13 Minutes of eComm Wisdom

[00:04] thank you for for jumping on and sharing sharing some of your insights in the space um so you’ve been running Source medium for a while for those who aren’t as familiar as I am can you describe in a few words what you’re working on yeah thank you Tim for having me on and I really appreciate the opportunity

[00:23] excited to dive into all things e-commerce today and data yeah so Source media we provide fully managed data infrastructure solution that is specifically designed for Brands doing between eight to nine figures in annual sales and essentially what we do is we we abstract away the complexity of unifying your data into this metrics frame framework that can then ultimately

[00:47] lay the foundation for a decision making framework that the entire company can adopt that’s still a little bit too high up in the air so if we bring it down to the use cases specifically you can really look at it in two sides one is RBI solution which dramatically simplifies things like reporting and internal dashboard building and then our

[01:09] data warehousing solution allows for the direct access to our developer friendly data sets and schemas and then that kind of opens up almost an infinite number of use cases anything from statistical modeling to customizing metric definitions as well as training your AI agents so really really are you do you feel like you’re competing more today with a looker type of company as opposed

[01:35] to other like triple whales of the world yeah I we actually see ourselves as actually directly competing with the modern data stack and that is a concept that kind of goes across Industries right this is really around businesses that are essentially building their data management infrastructuring house right things adopting things like B TR to Big query to transforming the data with

[02:03] tools like DBT or data form and ultimately to a lot of the Hidden layers of data management right anything from data observability and quality control to governance and Metric definitions and schema definitions and then bi which is like where looker sits ultimately so I think the problem that we uncovered is a lot of Brands adopted these Solutions not

[02:28] knowing really how complex and expensive it was going to be to build and to ultimately maintain so that’s where we come in we essentially focus on what is the output of a modern data stack and that is similar across many businesses that have Omni Channel sales but with a heavy e-commerce Focus so that’s where we can come in and just get you from

[02:55] zero to 100 super super quickly but you also know that this infrastructure is Battle tested across over $2 billion doar of of annual gmv that we process maybe to put it is there like a cool case study that you can highlight from a recent client where the impact that you guys delivered is so clear and obvious yeah so my favorite example is

[03:18] we’ve been working for a few months now with cpap.com so they are a direct consumer they sell CPAP machines and related accessories products right so they were on Magento with a lot of internally built technology then that includes the data management infrastructural stuff and so I think they had a lot of pain points around just the cost of maintaining that

[03:45] infrastructure and the ultimate Roi that was hard to see I think there was just still a lot of friction in terms of like individual leadership as well as operators being able to access the data that they need and can trust to make decisions so since they were already migrating e-commerce platforms we had an opportunity to also have them

[04:08] dramatically simplify the data management side of it into Source medium so then what their Tech team is able to do now is they can just like specifically focus on investing into things that that are specific to their business right we also have done a lot of great work with them in terms of getting the number to to be boardroom

[04:30] ready to be numbers that fpna can accept right the CFO would be happy about so they’re able to swap out some of our cost components but take our Revenue figures and other components that combines ultimately into the the kpis that the the entire company should care about so I think what’s really powerful there is think about when the CEO the

[04:55] CFO the CMO all the way down to the email marketing manager and the CX manager using one set of metrics and one set of definitions to make decisions so I’m really excited about where that’s headed the other example that’s been really cool is with our agency offering so one of our earliest adopters is the snow agency which is now part of Avenue

[05:20] Z so they’ve actually been able to build an entirely wh labeled dashboard business on top of our infrastructure right so that’s provided them with a lot of differentiation and helped them significantly increase close rate and just increase the amount of insights and value that they can offer to your to their customers besides like managing media so that is like a core part of

[05:46] their offering now where they can essentially create these Dash very intricate dashboards that’s that they know are going to perform and then they know they can trust the numbers on to to further help their customers and increase the value that they provide I want to know like how when you’re competing against the modern tech stack as or modern data stack as you’ve

[06:06] described that’s a lot of companies that are billion dollar companies that are going to be replaced by Source medium uh how what have you done on your from a team standpoint and from like a tech build standpoint or product build standpoint to enable you to get all these efficiencies that you can actually strip out a lot of these expensive techn

