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Cloud Case Studies: When Customer Stories don’t tell the entire Story!

Recently I was doing an analysis of Customer Reference Stories across the various cloud vendors and found some very interesting insights!

Mainly that the number of Customer Reference-able stories are one number… and the actual number of users of the Cloud platforms is significantly a FAR different number. Allow me to elaborate…

While there isn’t any direct published data as to how many customers each of the major cloud providers have… At least anything updated “recently” there is some anecdotal points to reference.

Amazon’s AWS Is Now A $7.3B Business As It Passes 1M Active Enterprise Customers

This article is from 2015. Contrast that to 2019 where AWS did $35B in business. So assuming for a moment that $35B is a little larger than $7.3B, it’s reasonable to say that means that AWS has a few customers, especially if there was a record of over 1 Million enterprise customers 5 years ago. Things get murkier as we try to get similar data from Azure, GCP, Alibaba, Oracle and so forth, so I’ll mention them, but dig deeper into AWS for the purpose of this story!

How many Customer Stories do these Clouds have?

AWS : 1442 Customer Stories

Azure : 1585 Customer Stories (or 3819 when using this Customer Stories page)

GCP : 955 Customer Stories

See, now this is where it gets a little murkier as the search engine for GCP For example is severely lacking, which is surprising coming from effectively a “search engine” company. Making a breakdown of Customer Reference examples by product VERY difficult, to nearly impossible.

Azure has an interesting search function which does not always load more than 12 references on a page (I opened another browser and tried it in Edge and got it to work sometimes, but it was inconsistent) But I do admire the sheer number of references available in different languages! I’ll be sure to do a deeper dive on this in the future!

And AWS seemed to load fast enough, which was good, as Customer References are broken up by Location, Segment, Industry, Use Case, and the exciting piece I’ll be sharing here… By Services Used! (Product)

Aren’t the numbers above less than 0.01% of 1M Customers?!

Now you’re starting to get it. That’s exactly what I was thinking! I did find some other references to various products, or solutions and so forth where a product might have hundreds of thousands of customers, or in other cases, millions of customers. Why then, for example are there only 701 Customer References which reflect using Amazon Simple Storage Service (S3) and herein lies the crux of my question! 🙂

I’ve been in Vendor-land many times myself and I know the challenges faced with taking a use-case, coordinating with a team (Marketing, Customer Service, Customer Support, Sales, Engineering, and so forth) and then getting Legal involved and an executive and corporate sign-off to have a reference-able example that can be publicly shared on a vendors website, sometimes even including a video. So I totally understand that, en masse. But then again… We’re talking about hundreds of references in a sea of millions of customers. That just seems like an opportunity for everyone to get engaged and get involved and do great things!

Elastic Cloud Compute (EC2)84058%
Simple Storage Service (S3)70149%
RDS37326%
Lambda24917%
CloudFront19113%
CloudWatch17012%
Redshift16912%
DynamoDB15411%
Route 531329%
EMR1289%
Kinesis1148%
CloudFormation1108%
Elasticache1098%

At the time of creating this blog post, this is the breakdown of the top 13 Services used in AWS, the number of customer references tagged with that information and the % of those services used compared against the 1442 public references that exist today.

This is just a drop in the bucket of the 65 services that are immediately searchable within the Customer Stories page, and while it certainly does not reflect the number of users who use these services, it does provide at least a breakdown of some of the most ‘popular’ services within the platform, at least as far as a customer is willing to go on record to be using! And not to forget, Amazon aims to be the most customer centric and obsessed company on earth, so this is just one reason why these data points mean so much to me; either as a prospective customer, an advisor to an enterprise or startup, or just filling one of my analyst or reviewer roles.

—— 65 Services# of Cust Ref
Pinpoint1
IoT Analytics1
Snowball Edge1
RoboMaker2
Chime3
Sumerian3
CloudHSM3
Shield3
Device Farm4
CodeBuild5
X-Ray5
Snowball7
Quicksight8
Greengrass8
Step Functions8
Fargate9
CodeCommit10
Config10

So what my plan and intention in a series of future blogs and articles will be to find the least used, or at least the least referenced in Customer Story examples, and dive deep into these solutions, what they do, what value they provide, and so forth. I’ve found sometimes some of the best features, functionalities, this and that aren’t used because people don’t know about them, or how to leverage their value. Sometimes they don’t even think about it, or it doesn’t come up in a story, ala Snowball and Fargate. Regardless though, I’ll be going through and diving into these solutions so we can see just what is behind the curtain and whatever other fun excitement will come from that!

So I hope you join me in this journey as we dig into some of these solutions that you might be left wondering, “Wait, WHAT is that? I never even heard of that!” Because for as popular as Route 53 is, making it 9th on the list above of popularly used services… I still catch people running their workloads and business on AWS who had no idea what was… And that’s only a little disturbing to me. 🙂