On average, brands see a 20X ROI with MakerSights.
Brief, high level statement explaining why the ROI Calculator is important and why the user should input their information.
Brief, high level statement on what the methodology is behind the ROI calculator. Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
Our methodology quantifies the impact to 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. At a minimum, brands must provide the estimated sell-thru rates for top-, middle-, and bottom-performing SKUs. For greater accuracy, brands can also provide the estimated promotional and/or markdown rates through to final unit sold; however, we do have data-driven assumptions for promotional and markdown rates that we can leverage if needed.
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 budget to higher performing SKUs (by increasing buy depths) to improve sell-through rates. This increases the sell-through percentage overtime, and reduces the percentage of sales at markdown, thereby increasing the gross margin dollars and average unit retail captured.
This model offers a conservative estimate for expected return on investment with MakerSights. We leverage reasonable, data-driven assumptions 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 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.
15,000 Unit Investment
CRM and Social media increases value
60 Total tests annually, 3 Categories
20 tests per category = 2 milestones x 10 tests per year
ROI = GM$ increase / cost of M/S platform
Quantifies the impact of increased gross margin dollars compared to the cost of MakerSights, showing the overall return on investment on tested products.
Demonstrates the change in gross margin dollars per unit, illustrating how brands can improve profitability of buys that are informed by consumer data.
Conservatively estimates how MakerSights can improve the following KPIs:
Retail Sales
Average Unit Retail Growth
Gross Margin Percent
On average, brands experience a 20x return on investment with MakerSights.
Right-size buy depths by region and channel at investment review and see a 4 - 8% increase in gross margin.
Cut 25-50% of products from Concept to Line Adoption, creating greater line efficiency and:
25-50% financial savings on samples
10-20% savings on time
1.2 - 2.3% increase in profit margins (from sample savings done)
$5,616 - $11,232 in savings per product development employee per year
Reach out to schedule a free demo with our team. Fill out the form and we’ll be in touch within 24 hours.
Book a demoJoin our newsletter to stay up to date on features and releases