SourceMedium vs building an in-house data stack

Why teams choose SourceMedium over building in-house

It's a familiar story. Tiege Hanley, a scaling DTC brand, built an in-house stack with Fivetran + Snowflake + Tableau and hired a full-time data scientist. After two years and significant monthly expenditure, the tools were still "too technical for business teams in marketing, operations, and finance." They switched to SourceMedium to get a platform that actually drove decisions. Here's why this pattern keeps repeating.

Building a proprietary ecommerce data stack means hiring data engineers ($120K–$175K), analytics engineers ($110K–$155K), and data analysts ($80K–$100K). A lean two-person team costs $250K–$330K/year — before a single tool subscription. Add the warehouse, ELT tool, transformation layer, BI platform, and orchestration tooling, and realistic total costs run $300K–$500K/year.

53% of these projects cost 189% of their original estimate. 31% get cancelled entirely.

Where the approaches differ

Build time vs day-one value: Building an in-house stack takes 6–12 months before the first useful insight — months 1–2 for hiring, 3–4 for tool selection, 5–8 for data modeling, 9–12 for dashboards and bug fixes. SourceMedium delivers pre-built data models and 20 analytics modules from day one.

The bus factor: When the single engineer who built your stack leaves, the replacement cost runs $65K–$260K — recruiters, onboarding, knowledge transfer. Plus 6–12 months of lost productivity while the new hire learns the custom architecture. SourceMedium's data models, quality checks, and templates are maintained by the platform, not a single employee.

Hidden maintenance costs: Source APIs from Shopify, Meta, and Google Ads change multiple times per year. Maintaining connectors alone requires 2–3 FTE ($300K–$450K/year). Add recruitment costs ($15K–$40K per hire), onboarding ramp (3–6 months per engineer), and the 10-year maintenance bill approaches $3 million.

"Too technical for business teams": The Tiege story illustrates the most common failure mode — the stack works technically but can't be used by the people who need the insights. SourceMedium is built for marketing, operations, and finance teams. Open-source Looker Studio templates give business teams a reporting layer they can actually customize without writing SQL.

Dedicated support, not a ticket queue: Every SourceMedium customer gets a named Customer Solutions Analyst — US-based, with hands-on DTC experience across marketing, ops, finance, and executive teams. Solution hours are included in your plan, scoped during the sales process so the highest-value work fits within what's already budgeted. No offshore support teams, no $250/hr professional services surprises, no "implementation packages" as a separate line item. If you need additional hours, pricing is transparent — and you always have the option to resource work with your own team instead.

A warehouse your team can build on. Your data lives in BigQuery with included compute — your data team can run custom SQL, build dbt models, and connect any BI tool natively. The foundation is managed; the analysis is yours. Centralize beyond ecommerce — finance, ops, or any custom source — into the same warehouse at no extra cost.

Automated quality vs manual maintenance. In-house teams spend significant time debugging pipeline failures and data discrepancies. SourceMedium runs 2,500+ automated quality checks daily across every source. When numbers reconcile back to Shopify and your ad platforms, the data team stops firefighting and starts analyzing.

When building in-house makes sense

Building in-house works for organizations with dedicated data engineering teams (3+ engineers), truly unique data requirements that no platform can address, and the budget to sustain $300K–$500K+/year indefinitely. If your ecommerce analytics requirements are highly custom and your team has the resources for ongoing maintenance and API upkeep, in-house provides maximum flexibility. Many SourceMedium customers started in-house, hit the maintenance wall, and switched — they now use BigQuery as the hub for both SourceMedium-managed ecommerce data and custom in-house pipelines for non-ecommerce sources.