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Business Intelligence

Embedded analytics and customer-facing dashboards

Embedded analytics that puts customer-facing dashboards inside your product or client portal, built by a tool-neutral team that advises before it builds.

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Customers see the value of your product inside your productMockup of a SaaS application with an embedded dashboard titled Your team saved 120 hours this month, with weekly hours saved (demo data).Your appEmbedded dashboardYour team saved 120 hours this monthDemo dataHours saved by automated tasks, weeklyHours saved120Tasks automated1,940vs last month+41%18W121W222W324W426W528W631W735W8This month: 120 hoursCustomers see the value of your product inside your productMockup of a SaaS application with an embedded dashboard titled Your team saved 120 hours this month, with weekly hours saved (demo data).Your appEmbedded dashboardDemo dataYour team saved 120 hours thismonthHours saved by automated tasks, weeklyHours saved120Tasks automated1,940vs last month+41%This month: 120 hours18W121W222W324W426W528W631W735W8

Embedded analytics, designed and governed end to end.

What it is

Embedded analytics shows data where users already work

Embedded analytics is the integration of dashboards, reports and data visualizations directly into another application, such as a SaaS product, client portal or internal system. Users see data in the context of their work, without switching to a separate BI tool or exporting to spreadsheets. They can decide what to do next on the same screen.

Users see the data and act on the same screenBefore: users go from the app to a CSV export, a spreadsheet and a separate BI tool. After: a chart inside the app sits next to the action the user takes.Users see the data and act on the same screenReporting outside the product vs embedded analyticsOutside the productYour appExport to CSVSpreadsheetSeparate BI toolThree tool switches before a decisionYour appEmbedded analyticsOpen orders by weekAct on this viewSame screenUsers see the data and act on the same screenBefore: users go from the app to a CSV export, a spreadsheet and a separate BI tool. After: a chart inside the app sits next to the action the user takes.Users see the data and act on the samescreenOutside the productYour appExport to CSVSpreadsheetSeparate BI toolThree tool switches before a decisionEmbedded analyticsYour appOpen orders by weekAct on this viewSame screen
Benefits

Embedded analytics makes your product more valuable and easier to renew

For product leaders, embedded analytics turns data your application already holds into visible value for customers. Users see what your product does for them, in numbers, every time they log in.

That changes renewal conversations. Instead of asserting value, your customer success team can point to it. The benefits below are the ones embedded analytics is designed to deliver. Each one ties a product metric to a commercial result.

Accounts that open in-app reports renew more oftenSorted bars, renewal rate by report usage: weekly 94%, monthly 88%, rarely 81%, never 72% (demo data).Accounts that open in-app reports renew more oftenDemo dataRenewal rate by how often customer users open embedded reports, last 12 months0%25%50%75%100%Opens reports weekly94%Opens reports monthly88%Opens reports rarely81%Never opens reports72%Association, not proof of cause: use it to target report adoption in onboarding and renewals.Accounts that open in-app reports renew more oftenSorted bars, renewal rate by report usage: weekly 94%, monthly 88%, rarely 81%, never 72% (demo data).Accounts that open in-appreports renew more oftenDemo dataRenewal rate by how often users open embeddedreportsOpens reports weekly94%Opens reports monthly88%Opens reports rarely81%Never opens reports72%Association, not proof of cause.

Customers see the value they get

In-app analytics shows results from your product, which supports renewals and upsell.

Users stay in your application

Insight in context reduces exports to spreadsheets and other tools.

A new pricing lever

Advanced reporting can become a premium tier or add-on.

Fewer one-off report requests

Self-service dashboards can cut support and engineering time.

Stronger product demos

Prospects see live, branded analytics in demos, which helps product and sales teams show value before purchase.

Usage insight for your product team

Embedded usage data shows which reports customers open, guiding the product roadmap with evidence.

How we work

Embedded analytics works through a data layer, a BI engine and an embedding method

Embedded analytics connects three layers: the data, the analytics engine and your application. The data layer prepares and secures the information. The analytics engine renders dashboards. The embedding method determines how tightly those dashboards integrate with your product's interface.

How data reaches a dashboard inside your product

Select a stage, use Next or the arrow keys

Data layer. Each tenant's data kept separate. App data flows to a warehouse or model, structured, governed and refreshed by tenant.

Step 1 of 6

The choice of embedding method is a trade-off between speed to market and depth of integration. An iframe can be live quickly but offers less control. APIs and SDKs take longer but feel native. A product can start with one and move to the other as adoption grows.

Security runs through every layer. Each tenant's data must stay separate from the data model to the screen, and that is designed in from the start, not added at the end. We document the architecture so your engineers can extend it.

The diagram below shows how a request flows from user login to a rendered, filtered dashboard. Each layer is shown with its owner. Security is tested first. Nothing is exposed by default.

Power BI
KPIs we track

Customers expect SaaS reporting metrics that prove value

Customers expect SaaS reporting metrics that show the value they get from your product, not just raw activity counts. Useful in-app metrics answer one question for the customer: is this product worth renewing? These groups are a practical starting point. Each metric can be shown per user, team or account.

