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The Birth of a Unicorn - Story 6

March 10, 2022

"The Birth of a Unicorn"

This is the sixth story out of a collection of bi-weekly fireside chats, which have evolved as our business does. The theme is about the Trials, Tribulations, and Triumphs of bringing a multi-faceted startup entering the "FINTech" space while at the same time building a runway for RAYL to become a Global "Challenger Financial Institution." And how to avoid the bear traps.
I hope you enjoyed the first Five chats from "The Birth of a Unicorn" series, where we have explored building a brand, vision, team, management tools, we have discussed raising capital, and in our last issue, we discussed technology.

This chat is all about big data…

In 2017, The Economist magazine coined the phrase in a cover headline, "Data is the new Oil," which is now immortalized in social media parlance.  

Everyone from SaaS providers to data centers owners in the data industry could be seen jumping up and down and waving their arms around in glee. The feeling was that at last, we had been recognized as a master cog in the Industrial revolution 4.0. Phrases like "Big Data and AI" started popping up, and dollars started to be spent. But this initial phase appeared to be about collecting it, wrapping a safety net around it, sticking it in a corner, and then forgetting about it.

That was all ok, but it was now starting to cost enterprises money, to archive and secure the data, which internally then the raised question of what we should keep and for how long? 

Some industry verticals such as banking, healthcare, and automotive took the lead, but this was driven mainly by in-country legislation, and unless there was a "Black Swan event," the data still sat there as dumb data.

Then three things happened:

1. Enterprise started to split out archive data away from primary data, mostly as a cost-saving exercise.

2. Data decisions forso-called Active / Active commands got moved closer to the Internet of Things devices for such activities as media streaming and financial transactions, and then the edge was coined, so we now had the core / fog and edge … are you still following me?

3. Enterprise started to believe that it could use Artificial Intelligence to interrogate the 10101s to accelerate decisions and gain better outcomes, so AI was placed at the edge. 

So with this spaghettified data inflows / outflows and demands of billions of end point end devices, how does RAYL intend to use data to create a competitive advantage for our customers?

The central plank of RAYL Innovation's data inclusion strategy is…what is stopping our customers from using all that data; after all, it is theirs – and constantly asking ourselves - is it just too expensive and cumbersome for the SME / micro merchant to use or can RAYL make it almost free to use? 

So, as a business we created RAYL.Apptive, the development was funded out of our early-stage crowdfunding which demonstrates the art of the possible. The vision was simple, could we collect all the commercial / productivity / sales & marketing applications that most of our customers use and put them in one place, under one inexpensive subscription.

Then let's compare the cost of all the free / subscription-based competitive applications and make RAYL significantly less expensive to work with – let's bill it per company, not per person basis.

Then the critical part – make it interoperable, so an data entry in to say a contact management database would automatically (on your command) flow through seamlessly into a CRM data base, which could be pulled up to populate a mailing campaign database and ultimately to an invoice database. SMART.

This is not a plug for RAYL, it's a narrative about the power of interoperability and data analytics for the Small Medium-sized Enterprise, and it's a proposition that is coming to life as you read this story.


Now from a merchant's perspective… 

From a merchant's perspective. There are effectively two database silos, the first associated with the credit or debit card, which the Merchant has little or no access to, and the second a database of anything associated with the point-of-saleInventory. Until now, never the two shall meet. 

With RAYL, a merchant can see (for example) exactly what wine Nicholas Jeffery bought today at his BC Liquor Store, what varieties, regions, and what was the average price per bottle was. Now RAYL can link all this data from purchases to the merchants' own RAYL contact/marketing database to make sure messages to Nicholas are salient to his last month's shop and then through the RAYL.Market place, find more Nicholas Jefferys - think of the power in the hands of the Merchant.   


Now from the Financial services perspective …

The first thing associated to the transaction above is the POS sales list subtracts the wines purchased off the inventory of the wine in the store and at the pre-set trigger buys more from the wholesaler.

With the Merchant's permission, RAYL can share commercial information with the Foundation Bank to explore the need to secure products and services. Data has massive weight here, as that trading data fulfills the Know Your Customer / KY Business and Anti Money Laundering. More important from the customer perspective, RAYL will know more about their trading profile than the Bank, so RAYL will be able to pitch on the Merchant's behalf for better terms, rates, and products. This data sharing will open up the environment for new FinTech products in Canada.

If you have any questions specifically about RAYL or being a CEO of a Unicorn in the making, feel free to drop me a line. If you have any other topics you would like us to explore, do shout out to me at njeffery@rayl.com.


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