13 Minutes of eComm Wisdom

Had a blast chatting with an old friend Tim Masek of @Storetasker. We got to chat a bit about: 1. What does SourceMedium do and who we do it for.

Overview

In this rapid-fire 13-minute session, Feifan Wang chats with Tim Masek of Storetasker about the core value proposition of SourceMedium and how it challenges the traditional “Modern Data Stack.” Feifan explains how SourceMedium abstracts away the complexity of unifying data for 8-9 figure brands, providing a fully managed infrastructure that delivers the power of enterprise tools like Looker without the six-month setup time or the need for a massive internal data team.

The conversation highlights key client wins, including a transformation story with CPAP.com where migrating to SourceMedium allowed the brand to simplify their tech stack while gaining “boardroom ready” numbers that aligned the CEO, CFO, and CMO. Feifan also touches on the future of data, revealing how SourceMedium is leveraging its massive dataset to train AI agents and co-pilots, moving beyond dashboards to predictive analytics and automated insights.

Key Takeaways

  • The Modern Data Stack Problem: Brands often adopt complex stacks (Fivetran + BigQuery + dbt + Looker) without realizing the immense cost and maintenance burden. SourceMedium solves this by delivering the output of that stack as a managed service.
  • Unified Decision Making: By providing a single source of truth, teams from the C-suite to email managers can operate off the same definitions and metrics, eliminating “data brawls.”
  • Agency Empowerment: How Avenue Z (formerly Snow Agency) built a white-labeled dashboard business on top of SourceMedium’s infrastructure to increase close rates and client retention.
  • Customer-Obsessed R&D: SourceMedium’s product roadmap is driven by solving real problems for customers directly, ensuring new features have broad market utility before shipping.
  • The AI Future: Unifying data is the #1 obstacle to AI adoption. With that solved, SourceMedium is now building internal AI co-pilots and open-source models (Llama, Gemini) for predictive analytics like churn scoring and forecasting.
  • GCP Alignment: Betting on Google Cloud Platform (GCP) as the best infrastructure for the AI era, helping brands migrate from AWS/Azure to leverage Google’s superior AI capabilities.

Transcript

[00:04] thank you for jumping on and sharing some of your insights in the sharing some of your insights in the space so you’ve been running SourceMedium so you’ve been running SourceMedium for a while for those who aren’t medium for a while for those who aren’t as familiar as I am can you describe in

[00:16] as familiar as I am can you describe in a few words what you’re working a few words what you’re working on yeah thank you Tim for having me on yeah thank you Tim for having me on and I really appreciate the opportunity and I really appreciate the opportunity excited to dive into all things excited to dive into all things e-commerce today and data yeah so Source

[00:28] e-commerce today and data yeah so SourceMedium we provide fully managed data media we provide fully managed data infrastructure solution that is infrastructure solution that is specifically designed for Brands doing specifically designed for Brands doing between eight to nine figures in annual between eight to nine figures in annual sales and essentially what we do is we sales and essentially what we do is we abstract away the complexity of

[00:42] we abstract away the complexity of unifying your data into this metrics unifying your data into this metrics frame framework that can then ultimately frame framework that can then ultimately lay the foundation for a decision making lay the foundation for a decision making framework that the entire company can framework that the entire company can adopt that’s still a little bit too high

[00:55] adopt that’s still a little bit too high up in the air so if we bring it down to up in the air so if we bring it down to the use cases specifically you can the use cases specifically you can really look at it in two sides one is really look at it in two sides one is RBI solution which dramatically

[01:04] RBI solution which dramatically simplifies things like reporting and simplifies things like reporting and internal dashboard building and then our internal dashboard building and then our data warehousing solution allows for the data warehousing solution allows for the direct access to our developer friendly direct access to our developer friendly data sets and schemas and then that kind data sets and schemas and then that kind of opens up almost an infinite number of

[01:19] of opens up almost an infinite number of use cases anything from statistical use cases anything from statistical modeling to customizing metric modeling to customizing metric definitions as well as training your AI definitions as well as training your AI agents so really are you do you agents so really are you do you feel like you’re competing more today

[01:32] feel like you’re competing more today with a looker type of company as opposed with a looker type of company as opposed to other like triple whales of the to other like triple whales of the world yeah I we actually see ourselves world yeah I we actually see ourselves as actually directly competing with the as actually directly competing with the modern data stack and that is a concept

[01:47] modern data stack and that is a concept that kind of goes across Industries that kind of goes across Industries right this is really around businesses right this is really around businesses that are essentially building their data that are essentially building their data management infrastructuring house right management infrastructuring house right things adopting things like B TR to Big

