Realizing the Potential Business-Specific Analytics in Jewelry (2021)

Realizing the Potential Business-Specific Analytics in Jewelry (2021)

Jewelry Specific Analytics and AI

The word “retail” gets used interchangeably as if all retailers are all the same.

But let’s be honest, what do fast food restaurants, automotive shops, jewelry stores, and online supplement stores have in common?

Not that much.

Sure, on the surface it may all seem like retail to the uninitiated, however, anyone who’s actually worked in medium to large-sized retail organizations will tell you they are each a world of their own.

Once you start “peeling the onion”, you quickly discover that each retailer has business-specific considerations that are critical for their business.

For instance,

  • Destination resorts that run gift shops must account for occupation rates in their hotels as well as weather.
  • Liquor stores have legal restrictions such as wet/dry zones, state lines, and deal with inventory in pallets, cases, and individual bottles.
  • Electronics and games retailers have presales and major demand spikes on game release days. They also offer trade-ins of used goods.
  • Fashion retailers need to account for size curves for every SKU

That’s why jewelry analytics software needs to be configured to work with the unique considerations of jewelry retailers.

Without accounting for these business-specific considerations, none of your data, or analytics will yield intelligent and reliable insight. In jewelry, your analytics will need to accommodate:

  • The differences in planning, allocating, and replenishing between fashion, softgoods, and hardgoods SKUs (e.g. loose diamonds and classic engagement ring designs, vs. seasonal necklaces and bracelets)
  • Balancing vastly different demands for the same SKUs at different locations
  • Ensuring assortment is effectively planned (and inventory is promptly replenished) to keep fixtures across all stores adequately filled
  • Rolling assortment strategies on inventory that never goes obsolete (e.g. precious metals, gems)

Last Year’s Data is Unreliable

The expression “garbage-in, garbage-out” strongly applies here. It doesn’t matter how sophisticated your analytics tools are, if you’re simply feeding it last year’s sales data, you’re in for a major disappointment.

If you run out of stock on a popular engagement ring design at your busy locations, you won’t know the true demand of the rings at each location, and you will repeat the same mistake in your forecast for next year.

Rolling assortment? New designs? Ran a promotion last year that you don’t plan for this year? Has Easter moved to a different day this year? Precious metal prices rose (or fell) sharply? Did you open new stores in areas with new geo-demographic diversity? Are people putting off weddings and engagements due to a pandemic?

The one constant in jewelry retailing is that there are no constants.

Simply relying on last year’s data is a big mistake, and you are not alone. This has been the typical, ineffective approach jewelry retailers have taken for decades.

Business-specific analytics will help fashion companies realize the potential of retail analytics.

Jewelry-Specific Analytics

It’s clear that a generic analytics solution won’t work for jewelry retailers (at least without massive amounts of customizations). But what can jewelry retailers do?

Aside from dealing with cumbersome, slow-loading, and incredibly complex Excel spreadsheets to run their entire business — jewelry retailers can look to implementing an analytics solution that is built specifically for jewelry. One such solution is Retalon.

Let’s take a look at one example of a jewelry retailer that implemented Retalon’s business-specific analytics.

Shane Co. is the largest privately owned jewelry retailer in North America.

Like many brick and mortar jewelry retailers, Shane Co. has thousands of truly unique loose gems — and Retalon’s software makes managing and allocating them a cinch.

Prior to Retalon, Shane Co. used a month-long rebalancing cycle to rebalance their stores. The process took an entire month because all of the data-analysis was being done manually. Now, Shane Co. optimally rebalances the stock across their entire company in just 15 minutes.

Better yet, Retalon’s jewelry analytics software helped Shane Co. reduce one of their main product lines by 40% while increasing sales at the same time by 20%.

But don’t just take our word for it. Here is a short interview with Tom Shane, CEO of Shane Co.:

How you can get started with business-specific analytics

First of all, you will need to determine what makes your business unique. It will often be a unique combination of art and science that you’ve built into your business process. You should start by considering the following:

  • What makes your business unique? (For example your assortment, operations, marketing, etc.)
  • What analytics and decision-making are you doing today that is working? What works but needs to be scaled? and what is not working?
  • What constraints does your business have? (legal, macro-environmental, competitive, internal, etc.)
  • What unique features, processes, or variables you’d like to include as a business rule or want to be accounted for.

Avoid analysis paralysis! Introducing new technology and processes to your business requires a lot of thought and planning, however, overthinking is a common mistake in retail. While you schedule additional meetings to discuss your competition is picking up market share.

Crawl-Walk-Run

There are some easy and low risk ways to dip your toes:

  • Get a personalized demo on a sample of your data so that you can see the system with your own stores and products and uncover hidden opportunities specific to your business.
  • Run proof of concept on a small department or category in your business.
  • Finally, when you are ready, work with Retalon experts to make the system your own. We offer best practices and assistance to configure the system for your business so you can get the most out of it.

The digital transformation is here, and analytics-driven retailers are going to take over. But having the most advanced analytics isn’t enough. It must also reflect your vision, your unique business process, and the reality on the ground.