See a 20X ROI with MakerSights
More than half of the world’s top brands leverage MakerSights to boost SKU productivity, improve sell-through rates, and maximize profitability across assortments. Inventory is often a brand’s biggest asset and liability. Curious how much you can increase your gross margin with MakerSights? All it takes is a few data points to discover how MakerSights can help you reduce risk, optimize your inventory, and deliver more of what your customers love — and less of what they don’t.
We built this calculator as a strategic resource for retail brands seeking ways to refine their assortment strategy. Whether you’re a hot new DTC brand with a small-but-loyal following or a tried-and-true multi-channel brand with global reach, MakerSights can partner with you across design, product, and merchandising to align your product strategy with core consumer preferences and new target audiences. Take a look at our methodology below to see how we calculate our contributions to your profitability.
This model offers a conservative estimate for the expected return on investment with MakerSights.
Our methodology quantifies the impact on gross margin dollars for each assortment that is tested through MakerSights, using a model that calculates the change in gross margin dollars that is driven by the redistribution of units within a brand’s performance buckets.
We assume SKUs fall into three performance buckets: top, middle, and bottom, which are classified by the average sell-through rate of a given SKU. Brands must provide the estimated sell-thru rates for top-, middle-, and bottom-performing SKUs.
When a brand uses MakerSights to test products, we assume the brand will reallocate inventory as a result of the consumer data and insights gleaned from testing. Brands can reallocate investment budget to higher performing SKUs (by increasing buy depths) to improve sell-through rates. This increases the sell-through percentage over time, and reduces the percentage of sales at a markdown, thereby increasing the gross margin dollars and average unit retail captured.
This model assumes a total unit investment of 15,000 and 60 total tests annually across 3 categories with 20 tests per category (2 milestones x 10 tests per year).
We leverage reasonable, data-driven assumptions for promotional and markdown rates within the model that are based on industry averages and aggregated data from our brand partners over several years.
The model does not include quantifying the impact of decreasing deadstock, which MakerSights also supports, nor does it include saved market costs (shipping, storage, marketing, etc.) or the incremental cost and time savings from SKUs dropped after testing with MakerSights in earlier stages of product development, which would result in a higher overall ROI.
Finally, this model does not take into account the MakerSights cost savings brands experience if tests are conducted using a CRM database or social media, which is free for brands using MakerSights, versus tapping into the MakerSights network of more than 45M consumers around the globe
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