[02:00] things adopting things like B TR to Big query to transforming the data with query to transforming the data with tools like DBT or data form and tools like DBT or data form and ultimately to a lot of the Hidden layers ultimately to a lot of the Hidden layers of data management right anything from of data management right anything from data observability and quality control

[02:14] data observability and quality control to governance and Metric definitions and to governance and Metric definitions and schema definitions and then bi which is like definitions and then bi which is like where looker sits ultimately so I think where looker sits ultimately so I think the problem that we uncovered is a lot the problem that we uncovered is a lot of Brands adopted these Solutions not

[02:28] of Brands adopted these Solutions not knowing really how complex and expensive knowing really how complex and expensive it was going to be to build and to it was going to be to build and to ultimately maintain so that’s where we ultimately maintain so that’s where we come in we essentially focus on what is come in we essentially focus on what is the output of a modern data stack and

[02:43] the output of a modern data stack and that is similar across many businesses that is similar across many businesses that have Omni Channel sales but with a that have Omni Channel sales but with a heavy e-commerce Focus so that’s where heavy e-commerce Focus so that’s where we can come in and just get you from we can come in and just get you from zero to 100 super quickly but you

[02:58] zero to 100 super quickly but you also know that this infrastructure is also know that this infrastructure is Battle tested across over $2 billion Battle tested across over $2 billion doar of annual gmv that we process doar of annual gmv that we process maybe to put it is there like a cool maybe to put it is there like a cool case study that you can highlight from a

[03:09] case study that you can highlight from a recent client where the impact that you recent client where the impact that you guys delivered is so clear and guys delivered is so clear and obvious yeah so my favorite example is obvious yeah so my favorite example is we’ve been working for a few months now we’ve been working for a few months now with cpap.com so they are a direct

[03:24] with cpap.com so they are a direct consumer they sell CPAP machines and consumer they sell CPAP machines and related accessories products right so related accessories products right so they were on they were on Magento with a lot of internally built Magento with a lot of internally built technology then that includes the data technology then that includes the data management infrastructural stuff and so

[03:40] management infrastructural stuff and so I think they had a lot of pain points I think they had a lot of pain points around just the cost of maintaining that around just the cost of maintaining that infrastructure and the ultimate Roi that infrastructure and the ultimate Roi that was hard to see I think there was just was hard to see I think there was just still a lot of friction in terms of like

[03:53] still a lot of friction in terms of like individual leadership as well as individual leadership as well as operators being able to access the data operators being able to access the data that they need and can trust to make that they need and can trust to make decisions so since they were already decisions so since they were already migrating e-commerce platforms we had an

[04:05] migrating e-commerce platforms we had an opportunity to also have them opportunity to also have them dramatically simplify the data dramatically simplify the data management side of it into SourceMedium management side of it into SourceMedium so then what their Tech team is able to so then what their Tech team is able to do now is they can just like

[04:17] do now is they can just like specifically focus on investing into specifically focus on investing into things that are specific to their things that are specific to their business right we also have done a lot business right we also have done a lot of great work with them in terms of great work with them in terms of getting the number to be boardroom

[04:30] getting the number to be boardroom ready to be numbers that fpna can accept ready to be numbers that fpna can accept right the CFO would be happy about so right the CFO would be happy about so they’re able to swap out some of our they’re able to swap out some of our cost components but take our Revenue

[04:41] cost components but take our Revenue figures and other components that figures and other components that combines ultimately into the kpis combines ultimately into the kpis that the entire company should care that the entire company should care about so I think what’s really powerful about so I think what’s really powerful there is think about when the CEO the

[04:55] there is think about when the CEO the CFO the CMO all the way down to the CFO the CMO all the way down to the email marketing manager and the CX email marketing manager and the CX manager using one set of metrics and one manager using one set of metrics and one set of definitions to make decisions so

[05:07] set of definitions to make decisions so I’m really excited about where that’s I’m really excited about where that’s headed the other example that’s been headed the other example that’s been really cool is with our agency offering really cool is with our agency offering so one of our earliest adopters is the so one of our earliest adopters is the snow agency which is now part of Avenue

[05:20] snow agency which is now part of Avenue Z so they’ve actually been able to build Z so they’ve actually been able to build an entirely wh labeled dashboard an entirely wh labeled dashboard business on top of our infrastructure business on top of our infrastructure right so that’s provided them with a lot right so that’s provided them with a lot of differentiation and helped them

[05:32] of differentiation and helped them significantly increase close rate and significantly increase close rate and just increase the amount of insights and just increase the amount of insights and value that they can offer to your to value that they can offer to your to their customers besides like managing their customers besides like managing media so that is like a core part of