[06:29] techologies and just go with Source medium instead yeah I think the two core competencies that allows us to together one is we try to spend 80% of our week working with customers my goal is that everyone in the company works with customers directly or indirectly but everyone should have an opportunity to solve problems with the customers to get

[06:53] uh directly and then that allows us to really understand the business specific domain and the problems that businesses want to solve and then ultimately that allows us to create and recognize the patterns right and that’s what gets absorbed into the product so once bug fixes happen or improvements in our definitions where new metrics are shipped or created right all of our

[07:23] customers can benefit from that and whether or not they want to adopt that particular metric or that particular ular data source is up to them but what they know for a fact is there is going to be broad acceptance otherwise we wouldn’t ship it to to everyone at scale and then the other thing is that we copy

[07:45] other kind of early other infrastructure companies that have gone IPO right so if you look at a company like paler which is what we model our company after or a company like Hashi Corp right those companies were entirely made of technical staff right in the early days including sales so our entire company is technical except for one but even that

[08:10] person is Savvy right technically savvy so everyone can write code everyone can contribute to the product in a technical sense and then that allows our R&D to just be basically the entire company all the time by focusing on providing value over whelming our customers with value on a daily basis I want to know like when you went

[08:36] into Source medium you had a vision and now you’re four years later working with some nine figure Brands you got a strong team behind you and a really cool product did you are you like on the path that you had envisioned four years ago or is Source medium today actually quite different than what you had uh set out

[08:56] to build four years ago yeah that’s actually such a funny question because when I started the what I wanted was a slack bot the company was incorporated in May 2020 uh so what I wanted was a slack bot that’s sit in your slack that has access to all your data that can you can talk to and give you

[09:19] insights I didn’t know that was uh called lln right so I had no idea how to build that to be honest and end up becoming like a daily slack reporting bot which became actually semi poopular where it had to be taken down but it’s coming back because of the API versions but I think then that led us to this

[09:43] winding journey to become a dashboard company right but really just like ultimately now where we’re going is that route right because the number one obstacle to adopting AI for an organization is UN Ying all your data right so that is like the most expensive time consuming and boring part of it so now that we’ve been doing that for four

[10:08] years I think what that sets us up for is to start really like extracting the value out of that data set in a dramatic way and that is going to be with a combination of enabling really use case driven statistical and machine learning modeling that brings open source options into the pray as well as internal Ai co-pilots and agents and we have some

[10:35] pretty exciting plans uh behind that so it’s somehow the we came full circle thanks to chat GPT and then the rest was history that makes perfect sense that you’re going to go back to that route uh and and apply some AI technology on top of it especially because you understand data sets of multi- Channel Ecom players pretty much better than anyone that’s

[10:59] super exciting do you like can you are you guys profitable can you just allocate resources that you already have on the team to work on that or would that potentially suggest another fund raise or or something like that yeah I think we have gotten to a place we weren’t always there I made a lot of mistakes but we’ve gotten to a

[11:21] place where we’re pretty close to being profitable the a metric that I track closely is a annual recurring Revenue per full-time employee we want to make sure that we learn from our lessons in the past and not just throw people at the problem but really think about Automation and really think about using technology to create productivity gains

[11:45] but I think what’s cool right now is we have our entire business built on top of gcp I’m a ex googler as well so I have some allegiances there but I also do believe they’re best positioned in the AI era as a cloud service provider so we’ve been getting a lot of businesses onto gcp we’ve we’ve gotten a lot of

[12:07] businesses to switch from other clouds like AWS and Azure onto gcp and our solution is flexible as well you know we can enable other clouds using gcp as the foundation so so Google is slowly recognizing that and we’re actually working with Google directly on like doing some proof of concepts by enabling like uh both Gemini Pro 1.5 right on top

[12:32] of your data as well as open source Alternatives like llama right so we’ll have pretty hopefully we’ll have some proof of concept to show the world soon the other thing I’m excited about is really to get some of the machine learning models enabled for Brands there’s a lot of things around Predictive Analytics that people need like time series forecasting lead

[12:55] scoring probability to churn so we will probably have those capabilities opened up sooner uh rather than later so very excited about that cool well Fay thank you so much for for the wisdom thanks for the time and uh great to catch up as always speak to you soon Al righty talk to you sir