Introducing The Bellwether

I see online that many professionals share artwork, animation samples, video edits, TED talk speeches, seminar sound bite platitudes, and incredibly well thought out articles on everything from how to score big on an interview to the top ten newest pronouns to hit the workforce this week.

These are things I wish I could add to my portfolio, but alas, my real calling is none of these.  What I do is harness the powers of everything that I’ve been and fold them into an ever evolving blob of processing code that I feel has finally started to come to fruition. 

This I am calling ‘The Bellwether,’ a system built that reaches across the web to aggregate data to track and rate hobby collectible products.  Of course, the details are so much more than my single line introduction… I’m still working on that…. but while I do, let me give you a little tour of the elements used to create this data churning entity.

Mission: to collect sales data across a number of sales channels on hobby collectible figures so as to be able to have a growing history of the viability of various hobby collectible product types from a variety of manufacturers working with various licenses down to the actual character selection. 

I’m putting all these elements on point.  Having worked in the marketing field and interacted with some of the brightest veteran toy marketing managers transitioning to hobby collectibles, I found the toughest questions to answer were ‘Will this toy type sell?’ ‘Who’s the number one in this segment?’ ‘What brands are hot for this demographic?’  I knew quite a bit since I had some pretty deep empirical data, but there weren’t numbers to show for it.  It was viewed as simply my ‘gut feeling,’ which is was, and it normally lean in reasonable direction, but numbers are what moved the businesses. NPD reporting was the bible by which decisions were derived, and even they were still trying to figure out how to report on the niche hobby collectibles genre.  Very much in the same way Amazon grouped hobby collectibles in the ‘toy’ category, NPD had no way of differentiating either.  For the two years we had them over for reporting, I asked the reps if there was a timeline for this info and they were ‘working on it.’ To be fair, traditionally, growth in hobby collectibles would be insignificant in the toy business, but a player like Funko broke the mold.  Every toy manager was scrambling to replicate the same idea in the mass retail segments not understanding that the strategy Funko used was carefully grown over time from collectors to mass.  Most toy producers wanted to instantly leverage their buyer connections and tried going from mass to collectors, which resulted in complete and utter failures across the board from large chain retailers to top brand toy manufacturers.  Inventory saturation due to over production was one of the very first problems presented to me that was plaguing my new corporate employer as it had become a massive stain that took years to wipe clean.

With this in mind, I wanted a tool that could gather information on products selling out in the wild and get a read on its popularity through site rankings and sell thru. In addition, apply my dormant brain trust of hobby figure knowledge to the definition of what demographics brands really cater to, and what related brands might go well with riding on the success of others.  I see this missing in even Amazon’s site where its common to see figures from a mature rated anime title being advertised as a pre-school toy for toddlers (Magica Madoka is cute and all, but definitely not for kids). Appreciation for niche category insight of this type is difficult to earn in the mass market crowd as it takes a fan to know what a fan wants, and to know why fans want it.  Apply this know how to a computer learning system, and you’ve got a kick started analytics system that can drill down to the selling success and failure of any collectibles of any character from any series by any manufacturer.  I do believe in time, systems will begin to learn more about the license associations, but over 20 years of having been a part of every angle of niche genre categories from being a fan to owning my own store, to working in a lead managerial role in a corporate office, I feel I have a unique head start.  In short, when the data comes in, you’ll still need someone who can speak geek.

I do see other sites trying to do something similar like hobbydb which feels too broad and poppriceguide which seems way more niche than I want.  Part of my angle is to roll up products to see who the most effective manufacturers are in a particular sector.  I don’t feel that from these other guys even though I really like what they’re bringing to the table. 

For the one person that got through all the dribble above, thanks for reading. Let me know your thoughts on the system as I’m always looking to improve its features.

I pulled out all the stops on this one by smashing together every platform and coding language I’ve ever practically used in the last 10 years.  And, yes, I and I alone designed, programmed, and currently manage the entire system from back-end database grooming to Google Chrome Extension development to applying a weight to the likelihood someone will like Lobo if they’re into Wolverine.

– wooCommerce
MS-SQL Server

Coding Languages:
– Dynamic Image Generation

– DataMining – (Node.js in the future)

MS-SQL Server
– Views
-Stored Procedures

API Connections:
WooCommerce – Python
Amazon – Python/ColdFusion
Google Chrome Extension API
eBay – TBD



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