"RaftLabs elevated my ideas and brought them to life when everything seemed impossible."
Grady Lakshmono
CoFounder, Moka (acquired by Gojek) & Gula (acquired by Runchise)
Data Analytics Services for Business Decisions
Data analytics services for the decision your dashboard cannot settle.
A dashboard can show that churn rose or margin fell. A focused analysis tests why, checks alternative explanations, and gives the decision owner a reproducible answer. We scope one question first, work with the data that can support it, and state what the evidence cannot prove.
Bring the problem, the current workflow, or the existing code. We reply with a practical next step within one business day.
The brief
Start with what is not working.
Good software decisions begin with the constraint, not a list of features or a preferred technology.
01
Are leaders debating why a metric moved because the dashboard stops at what happened?
02
Is a product, pricing, or operating decision waiting behind an analysis backlog?
Plain answer
Data analytics services answer a specific business question using available data, such as why churn changed, where a funnel breaks, or whether an experiment moved the intended metric. RaftLabs scopes the decision first, validates the data, documents the method, and delivers a reproducible finding. Focused engagements start at $10000.
What to remember
- A focused engagement covering one or two related questions starts at $10000 and usually takes two to four weeks.
- The deliverable is a finding with a reproducible method and stated limits, not simply a collection of charts.
- Data engineering makes data dependable, business intelligence provides recurring dashboards, and analytics investigates a specific question about what happened or why.
- You receive the finding, the method, important limitations, reusable queries or transformation logic where applicable, and a recommendation tied to the original decision.
- Do not commission a focused analysis when the real need is a permanent dashboard, a forecast, or a production machine-learning model; those are scoped separately.
The dashboard was accurate. The decision was still a guess.
Churn rose in March. The weekly chart showed the change clearly, but it could not tell the team whether pricing, onboarding, seasonality, or one customer segment caused it. Each leader arrived with a different explanation.
A focused analysis should close that gap. The work starts with the decision, then tests what the available data can support.
Relevant product proof
- GrowViral product delivery
- 14 weeks
- Referral and campaign platform
- connected services
- 12+
- Recorded case-study scope
- campaign conversion result
- 2.5x
- Client-reported outcome
The GrowViral case study documents attribution and performance analytics inside a product RaftLabs delivered. We do not yet publish a case study for a standalone analysis engagement, and the client's conversion result is not a forecast for another business.
Use a focused analysis when one decision needs a defensible answer.
A question without an owner or a decision deadline usually becomes an interesting report that nobody uses.
A fit
A specific metric, segment, funnel, or experiment needs investigation.
The relevant records exist in accessible systems, files, or databases.
Someone is prepared to act differently if the evidence supports it.
Not a fit
The team needs a permanent dashboard or self-service reporting layer.
The underlying data is inaccessible or too incomplete to support the question.
The request is a forecast or production machine-learning model.
Data analytics vs business intelligence
Choose by the job the result must do
| Focused data analytics | Business intelligence | |
|---|---|---|
| Question | Why did this change, and what should the owner decide? | What is happening across agreed metrics each week? |
| Output | Finding, method, limits, and recommendation | Recurring dashboard, definitions, access, and refresh |
| Duration | Usually two to four weeks for a focused question | Built and maintained as an operating product |
| Route elsewhere when | The answer needs prediction or a permanent system | The source data first needs reliable pipelines |
Scope
Questions we investigate
- 01
Cohort and segmentation analysis
Compare how groups behave over time without letting a blended average hide the useful difference. - 02
Funnel and behaviour analysis
Trace where a defined journey breaks, then test whether the drop is associated with a segment, channel, device, or workflow change. - 03
Root-cause and variance investigation
Explain why margin, churn, conversion, fulfilment, or another agreed measure moved by testing plausible causes against the records. - 04
Experiment read-outs
Check whether an A/B test or operational change moved the intended measure, whether the sample supports the conclusion, and what the result does not establish. - 05
Analysis handoff
Turn a repeated, valuable question into a scoped reporting requirement only after the first investigation proves it deserves a permanent view.
How it works
From business question to defensible finding
- Phase 101
Define the decision
Name the question, owner, deadline, success measure, and evidence that would change the next decision.
- Phase 202
Validate the data
Locate the relevant sources, write the metric definitions, and test whether the records can support a responsible conclusion.
- Phase 303
Test explanations
Run the appropriate cohort, funnel, variance, root-cause, or experiment analysis and challenge the first plausible pattern.
- Phase 404
Hand over the finding
Deliver the result, method, limitations, reusable queries, and recommendation tied to the original decision.
Risk
How a clean chart reaches the wrong conclusion
- The metric changes halfway through
- Write the population, time window, exclusions, and calculation before testing explanations.
- A segment reverses the headline
- Inspect meaningful cohorts before trusting an overall average, especially when the customer mix has changed.
- Correlation is presented as cause
- Test alternative explanations and state when the available data supports association rather than causation.
- Missing records look like behaviour
- Profile source coverage and reconcile joins before treating an absence as a customer or operational event.
Scope and price
A focused data analysis starts at $10000.
Start with one decision, one or two related questions, the records needed to test them, and a reproducible handoff.
If the assessment shows that the real need is a pipeline, recurring dashboard, predictive model, or custom analytics product, we will scope that work separately.
Starting investment
Starts at $10000
A focused engagement usually takes two to four weeks. Multiple systems, weak identifiers, unclear definitions, or deeper experimental work can extend the plan.
Fixed scope
The question, sources, deliverable, and price are written down before analysis begins. New questions enter only through an approved change.
Evidence boundary
The handoff states what the data supports, what remains uncertain, and which decision the finding was designed to inform.
Proof
What clients say about working with RaftLabs
Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.
Work with us
Bring the question your current reporting cannot answer.
Share the decision, deadline, and systems that may hold the evidence. We will tell you whether the next step is analysis, better data plumbing, a dashboard, or no project at all.
- Scope and cost agreed before work starts. No surprises. No obligation.
- Working prototype within 3 weeks of kickoff.
- Pay by milestone. You see progress before each invoice.
- 60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
- All conversations are NDA-protected.
Common questions
Data analytics services investigate a defined business question with available data. Typical work includes cohort and segmentation analysis, funnel analysis, root-cause investigation, variance analysis, and experiment read-outs. The deliverable is a finding with a reproducible method and stated limits, not simply a collection of charts.
Data engineering makes data available and dependable. Business intelligence provides recurring dashboards and reporting. Data analytics investigates a specific question, usually about what happened or why. Predictive analytics estimates what may happen next. If the real need is a permanent product or pipeline, we route the work to that service.
A focused engagement covering one or two related questions starts at $10000 and usually takes two to four weeks. Deeper or recurring work can take four to eight weeks. Final scope depends on data access, source quality, metric ambiguity, and the number of explanations that need testing.
You receive the finding, the method used to reach it, important limitations, reusable queries or transformation logic where applicable, and a recommendation connected to the original decision. We define key metrics before analysis so another competent analyst can inspect or rerun the work.
RaftLabs does not yet publish a case study for a standalone analysis engagement. Our published GrowViral case shows attribution and performance analytics inside a product we delivered. That is relevant implementation proof, not evidence that every bounded analysis will produce the same commercial result.