own numbers. On the follow-up review roughly five months later, the underlying metrics strengthened:
#1
in the category for dollars per customer
90%+
of year-over-year growth incremental to the category
+2.25pt
repeat rate gain over the prior 13-week period
Metrics drawn from Charter data reporting across two category reviews.
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Repeat rate reached roughly 11.5%, against 7.7% for the next-highest brand in the category.
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Retailer loyalty index climbed into the top two in the category, up substantially from the prior review.
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More than a quarter of shoppers were first-time buyers of the brand, and roughly a quarter of those returned to buy again.
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Online content issues surfaced in the review were corrected, lifting item-level content scores and discoverability.
The distribution conversation changed shape. Instead of asking for more stores on the strength of its own sales, the brand could name which stores, which competing items were underperforming in them, and what the category stood to gain. That's a conversation a merchant can act on.
Why This Took Charter
Almost none of this analysis is possible with syndicated data. Competitor dollars per store and per customer, incrementality against the category, switching and cross-shop, store-level distribution gaps, trial and repeat by cohort, these come from Walmart's first-party transaction record, not a projected panel. Charter made the data available. Building the argument from it is the work.