01Requirements
Reporting requirements
Users, decisions, KPIs, filters, drill-downs, cadence, access and device requirements — documented before anything is built.
- └decision per view
- └filters + drill paths
- └access + device needs
US dashboard and reporting services
Dashboards built for the decision, not the metric list
Digital Otters builds Looker Studio, Power BI and connected marketing dashboards for US executives and channel teams. Every view is designed around a decision, governed metric definitions, reliable refresh and the level of detail each role actually needs.
01US-focused commercial strategy02Strategy and implementation in one team03Client-owned accounts and data04Clear scope, boundaries and reporting
US project inquiry
Request a dashboard scope
Tell us who needs the report, which systems hold the data, and what decision the dashboard should make easier.
// Tool licenses and paid connectors stay with their providers, in accounts you own.
The short answer
Dashboards and reporting: the short answer
Dashboard and reporting services build the live views a team actually opens — marketing performance, pipeline and revenue in one place, connected to GA4, ad platforms and the CRM, designed around the decisions each audience makes rather than every metric that exists. A dashboard nobody opens is a data problem wearing a design costume.
Direct definition: Digital Otters provides marketing dashboard and reporting services using Looker Studio, Power BI and connected data sources to deliver governed executive, channel, pipeline and customer reporting.
- Platform
- Google Looker Studio on client-owned sources
- Design rule
- Each chart answers a named decision
- Audiences
- Executive, channel and operational views separated
- Refresh
- Live connections, not monthly PDF exports
What you receive from dashboards & reporting
The exact scope follows your current systems, commercial objective and who is implementing.
02Model
Metric and data model
A governed dictionary and reusable model covering formulas, grain, joins, exclusions, freshness and ownership.
- └metric dictionary
- └joins + grain documented
- └owner per metric
03Build
Dashboard and reporting workflow
Role-specific views, automated refresh, validation, permissions, training and the maintenance guidance your team keeps.
- └role-specific pages
- └refresh + subscriptions
- └training + handover
Failure modes
Why dashboards become expensive wallpaper
A dashboard can refresh automatically and still be misleading, slow or ignored. The definitions, the data model and the audience matter far more than decorative visualization.
01✕ unused
Every metric gets equal emphasis
Three tiers, decided before layoutWithout a hierarchy from outcome to driver to diagnostic, the reader has to invent the priority themselves — so they stop reading.
02
Data is blended without common keys
Join keys proven, or no blendLooker Studio blends and other joins need compatible dimensions, aggregation and grain. Force it and the totals quietly lie.
03
The dashboard is the data model
Model once, reuse everywhereComplex formulas buried inside individual charts cannot be reused, audited or maintained by anyone who did not build them.
04
Refresh ownership is unclear
Named owner + failure alertingCredentials, gateways, connectors, API limits and source changes break reports silently, usually the week before a board meeting.
05
Executives and specialists share one view
Separate views per roleLeadership needs direction and exceptions; channel teams need diagnostic depth. One page for both serves neither.
Role views
Executives and specialists do not share one view
Leadership needs direction and exceptions. Channel teams need diagnostic depth. Select a role to see what its view contains — and what we deliberately leave out.
Audience
Adoption test
Do people open it weekly without being asked? That is the only success metric that matters.
view · executive scorecard · 1 pagecadence · monthly, with a weekly exception alert
Are we on track, and what needs a decision this month?
One page, outcome first. Leadership should be able to read direction, variance and the exceptions that need a decision without opening a filter.
tier 1Revenue vs targettier 1Qualified pipelinetier 2Efficiency by channeltier 2Exceptions needing a call
Included
- Outcome vs target, with variance stated
- Efficiency and contribution by channel
- Exceptions and what we recommend doing
Left out on purpose
- Keyword, ad-group and creative detail
- Every metric a platform can export
- Unexplained week-on-week noise
view · channel performance · multi-pagecadence · weekly, live connections
Which campaign, audience or asset should change this week?