What a customer sees inside your product

Demo data
Active users (30d)184▲ +12%
Teams active9 of 11▲ +2
Reports feature use63%▲ +8 pts
Sessions per user14▲ +3

Weekly active users up 30% since onboarding

Weekly active users, last 8 weeks

120140160180200W1W2W3W4W5W6W7W8184 in W8: Highest weekly usage so far120140160180200W1W3W5W7184 in W8: Highest weekly usage so far

So what: Customers see adoption growing, which gives customer success a clear renewal story.

TeamActive usersSessionsChange
Operations62910+15%
Sales48640+9%
Finance31420+11%
Support43590+13%

Show adoption

Demo

Usage: active users, feature use and activity trends by team.

Show results

Demo

Outcomes: orders processed, tickets resolved or hours saved.

Show progress

Demo

Targets: performance against goals each customer sets.

Support renewals

Demo

Consumption: usage against plan limits and spend over time.

Show benchmarks

Demo

Comparisons: anonymized peer averages or the customer's own history, where your data and contracts allow it.

SaaS analytics
Use cases

Embedded analytics use cases span SaaS products, portals and supplier reporting

Embedded analytics fits any application where users need to see data about their own activity, results or assets. These are common use cases, from SaaS products to client and investor portals. Each one names the outcome for the end user. A first release usually serves one user group, then expands.

Each embedded view shows end users their own resultsFour use-case cards with demo charts: active users in a SaaS product, leads in a client portal, occupancy in an owner portal, on-time delivery in a supplier portal.Demo dataSaaS productWeekly active usersup 18%Users, weeklyClient portalLeads grew threemonths runningLeads, monthlyOwner portalOccupancy 94%,two units vacantBldg 1Bldg 2Bldg 3Bldg 4Units letSupplier portalOn-time deliverydipped in week 6On-time %, weeklyEach embedded view shows end users their own resultsFour use-case cards with demo charts: active users in a SaaS product, leads in a client portal, occupancy in an owner portal, on-time delivery in a supplier portal.Each embedded view showsusers their own resultsDemo dataSaaS productWeekly active usersup 18%Users, weeklyClient portalLeads grew threemonths runningLeads, monthlyOwner portalOccupancy 94%, twounits vacantUnits letSupplier portalOn-time deliverydipped in week 6On-time %, weekly
Use case 1

Product value visible to customers

SaaS products: in-app dashboards that show usage, outcomes and performance inside the application.

Use case 2

Clients see their results

Client portals for agencies, consultancies and service firms that share results with their clients.

Use case 3

Owners and investors self-serve

Property and asset portals with portfolio, occupancy and income dashboards for owners and investors.

Use case 4

Suppliers and customers aligned

Manufacturing and supply chain views of orders, quality and delivery performance for external users.

real estatemanufacturing
Comparison

Buying and embedding a BI platform is usually faster than building

Build from scratchBuy and embedTraditional BI
Embedded vs traditional BIEmbedded: inside your app, for customersTraditional BI: separate tool, for staff
Build from scratchFull controlLong developmentOngoing engineering cost
Buy and embedFaster to marketLower maintenanceSome customization limits
business intelligence
How we work

Our embedded analytics delivery keeps product and engineering in the loop

We deliver embedded analytics in clear phases, so product and engineering teams know what to expect and when. Each phase ends with a review, and your developers stay involved throughout, because the embedded layer becomes part of your product.

Embedded analytics delivery in six phases

Select a stage, use Next or the arrow keys

Discovery. A clear build-or-buy decision. Define users, tenants, metrics and commercial goals, review the data, confirm readiness and choose build or buy.

Step 1 of 6

Discovery is advisory work and the gate for the build. We propose implementation only when the data, the product team and the commercial case are ready, and we say so when a vendor's native reporting would serve you better.

Timelines depend on the number of tenants, data sources and dashboards, and are set during discovery. We agree what the first release will include, usually a small set of high-value dashboards for one user group, and expand from there based on usage data.

After launch we track adoption and capacity costs, so you can see which dashboards customers use and what the embedded layer costs to run.

The aim is simple: dashboards that customers use, built on data they can trust, at a cost your product can carry. Each phase has a named owner on both sides and a short written sign-off before the next one starts. Your team owns everything we build. You get a written plan per phase. Every phase ends with a demo.

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Frequently asked questions

Embedded analytics: questions product leaders ask before choosing a platform

We are tool-neutral and recommend the platform that fits your product, users and budget. Power BI Embedded is a common choice because of its security model and capacity-based pricing, but the data model and architecture we design are not tied to a single vendor.

We apply row-level security in the analytics model and pass a secure token from your application that identifies the user and tenant. Each user sees only the data they are entitled to, and we test tenant isolation thoroughly before launch.

Building gives full control but needs sustained engineering time. Embedding an existing BI platform is usually faster and cheaper to maintain. We compare both options against your product roadmap, team capacity and customization needs during discovery and recommend one, with the reasons and trade-offs written down.

Yes. Through themes, APIs and SDKs we can apply your fonts, colors and layout, hide BI platform branding where licensing allows, and control filters and interactions from your own interface, so the dashboards feel like part of your product rather than a separate tool.

Scope your embedded analytics project in one call

Tell us about your product, your users and the data they need to see. We will outline the architecture, the build-or-buy choice and a phased delivery plan for your embedded analytics project. You will also see the main cost drivers, so your product team can plan budget and release timing with confidence before any build begins. If embedding is premature, we say so.

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