Struggling to flush out excess inventory? You aren’t alone.
According to Marketwatch, the Inventory-sales ratio for general merchandise stores spiked to a 15-year high. The mangling of the supply chain has created havoc on the inventory side. Retailers tried to keep up with demand when we were all huddled in our homes, then containers became moored in ports, and by the time inventory hit the shelves — well, then we no longer had a penchant for those items.
So aside from calling a liquidator, what can you do? Your AI-powered recommendation system might be able to help you move that excess stock — in a way that actually dovetails with business needs — and builds customer loyalty.
First, let’s step back.
What Is an Inventory Management System?
Inventory Management Systems (IMS) or even some all-in-one Enterprise Resource Planning (ERP) Software are terrific for letting you know about stock overage.
An IMS helps manage all the processes that go into ordering, storing, and profiting from the purchase order phase all the way to getting into the customer’s house. It’s a lot of data, and you can forgive your merchandisers for not being able to keep up with it.
When your IMS was set up to re-order goods automatically — and then the shipping nightmare started — you had the perfect storm. Now the key is to move that inventory to reduce storage costs.
A good recommendation system can help — if it allows business-based recommendations.
What Are Business-Based Recommendations?
This recommendation category’s aim is to suggest products based on business priorities. This means ensuring that suggestions are geared toward generating profit, clearing expiring inventory, and satisfying supplier relationships — while aligning with the brand.
Business-based recommendations tap into the following types of data:
Let’s dig into some of the most-used business-based recommendations.
Not surprisingly, this (popular) type of product recommendation focuses on price and inventory. Whether you need to move excess inventory or as part of a special promotion, price is a popular tactic. Shoppers who are price sensitive certainly will find sales items attractive.
But here’s a twist. Even your most loyal active shoppers will be happy to fill their cart with sale items — in addition to whatever full-priced items they’ve already selected.
Think of putting these types of recommendations on homepages and category pages – but don’t forget your Check-out page! Impulse buys during checkout are a wonderful point of sale tactic.
Amazon and other retailers like Home Depot have been looking to offset earnings with incremental revenue using advertising.
In fact, over the past few years, “sponsored products” recommendations have partly replaced organic suggestions. To inspire shoppers, these product recommendations are ideally placed in a retailer’s ecommerce homepage.
See if you can’t negotiate manufacturer credit by pushing their product front and center.
To better compete with the Amazons of the retail world, brands and retailers need to create strong emotional connections with their customers. Curated ecommerce emerged as a trend to
help develop a more distinctive brand voice as a tastemaker while cultivating brand loyalty and
increasing average order values and sales.
Curated product recommendations can tap into a merchant’s unique understanding of its customers’ lifestyles and product preferences to deliver a boutique-like shopping experience.
Merchandisers can take a more active role in guiding customers to results that help the business achieve goals. These product recommendations are ideally placed in an ecommerce homepage, to inspire shoppers.
And these recommendations are just a start – what if you combined them with other types, to craft even more powerful shopping experiences?
Personalize … On Sale
Serving and recommending items that are on sale can be a powerful tactic. But this can be even more powerful when recommendations for discounted products and great deals are also personalized based on the shopper’s profile, preferences, and needs — sometimes also known as behavioral data, which comes in many flavors:
This kind of data can create what we call affinity-based recommendations. And when combined with other recommendations like on sale, you can create a personalized, curated list for a wide number of shoppers.
Consider using them throughout the shopper journey, most notably on homepages, no results pages, and, even at checkout.
Remember this personalization works for cold-start (guest) shoppers too.
AI-Powered Recommendation & Personalization
Machine learning continues to play an important role with recommender and personalization systems. Having more varied and high-quality data tends to result in better models.
When you can index all of this data, with purpose-built models, and the ability to capture every customer action — real time — you create a very powerful merchandising tool.
So while having a surplus of items can wreak havoc on your bottom line, the different types of recommendation elements mentioned above can help increase revenue. Use them strategically to make the best of an excess situation.
Learn more about the various elements your recommendation system should have with the ebook, Introducing Ecommerce Alchemy.