Diagnostic depth by design: campaign, audience, creative, landing page and cost — with filters and drill paths that make a cause findable in minutes.
tier 1Qualified leads + CPAtier 2Campaign and audience splittier 2Creative and landing pagetier 3Search terms and placements
Included
- Campaign, audience and creative breakdowns
- Cost per qualified outcome, not per click
- Filters, date compare and drill paths
Left out on purpose
- Board-level narrative framing
- Metrics no one can act on this week
- Blends that need a caveat to read
view · operational monitor · livecadence · daily, or on alert
What is stuck right now, and who owns it?
Built for the person who has to act today: routing, response times, unclaimed records, data-quality failures and the owner of each.
tier 1Response time vs SLAtier 2Unclaimed or stalled recordstier 2Workflow and sync errorstier 3Data-quality checks
Included
- Service levels and what breached them
- Queues, owners and escalation status
- Refresh and connector failures
Left out on purpose
- Attribution debate and modeling
- Long-range trend narrative
- Revenue commentary for the board
view · spend and contribution · monthlycadence · monthly close, reconciled
Does marketing spend reconcile, and what did it contribute?
Reconciled figures in the same units as the ledger: spend by channel and market, committed versus actual, and contribution where the data supports the claim.
tier 1Spend vs budgettier 2Contribution by channeltier 2Committed vs actualtier 3Reconciliation exceptions
Included
- Spend by channel, market and period
- Committed versus actual, reconciled
- Contribution where data supports it
Left out on purpose
- Platform-reported conversions as revenue
- Mid-month estimates presented as final
- Metrics with no ledger equivalent
Services
From source to decision, in that order
We can build a single scorecard or a governed reporting environment. The sequence does not change.
01Reporting requirementsDefine
Users, decisions, KPIs, filters, level of detail, cadence, devices and access — agreed in writing first.
requirementsdoc
02Metric dictionaryGovern
Formula, source, grain, exclusions, owner and expected refresh for every metric that matters.
metricdictionary
03Data connection and modelingConnect
Looker Studio connectors, BigQuery, spreadsheets, CRM and advertising APIs, or Power BI semantic models with Power Query and DAX.
modeledsources
04Report and dashboard designDesign
Page hierarchy, visual choices, filters, drill paths, mobile behavior and accessibility — prototyped before build.
pageprototypes
05Refresh, subscriptions and accessAutomate
Scheduled refresh, gateways, row-level security, subscriptions, alerts and permission sets per role.
refresh +access plan
06Validation and governanceOperate
Reconciliation against sources, change control, adoption review and a backlog of new decision requirements.
governanceregister
Platform choice
Choose the platform from data and governance needs
Neither tool is universally better. We recommend one after reviewing your data, your users and your governance requirements.
| Criterion | Looker Studio | Power BI |
|---|---|---|
| Best when | Marketing reporting centred on Google data and fast iteration. | Microsoft environments and broader enterprise reporting needs. |
| Data layer | Connectors, blends and BigQuery for modelled data. | Semantic models built with Power Query and DAX. |
| Governance | Report-level control; discipline comes from the metric dictionary. | Workspaces, semantic models and row-level security. |
| Refresh | Connector-dependent, with cached extracts where needed. | Scheduled refresh, gateways for on-premise sources. |
| Sharing | Link-based sharing and scheduled email delivery. | Licensed workspaces, apps and report subscriptions. |
| Watch out for | Chart-level formulas that quietly become the data model. | License and capacity cost, plus model ownership skills. |
// Licenses, gateways, premium capacity and paid connectors are quoted by their providers, not by us.
Delivery process
How a reporting build is delivered
Seven stages. Business definitions, data design, implementation, testing, documentation and ownership stay explicit at each one.
