BI Rule: Price the Offer, Not the Platform
How should an agency set fees and margin expectations for a BI-powered reporting or analytics offer? Set fees based on the full delivery workflow (data modeling, source reliability, analyst review, decision cadence, client access), not on the platform subscription cost.
By InnovaAI ResearchPublished Updated
“How should an agency set fees and margin expectations for a BI-powered reporting or analytics offer?”
Set fees based on the full delivery workflow (data modeling, source reliability, analyst review, decision cadence, client access), not on the platform subscription cost.
Agencies often price BI retainers as a markup on the software license, ignoring the hidden costs of data cleaning, dashboard iteration, and client onboarding, which can consume 3-5x the platform cost in analyst hours.
The platform alone does not establish offer value; data modeling, source reliability, analyst review, decision cadence, and client access all affect delivery cost and usefulness. For example, Knowi connects to over 70 data sources without ETL, but that doesn't eliminate the need for analyst review or client training. Similarly, Sigma Computing's live queries on warehouse data still require governed data models to be useful. A recent study of 107 million AI answers shows that citation gaps and data quality issues can undermine client trust, reinforcing that the platform is just one layer in a reliable reporting stack.
- •Agency is scoping a managed analytics retainer for a client without an internal data team
- •Agency is comparing white-label BI platforms for resale or embedded reporting
- •Agency is pricing a one-off dashboard build and needs to justify the cost
- •Agency is deciding whether to invest in data modeling and source integration vs. relying on out-of-the-box connectors