[05:46] media so that is like a core part of their offering now where they can their offering now where they can essentially create these Dash very essentially create these Dash very intricate dashboards that’s that they intricate dashboards that’s that they know are going to perform and then they know are going to perform and then they know they can trust the numbers on to

[05:56] know they can trust the numbers on to further help their customers and further help their customers and increase the value that they provide increase the value that they provide I want to know like how when you’re I want to know like how when you’re competing against the modern tech stack competing against the modern tech stack as or modern data stack as you’ve

[06:06] as or modern data stack as you’ve described that’s a lot of companies that described that’s a lot of companies that are billion dollar companies that are billion dollar companies that are going to be replaced by SourceMedium going to be replaced by SourceMedium how what have you done on your from a how what have you done on your from a team standpoint and from like a tech

[06:19] team standpoint and from like a tech build standpoint or product build standpoint or product build standpoint to enable you to get all standpoint to enable you to get all these efficiencies that you can actually these efficiencies that you can actually strip out a lot of these expensive techn strip out a lot of these expensive techn techologies and just go with Source

[06:30] techologies and just go with SourceMedium instead yeah I think the two core medium instead yeah I think the two core competencies that allows us to together competencies that allows us to together one is we try to spend 80% of our week one is we try to spend 80% of our week working with customers my goal is that

[06:45] working with customers my goal is that everyone in the company works with everyone in the company works with customers directly or indirectly but customers directly or indirectly but everyone should have an opportunity to everyone should have an opportunity to solve problems with the customers to get solve problems with the customers to get directly and then that allows us to

[06:57] directly and then that allows us to really understand the business specific really understand the business specific domain and the problems that businesses domain and the problems that businesses want to solve and then ultimately that want to solve and then ultimately that allows us to create and recognize the allows us to create and recognize the patterns right and that’s what gets

[07:10] patterns right and that’s what gets absorbed into the product so once bug absorbed into the product so once bug fixes happen or improvements in our fixes happen or improvements in our definitions where new metrics are definitions where new metrics are shipped or created right all of our shipped or created right all of our customers can benefit from that and

[07:25] customers can benefit from that and whether or not they want to adopt that whether or not they want to adopt that particular metric or that particular metric or that particular ular data source is up to them but what ular data source is up to them but what they know for a fact is there is going they know for a fact is there is going to be broad acceptance otherwise we

[07:38] to be broad acceptance otherwise we wouldn’t ship it to everyone at scale wouldn’t ship it to everyone at scale and then the other thing is that we copy and then the other thing is that we copy other kind of early other infrastructure other kind of early other infrastructure companies that have gone IPO right so if

[07:50] companies that have gone IPO right so if you look at a company like paler which you look at a company like paler which is what we model our company after or a is what we model our company after or a company like Hashi Corp right those company like Hashi Corp right those companies were entirely made of companies were entirely made of technical staff right in the early days

[08:04] technical staff right in the early days including sales so our entire company is including sales so our entire company is technical except for one but even that technical except for one but even that person is Savvy right technically savvy person is Savvy right technically savvy so everyone can write code everyone can so everyone can write code everyone can contribute to the product in a technical

[08:18] contribute to the product in a technical sense and then that allows our R&D to sense and then that allows our R&D to just be basically the entire company all just be basically the entire company all the time by focusing on providing value the time by focusing on providing value over whelming our customers with value over whelming our customers with value on a daily

[08:32] on a daily basis I want to know like when you went basis I want to know like when you went into SourceMedium you had a vision and into SourceMedium you had a vision and now you’re four years later working with now you’re four years later working with some nine figure Brands you got a strong some nine figure Brands you got a strong team behind you and a really cool

[08:45] team behind you and a really cool product did you are you like on the path product did you are you like on the path that you had envisioned four years ago that you had envisioned four years ago or is SourceMedium today actually quite or is SourceMedium today actually quite different than what you had set out

[08:56] different than what you had set out to build four years ago to build four years ago yeah that’s actually such a funny yeah that’s actually such a funny question because when I started the what question because when I started the what I wanted was a slack bot the company was I wanted was a slack bot the company was incorporated in May

[09:10] incorporated in May 2020 so what I wanted was a slack bot 2020 so what I wanted was a slack bot that’s sit in your slack that has access that’s sit in your slack that has access to all your data that can you can talk to all your data that can you can talk to and give you

[09:19] to and give you insights I didn’t know that was insights I didn’t know that was called lln right so I had no idea how to called lln right so I had no idea how to build that to be honest and end up build that to be honest and end up becoming like a daily slack reporting

[09:32] becoming like a daily slack reporting bot which became actually semi poopular bot which became actually semi poopular where it had to be taken down but it’s where it had to be taken down but it’s coming back because of the API versions coming back because of the API versions but I think then that led us to this but I think then that led us to this winding journey to become a dashboard