01DefineIdentify users and decisions
Document the questions, metric hierarchy, filters, cadence, detail and distribution requirements.
requirements signed off02AuditReview sources and quality
Assess identifiers, grain, history, freshness, credentials, APIs and reconciliation feasibility.
source assessment03ModelCreate reusable metrics
Build transformations, joins, calculated fields or semantic models with documented ownership.
metric model04DesignCreate the reporting experience
Prototype page hierarchy, visuals, filters, drill paths, mobile behavior and accessibility.
approved prototype05ValidateReconcile and test permissions
Compare source totals, edge cases, refresh, access, exports and load performance.
reconciliation log06LaunchTrain users and document governance
Provide definitions, ownership, the update process and a support boundary everyone understands.
handover pack07OperateMaintain and improve
Monitor freshness, source changes, adoption and new decision requirements as they appear.
operating cadenceWhat separates the work
One decision per chart
Dashboards fail by addition: every stakeholder adds a metric until the screen reports everything and informs nothing. Our build rule is that each chart must answer a decision someone actually makes — budget allocation, channel scaling, lead follow-up speed — and anything that answers no decision goes in an appendix, or nowhere.
Executive views get pipeline and efficiency; channel operators get diagnostic depth; nobody gets forty tiles of unprioritised numbers. The measure of success is boring and observable: whether people open it weekly without being asked.
Measurement
How we judge whether the reporting works
Five areas to evaluate, then four delivery controls that must be true before sign-off. Controls, not performance guarantees.
Trustreconciled
Reconciliation, metric consistency, freshness and documented limitations.
Adoptionopens
Active viewers, subscriptions, use in meetings and fewer manual report requests.
Decision speedtime to act
Time from a performance change to a responsible action being taken.
Maintainabilityreuse
Reusable metrics, clear ownership and less chart-level duplication.
Performancereliability
Load time, refresh reliability, connector errors and source cost.
Quality controls · signed off before launch
Metric definition
Every KPI has one documented formula, source, grain and exclusion rule.
Source reconciliation
Dashboard totals are compared with source systems before sign-off.
Refresh and access
Credentials, gateways, API limits, row-level access and failure ownership are explicit.
Role-specific design
Executives receive direction and exceptions; operators receive diagnostic depth.
Client fit
When a dashboard earns its screen time
We would rather name a constraint before a proposal than build a report that quietly stops being opened.
Strong fit when
- 01Several teams currently rebuild the same reports by hand
- 02Metric definitions and source ownership can be standardised
- 03Executives and channel teams need different levels of detail
- 04The organization will assign owners for credentials, refresh and governance
Poor fit when
- 01You want all available metrics on one page
- 02Source data is known to be wrong and cannot be repaired
- 03No one will own dashboard access and ongoing changes
- 04The dashboard is expected to replace discussion, analysis and judgement
Engagement model
Pricing follows data modeling, source count, access and reporting depth
We scope sources, connectors, transformations, historical data, pages, roles, filters, semantic models, row-level permissions, refresh, subscriptions and ongoing commentary. Tool licenses and paid connectors remain separate.
01
fixed projectExecutive marketing scorecard
One governed page for leadership: outcome, variance, efficiency and the exceptions that need a decision.
- └1 page, 3 tiers
- └metric dictionary
- └monthly cadence
- └exception alerts
02
phased buildLooker Studio dashboard
Connected marketing reporting on Google-centred data, with calculated fields, blends and documented refresh.
- └connectors + blends
- └role-specific pages
- └filters + drill paths
- └refresh documented
03
phased buildPower BI marketing and sales report
Semantic model, reports and workspace governance for Microsoft environments and broader enterprise reporting.
- └semantic model
- └Power Query + DAX
- └row-level security
- └gateway + refresh
04
project + retainerAutomated client reporting system
Templated, multi-account reporting with scheduled delivery — for teams reporting to many stakeholders.
- └template per account
- └scheduled delivery
- └commentary workflow
- └QA before send
05
retainerOngoing dashboard and reporting support
The reporting estate maintained: refresh monitoring, change requests, new pages and adoption review.
- └refresh monitoring
- └change requests
- └new decision views
- └quarterly adoption review
You receive a tailored US-dollar proposal with deliverables, responsibilities, milestones, assumptions and support boundaries — plus which pages we would build first if the budget has to be staged.
