Data + analytics
Data platform websites that don't need a 40-minute call.
Judged on: where do you sit in my stack, and what do you replace?
Data buyers arrive with a stack, a pipeline problem and a budget under review. They want to know where you sit, what you replace and what it costs at their volume. We make that answerable in one scroll.
Who's reading your website
Head of data
Where you fit in the stack, and what you replace
Data engineer
Connectors, schemas, latency and failure behaviour
Analytics or BI lead
Time to first dashboard, and self-serve for the business
Security + finance
Data residency, access control and cost at real volume
The problem
Why data platform websites are hard
- 01
Nobody knows what layer you are
Warehouse, lakehouse, ETL, reverse ETL, semantic layer, observability. If the homepage doesn't place you, buyers guess wrong and leave.
- 02
Architecture diagrams as marketing
A twelve-box diagram proves the product is complicated, not that it's good.
- 03
Consumption pricing panic
Credits and consumption models make finance nervous. Unclear pricing pushes deals into long procurement loops.
- 04
Migration fear
Buyers are not comparing you to nothing. They're comparing you to ripping out something that already works.
The stack question
Answer these four or lose the evaluation
Data buyers arrive mid-project with a stack diagram in their head. Your site either slots into it in the first minute, or it does not.
Layer
What you sit between, named tools on both sides
End-to-end data platform
Replace
The tool or script this removes
Complements your existing investments
Limits
Volume, latency, refresh rate, connector list
Scales infinitely
Cost
A worked example at a stated volume
Credits, explained nowhere
The fix
What your website has to do
Place yourself in the stack in one line
Say what you sit between and what you replace. Name the tools your buyers already run.
One diagram, five boxes
Show the path data takes through you, not your entire internal architecture.
Publish connectors and limits
A searchable connector list, refresh rates and volume limits answer most technical questions without a call.
Make cost modellable
A calculator or worked example at a stated volume. Vague consumption pricing reads as risk.
Proof
Trust signals buyers look for
Put these where buyers make decisions: near CTAs, on pricing and in the footer. Not buried on an About page.
- Connector and integration list
- Architecture and data flow documentation
- Security, residency and access control page
- Benchmark or performance notes with method
- Migration guides from named tools
- Customer logos by data maturity
94%
of buying groups rank their preferred vendors before first contact with sales.
If your website doesn't make the shortlist, sales never gets a shot.
Where to start
Pages we'd build first
A typical starting sitemap for data platform companies. We adjust it after the audit.
Homepage
Where you sit, what you replace
Product pages
By layer or capability
Connectors
Searchable, with refresh detail
Pricing + calculator
Cost at real volume
Migration guides
From the tools you displace
Docs
Deep enough for engineers
Data + analytics FAQ
Questions we hear a lot
Something else? Email admin@baddesign.io. The founder replies.
Our product does several things. Which do we lead with?
Lead with the one that gets you the fastest yes from your best-fit buyer. The others belong on product pages, not in the headline.
Should we publish benchmarks?
Only with the method next to them. Data buyers will check, and an unexplained benchmark costs more trust than it buys.
Is a cost calculator risky?
Less risky than silence. Show a worked example at a realistic volume, with the assumptions written down.
Let's fix your data platform site.
Send your URL. We'll review it against what buyers in your industry look for, and send the top fixes free.