Customer Dashboards: Build or Buy?

This article explores the build or buy decision for customer-facing dashboards and reports. We’ll cover why an in‑house build looks attractive at first, where hidden costs pile up, why traditional embedded business intelligence software often disappoints, and how you can get the best of both worlds, without the trade-offs.

TL;DR

• There are trade-offs when choosing to ‘build or buy’ in-app dashboards for your customers
• Building in-house gives you full control, but comes with vast hidden costs that compound over time.
• Embedding a general‑purpose BI software can save time, but there’s massive trade-offs on speed, control and your customers’ experience.
• Using a purpose-built, developer-friendly tool like Embeddable can give you the best of both worlds.

‍

Why an in‑house custom build is appealing

Teams lean toward building because it promises:

• Full control over UX, UI, interactions, and performance.
• No vendor dependency or external license line‑item.
• A perfect fit with your design system, component library, and CI/CD processes.
• You may also have had bad experiences with embedded BI tools.

These benefits are real, especially when analytics are core to your product, and they explain why many teams start here.

‍

The costs (and hidden costs) of building dashboards yourself

Teams who “get a v1 working” often discover the ongoing cost curve is steeper than expected. We’ve spoken to thousands of companies who have pursued a custom build, only to find themselves running into these problems. 

1) Engineering time for the initial build

Even if you’re using one of many great charting libraries, you still must:

• Write and maintain SQL queries and models per chart; and handle schema evolution.
  
• Implement data access, connections, and set up scalable, performant caching for speed.
  
• Build in multi‑tenancy and fine‑grained data isolation (often via RLS) so each customer only sees their own data.
  
• Implement interactions (drill‑downs, cross‑filtering, parameters) across components.
  
• Add export/share flows, and support localization (language, currency, time zones).

2) The feature treadmill, customers ask for more

Custom views, self‑serve filters, drill‑down, CSV/Excel/PDF export, scheduled delivery, white‑labeling, and per‑role governance are routine asks. Each one consumes cycles across product, design, and engineering.

3) Every change runs your full delivery process

Discovery → acceptance criteria → spikes → scoping → design → estimation → sprint planning → build → QA → design review → release → iterations. Even healthy Agile teams experience this overhead; it’s inherent to shipping software at quality.

4) Performance: users expect sub‑second load times

Usability research highlights three response‑time thresholds: ~0.1s feels instantaneous, ~1s preserves flow, ~10s risks abandonment. These are benchmarks that strongly influence how “fast enough” your dashboards must be. (ref: NNGroup)

5) After a year, it’s tech debt

Analytics models, joins, metrics definitions, and visualization glue code drift from reality. The “v1” becomes hard to extend, especially as stakeholders ask for new slices and latency budgets tighten.

6) Opportunity cost

Every hour spent re‑implementing table stakes analytics is an hour not spent on differentiating product features. That trade‑off compounds.

All in all, the total cost of pursuing a custom, in house build is scary; and not a cost teams should take on lightly.

‍

Should you ‘Buy’ and embed your business intelligence tool?

On paper, “buy” should be simpler: plug in an embedded analytics tool and ship more, faster. In practice, many teams tried the “buy” option and hit walls. 

This is because most of the tools teams have been using (think PowerBI, Looker, Tableau, Metabase, Sigma, Sisense etc.) were designed for data teams and internal BI, not for your product and engineering teams to embed in customer‑facing applications.

The architecture of traditional embedded business intelligence software is not designed for embedding in your application, and it shows. You’re effectively using a hammer for a screw, when you should be using a screwdriver.

‍

Customer-facing dashboards and reports should:

• Look and feel like native within your application. Use your design system, Load in your DOM (iframe embeds are a no-go)
• Load fast for customers (ideally sub-second)
• Scale up and down elegantly to potentially vast quantities of data consumers.
• Be flexible and extendable in any way you want for your customers.
• Handle multi-tenancy easily and intuitively
• Be tools for your product and engineering team, not your data team.