Request a scopeProof before proposal
Evidence you can review before you sign
We do not publish invented case studies or anonymous performance claims. In discovery we show the structure of the work and agree what proof is relevant.
dashboard-wireframe.pdfanonymized
Dashboard wireframe exampleAn anonymized layout showing how outcomes, drivers and diagnostics are separated for faster reading.
- └three-tier hierarchy
- └filter + drill design
- └mobile behavior noted
metric-dictionary.xlsxanonymized
Metric dictionary exampleHow every important measure is defined, sourced, calculated and owned before any chart is built.
- └formula + grain
- └exclusions per metric
- └named owner
data-flow-refresh.pdfanonymized
Data-flow and refresh mapHow source credentials, connectors, refresh schedules, failures and access are documented.
- └source → model → page
- └refresh schedule
- └failure owner + alert
Platforms and tools
The stack behind our reporting work
Major, verifiable platforms only — configured in accounts you own, documented so your team can run them.
// All properties, workspaces and data remain under client ownership.
Google Looker StudioReport design, connectors, calculated fields and blends.dashboard layer
Google Analytics 4Web and campaign source data, implemented on our GA4 service.web + campaign
Google BigQueryBlended and modelled data where blends alone cannot be trusted.modeling
Google SheetsControlled manual inputs — budgets, targets, annotations.manual inputs
Microsoft ExcelFinance-side exports and reconciliation against the ledger.reconciliation
Frequently asked questions
Ask a questionQuestions buyers ask about dashboards
01What should a marketing dashboard include?
It should include commercial outcomes, leading drivers, diagnostic metrics, definitions, filters and enough detail for the intended user to decide what to do next.
02Do you build Looker Studio dashboards?
Yes. We can connect supported data sources, create calculated fields and blends, design reports and document ownership and refresh.
03Do you provide Power BI dashboards?
Yes. Work can include semantic models, reports, dashboards, workspaces, refresh and permissions.
04Can you combine advertising and CRM data?
Yes, when common identifiers, campaign taxonomy and appropriate data access exist. The design will document attribution and reconciliation limitations.
05How do you prevent different reports showing different numbers?
We establish a metric dictionary, source hierarchy, transformation logic, refresh rules and ownership before visual design.
06Can reports be emailed automatically?
Depending on the platform, we can configure subscriptions, scheduled exports, alerts or workflow-based delivery.
07Will the dashboard update in real time?
Refresh depends on each data source, connector, license and business requirement. Real-time reporting is not always necessary or economical.
08How much do marketing dashboard services cost?
Pricing depends on the number of data sources, data modeling, connectors, dashboard pages, user roles, refresh requirements and whether ongoing reporting commentary is included.
09Should we use Looker Studio or Power BI?
Looker Studio is often efficient for Google-centered marketing reporting. Power BI can be a better fit for Microsoft environments, governed semantic models and broader enterprise reporting. We recommend the platform after reviewing data, users and governance.
10Can you combine marketing, CRM and sales data?
Yes, when the sources have compatible identifiers, definitions and access. We document where data cannot be joined reliably instead of forcing misleading blends.
Why Digital Otters
Why US companies choose us for dashboards
We combine commercial strategy, platform implementation and measurement without taking ownership of your accounts or your data.
FocusOne decision per view
We remove decorative reporting and make the next action obvious to the person reading it.
TrustGoverned numbers
Metrics are reconciled against their sources before they are presented as a shared source of truth.
LongevityBuilt to be maintained
Credentials, refresh, ownership, calculated fields and change control are documented for your team.
// Methodology reviewed against current official platform and search documentation on August 4, 2026.
Replace reporting debates with one governed decision view
Share the current reports, data sources, users and decisions. We will recommend the dashboard, the model and the refresh approach — and say which page to build first.
Digital OttersIn the reply
Which reports we would retire immediatelyThe page hierarchy we would build firstWhat has to be fixed upstream before we buildA US-dollar range with assumptions written down