09 Jul Realizing the Potential Business-Specific Analytics in Specialty Retail (2021)
Business Specific Analytics and AI for Specialty Retail
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, gift shops, 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.
- 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 specialty retail analytics software needs to be flexible and powerful enough to work with unique business cases and considerations.
But before we dive into the nuances of specialty retail analytics — let’s first agree on a definition of “specialty retail.”
Simply put, you’re a specialty retailer if you carry a deep assortment of non-commodity items. This includes everything from gift and book stores to sporting goods and furniture stores.
Without accounting for these business-specific considerations, none of your data, or analytics will yield intelligent and reliable insight. In specialty retail your analytics will need to accommodate:
- The importance of occasion shopping on the demand of all of your SKUs (mother’s day, valentine’s, etc.)
- Balancing vastly different demands for the same SKUs at different locations
- Managing incredibly fast assortment changes, bringing in new SKUs monthly while retiring old ones
- Predicting and planning for new products that have no sales history
- Accounting for unique vendor and manufacturer constraints on purchasing and shipping
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 SKU at your busiest locations, you won’t know the true demand of the products 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? Vendors changed their policies and minimums? Did you open new stores in areas with new geo-demographic diversity? Have you changed your fulfillment model to focus on online?
The one constant in specialty 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 specialty retailers have taken for decades.
It’s clear that a generic analytics solution won’t work for specialty retailers (at least without massive amounts of customizations). But what can specialty retailers do?
Aside from dealing with cumbersome, slow-loading, and incredibly complex Excel spreadsheets to plan and run their businesses — specialty retailers can look to implementing an analytics solution that is built specifically for organizations like them. One such solution is Retalon.
Let’s take a look at one example of a specialty retailer that implemented Retalon’s business-specific analytics.
The Paper Store is an American gift-shop retailer with more than 80 locations.
Like many brick and mortar specialty retailers, The Paper Store struggled with managing and optimizing a massive assortment ranging more than 13 categories (including hallmark reading cards, fashion, toys, sports items, outdoor lighting, etc.). Retalon’s business-specific AI has helped them optimize their product assortment while reducing total units.
The Paper Store now confidently forecasts all the peaks and valleys, and they know exactly what they need to bring in and when to maximize sales and minimize inventory.
Unsurprisingly, this is all thanks to a much more accurate and reliable forecast built for specialty retail.
But don’t just take our word for it. Here is a short interview with Bob Anderson, CEO of The Paper Store:
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.
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.