[09:46] winding journey to become a dashboard company right but really just like company right but really just like ultimately now where we’re going is that ultimately now where we’re going is that route right because the number one route right because the number one obstacle to adopting AI for an obstacle to adopting AI for an organization is UN Ying all your data

[10:00] organization is UN Ying all your data right so that is like the most expensive right so that is like the most expensive time consuming and boring part of it so time consuming and boring part of it so now that we’ve been doing that for four now that we’ve been doing that for four years I think what that sets us up for

[10:11] years I think what that sets us up for is to start really like extracting the is to start really like extracting the value out of that data set in a dramatic value out of that data set in a dramatic way and that is going to be with a way and that is going to be with a combination of enabling really use case

[10:22] combination of enabling really use case driven statistical and machine learning driven statistical and machine learning modeling that brings open source options modeling that brings open source options into the pray as well as internal Ai into the pray as well as internal Ai co-pilots and agents and we have some co-pilots and agents and we have some pretty exciting plans behind that so

[10:38] pretty exciting plans behind that so it’s somehow the we came full circle it’s somehow the we came full circle thanks to chat GPT and then the rest was thanks to chat GPT and then the rest was history that makes perfect sense that history that makes perfect sense that you’re going to go back to that route

[10:48] you’re going to go back to that route and apply some AI technology on top and apply some AI technology on top of it especially because you understand of it especially because you understand data sets of multi- Channel Ecom players data sets of multi- Channel Ecom players pretty much better than anyone that’s pretty much better than anyone that’s super exciting do you like can you are

[11:02] super exciting do you like can you are you guys profitable can you just you guys profitable can you just allocate resources that you already have allocate resources that you already have on the team to work on that or would on the team to work on that or would that potentially suggest another fund that potentially suggest another fund raise or something like

[11:13] raise or something like that yeah I think we have gotten to a that yeah I think we have gotten to a place we weren’t always there I made a place we weren’t always there I made a lot of mistakes but we’ve gotten to a lot of mistakes but we’ve gotten to a place where we’re pretty close to being

[11:24] place where we’re pretty close to being profitable the a metric that I track profitable the a metric that I track closely is a annual recurring Revenue closely is a annual recurring Revenue per full-time employee we want to make per full-time employee we want to make sure that we learn from our lessons in sure that we learn from our lessons in the past and not just throw people at

[11:36] the past and not just throw people at the problem but really think about the problem but really think about Automation and really think about using Automation and really think about using technology to create productivity gains technology to create productivity gains but I think what’s cool right now is we but I think what’s cool right now is we have our entire business built on top of

[11:50] have our entire business built on top of gcp I’m a ex googler as well so I have gcp I’m a ex googler as well so I have some allegiances there but I also do some allegiances there but I also do believe they’re best positioned in the believe they’re best positioned in the AI era as a cloud service provider so

[12:02] AI era as a cloud service provider so we’ve been getting a lot of businesses we’ve been getting a lot of businesses onto gcp we’ve we’ve gotten a lot of onto gcp we’ve we’ve gotten a lot of businesses to switch from other clouds businesses to switch from other clouds like AWS and Azure onto gcp and our like AWS and Azure onto gcp and our solution is flexible as well you know we

[12:15] solution is flexible as well you know we can enable other clouds using gcp as the can enable other clouds using gcp as the foundation so Google is slowly foundation so Google is slowly recognizing that and we’re actually recognizing that and we’re actually working with Google directly on like working with Google directly on like doing some proof of concepts by enabling

[12:28] doing some proof of concepts by enabling like both Gemini Pro 1.5 right on top like both Gemini Pro 1.5 right on top of your data as well as open source of your data as well as open source Alternatives like llama right so we’ll Alternatives like llama right so we’ll have pretty hopefully we’ll have some have pretty hopefully we’ll have some proof of concept to show the world soon

[12:43] proof of concept to show the world soon the other thing I’m excited about is the other thing I’m excited about is really to get some of the machine really to get some of the machine learning models enabled for Brands learning models enabled for Brands there’s a lot of things around there’s a lot of things around Predictive Analytics that people need

[12:53] Predictive Analytics that people need like time series forecasting lead like time series forecasting lead scoring probability to churn so we will scoring probability to churn so we will probably have those capabilities opened probably have those capabilities opened up sooner rather than later so very up sooner rather than later so very excited about that cool well Fei thank

[13:06] excited about that cool well Fei thank you so much for the wisdom thanks you so much for the wisdom thanks for the time and great to catch up as for the time and great to catch up as always speak to you soon Al righty talk always speak to you soon Al righty talk to you sir