Get Ahead of Markdowns With These Three Steps

Press enter to search
Close search
Open Menu

Get Ahead of Markdowns With These Three Steps

By Justin Peimani, Head of Business Development, Askuity - 01/16/2017
It is no secret that the American shopper loves a good deal. Unfortunately, this season that good deal will place increased strain on the relationship between apparel brands and their department store partners.

Several of the largest department stores, including Macy's, Nordstrom and Kohl’s, have deliberately reduced order volume in an attempt to avoid the same inventory glut that led to deep markdowns during the 2015 holiday season. In a defensive maneuver, several prominent fashion brands, such as Michael Kors and Coach, have excluded themselves from store-wide promotions. Others, such as Diane Von Furstenberg, have chosen to pull out of certain department stores altogether, as was the case with Bloomingdale’s.

However, this cannot — and should not — be the way of the future. Brands and their retailers are engaged in a symbiotic relationship. It is in their mutual interest to work together. But how can apparel brands do this, given the threat of deep price discounts tarnishing the retailer-brand relationship?

The answer lies in the following three-step plan.

Step 1: Plan assortments by region for brick-and-mortar customers
This first step is not news to any apparel brand. Shoppers in Miami wear different fabrics and colors in comparison to their counterparts in Seattle. However, in an era of lower purchase volume, it stands to reason that unsold inventory will cost the retailer a premium and, in turn, will hamper the brand’s next planning cycle.

To avoid this, brands must clearly segment their SKU and store-level performance. One way to achieve this is to perform a quadrant analysis. This practice was first developed by Wal-mart but has been adopted across a number of retail verticals since. It involves segmenting SKUs and stores into A, B and C categories. These data points are then placed into a matrix to identify which combinations of SKUs and stores leads to the highest sales per square foot.

From here, brands can best advise their buyers on which inventory to send where and thus reduce the chances of aggressive price promotions to offset unsold pieces.

Step 2: Use brick-and-mortar performance to inform e-commerce assortments, and vice versa
The second step is a practice that is not yet widely adopted across all apparel brands but has been a staple for several leading consumer goods brands for a number of years. This practice will be particularly important going forward, given that 67 percent of orders placed online (across all retail verticals) in November were discounted, up from 38 percent in 2015. In other words, aggressive price promotions will become a concern for brands both online and in-store.

To avoid this issue, brands must develop a holistic view of their online and in-store presence. Millennial shoppers, in particular, will use brick-and-mortar locations to identify their desired style and size before placing their orders online. These new-age buying habits have contributed to the rise of e-commerce for fashion and apparel brands, with e-commerce accounting for 20 percent of all apparel purchases globally.

More concretely, once brands have conducted their first step analysis, they can double down their e-commerce advertising efforts on their strongest regions to maximize both their brick-and-mortar and their e-commerce sales. 

This logic is also conversely applicable as brands may apply the same regional assortment analysis to their e-commerce sales. By identifying their strongest SKUs by region, brands can use this information to support an argument for larger purchase orders to supply certain regions within a brick-and-mortar chain. It is important to note, however, that this analysis is not applicable to every e-commerce retailer. Certain retailers, such as Amazon, make this analysis possible by providing their vendors with ship-to information by zip code within their ARA (Amazon Retail Analytics) Premium offering.

Step 3: Extend the logic to independent retailers
This third step is perhaps the least common practice among apparel brands. This is because account executives and national account managers for independent retailers are often, but not always, separated from their colleagues who manage the larger department stores.

Nevertheless, this final best practice is critical to maximizing sales among the coveted Millennial shopper segment. These younger shoppers increasingly value the tailored and personal relationship that is built with the smaller, boutique retailers.

The largest challenge to this final arrow, however, is that independent retailers do not often provide their partners with sell-through information. And when they do, it is often inconsistent in either format or frequency, or both.

There is, however, a workaround. Once the second step analysis is complete, brands can overlay the regional assortment trends noticed in their larger customers and e-commerce channels to their independent customers. Nonetheless, brands must be careful to only cross-compare retailers that share similar customer demographics. From there, brands can recommend assortments to their independent customers based on the preference of similar shoppers in their geographic vicinity.

Times change, and we change with them
There are never any guarantees in retail. Changes in the weather and seasonal shopper preferences, for example, can throw a wrench into even the most meticulous plan.

When brick-and-mortar retailers are feeling the pressures of competition from their e-commerce counterparts, the burden shifts to brands to provide increased support and informed recommendations to their retail partners. Effective planning, powered by data, empowers apparel brands when faced with this daunting challenge. And the right tools afford brands the opportunity to assess their performance, both online and offline, and provide recommendations that deliver real value to the retailer.


Justin Peimani is head of business development for Askuity, which provides a retail sales enablement platform that drives profitable insights.