‍

For the internal business intelligence use case:

• It doesn’t need to look like your application and adopt your design system - it’s an internal tool.
• It doesn’t need to load really fast - the users are data analysts, and they know a SQL query is running against the database (your customers don’t know or care about this)
• It doesn’t need to handle huge scale & concurrency - the number of internal users you have at any one time is typically nowhere near the scale of customer-users.
• A standard set of the most common business charts is fine - you don’t need more.
• It’s a single tenant environment - i.e. only your team is accessing the data. So handling multi-tenancy with a traditional embedded BI tool requires workarounds and complexity.

The architecture needed; indeed the tools needed; to deliver for these very different use cases is vastly different.

A completely different approach is required.

‍

How to get the best of both worlds: the optimal architecture for embedded analytics

A modern approach is headless, developer‑first embedded analytics. Not part of a general-purpose BI tool built for data teams, but a purpose-built tool that’s built for product and engineering teams to deliver incredible customer experiences with fast iterations and secure, scalable embedding.

Embeddable offers you the sweet spot between “build it yourself” and “buy and bolt it on.” Below is a structured breakdown of how it avoids the pitfalls of both, with real-world voices to back it up.

1. Looks and feels native within your application

Traditional BI embeds (iframes) break your design system and feel bolted on. Embeddable dashboards render as lightweight web components directly in your DOM. They inherit your CSS, work with your layouts, and follow your accessibility rules, so they feel like they were built in-house.

“Using Embeddable, we have successfully achieved our goal of building dashboards with a no-code solution that use our own components. The platform has allowed us to maintain our desired look and feel.” - Pierre Vaidie, Co-founder & Head of Engineering at Pledge

2. Build and iterate fast

Custom builds are laborious to iterate on, this is a great benefit of an off-the-shelf tool. Embeddable also provides a platform to enable rapid build and iterations, and enables the release of advanced features with a few clicks.

“Using Embeddable is making it easier & quicker to build insights and dashboards for our customers, by enabling us to make changes in a no-code builder and deploy them without engineering input.” - Ritchie Cargill, Technical Lead at Resident Advisor.

2. Load fast for customers (sub-second)

Users won’t wait 5–10 seconds for data. Embeddable is built with advanced caching, pre-aggregations, and query optimization. This ensures sub-second interactions wherever possible, preserving user flow and avoiding churn.

“The charts and dashboards load lightning-fast for users” - Jason S., Senior Software Engineer

3. Scale up and down elegantly to vast quantities of data consumers

An internal BI tool might be fine for 50 analysts, but not for 50,000 customers. Embeddable is architected for SaaS-scale concurrency, with tokenized access and horizontal scalability built in. Whether you’re serving hundreds or millions of users, it grows with you.

4. Be flexible and extendable in any way you want

Custom builds give you flexibility but slow down iteration. BI tools are fast to start but rigid. Embeddable provides both: you can use its chart components as-is, extend them, or replace them entirely with your own or with libraries like D3, ECharts, or Recharts. Everything is code-first, so you’re never boxed in.

“Now we have a solid foundation to iterate and continuously offer new ways of visualizing data for our customers.” - Brian Rountree, VP of Engineering at Monta.

5. Handles multi-tenancy easily and intuitively

Building secure data isolation yourself is complex, and most BI tools don’t do it well. Embeddable makes it straightforward with tokenized embedding, row-level security, and dataset modeling. Each tenant sees only their own data - no workarounds needed.

6. Built for your product and engineering team, not your data team

Most BI software was designed for internal analysts. Embeddable is built for developers: modern SDKs, native React support, APIs your engineers will actually like, and a no-code builder so PMs and analysts can compose dashboards without creating dev bottlenecks.

“The impact on our development team has been immense.” - Kaitlyn Lovatt, Lead Product Manager at HONK.

‍

Should you build or buy customer dashboards?

• Build it yourself: Full control, no third‑party dependency; but expect major engineering and opportunity costs.
  
  
• Buy and embed a traditional BI tool: Faster to ship and has built-in features; but it won’t feel native in your application, embeds via iframes, slower loads, scales poorly, and developer friction.
  
  
• The best of both worlds: Embeddable. A purpose‑built solution that gives you the control and extensibility of a custom build, with the build and iteration speed of an embedded analytics tool; plus performance at scale and a delightful developer experience.

‍Call to action:
Want a quick architectural review and a hands-on look at how your dashboards could work with Embeddable? Book a call with our team to explore fit and timelines.