RESEARCH SUPPORT
Applied Business Statistics Support
Documented Methods Behind Decisions
For research teams in companies and agencies: customer surveys, controlled experiments and forecasts analyzed with documented methods, stated assumptions and results that a decision-maker can rely on and an auditor can reproduce.
No Commitment Required
Strictly Confidential
In-House PhD-Level Statisticians
Fixed Project Fee
Same-Day Response
What Does Formal Research Support for a Business Team Involve?
Applied business statistics applies formal research methods to questions that an organization must decide: what customers prefer, whether a change worked and what demand is likely to be. It covers the design of surveys and experiments, the analysis of the resulting data with models that suit the design, forecasting with an honest account of its uncertainty, and documentation that lets another analyst reproduce every figure. OnlineSPSS, a specialist statistical consultancy for academic, clinical and professional research, supports research and insights teams, consultants and analysts in industry: an in-house PhD-level statistician carries out the agreed analysis on your data and records the methods used. The decision the results inform, and how they are presented inside the organization, stay with your team.
WHEN TO ENGAGE
When Business Teams Bring in a Statistician
Teams usually seek formal analysis when a decision carries cost and the evidence must withstand scrutiny.
Study Before Launch A survey, pilot or experiment is being planned, and the sample size, the sampling or randomization approach and the primary metric must be set while they can still be changed.
Results Needing Rigor A test or survey has finished, and the team needs an analysis that separates a real difference from noise, handles many metrics and reports effect sizes with intervals.
Forecast to Build or Review Demand, sales or cost is to be forecast, and the model must be validated on later periods and its uncertainty communicated to the people who plan with it.
Board or Client Scrutiny A leadership team, regulator or client has questioned a figure or a method, and the analysis must be documented and reproducible to stand up to the challenge.
WHAT THE SUPPORT COVERS
Statistical Components of Business Research We Support
The work covers the whole path from a study design to a leadership summary, and formal methods change the answer at each of these stages.
Survey Design and Analysis
Customer, employee and market surveys are designed and analyzed with attention to sampling, nonresponse and weighting, in the manner of Marketing research.
Experiments and A/B Tests
Controlled experiments are analyzed with a prespecified metric, an effect size with its interval and a stated rule for when the test ends, as in Business Analytics projects.
Forecasting
Demand and sales forecasts are built with Time Series Analysis, validated on later held-out periods and reported with prediction intervals.
Customer and Market Models
Drivers of satisfaction, churn or purchase are modeled through Quantitative Data Analysis, with the limits of observational customer data stated.
Pilots and Small Samples
Industry research analysis often rests on pilots, quality studies and benchmarks with small samples, so uncertainty is reported and a decision is not made on a noisy difference.
Documented Reporting
Methods and results are written for a technical appendix and a leadership summary, and work that will also be published follows the reporting conventions of Business, Management & Economics research.
COMMON ISSUES
Why Business Analyses Mislead Decision-Makers
Unreliable figures in a leadership meeting usually trace back to a few avoidable errors, and these six are the ones most worth preventing.
Peeking at Test Results An experiment is stopped the first time the metric looks significant, which can push the false-positive rate well above the level the test was designed for.
Respondents as Customers A survey of customers who responded is taken to describe all customers, when responders often differ from nonresponders in ways that matter for the question.
Outliers Drive the Mean Revenue per customer is often highly skewed, so a few large accounts can drive the mean, and a comparison of means can mislead without a robust summary or a suitable model.
Forecast Fit Mistaken for Skill A model that fits past sales closely is trusted, though only its accuracy on later periods it has not seen shows whether it can forecast.
Significant Read as Valuable A statistically significant lift is reported without its size or interval, so the team cannot tell whether the effect is worth the cost of acting on it.
Campaign Credited With the Sales A link between a campaign and sales in observational data is reported as the campaign's return, without ruling out seasonality or customers who were already likely to buy.
DELIVERABLES
What You Receive for Your Business Analysis
Each item is built so that an analyst, an auditor or a client can check a reported figure against its source without asking how it was made.
Test or Survey Protocol A short protocol stating the question, primary metric, sample size, sampling or randomization approach and planned analysis, written before the data arrive.
Cleaned Dataset With Dictionary A cleaned dataset with a data dictionary, the rules for exclusions and duplicates and a log of every transformation applied to the raw file.
Lift and Difference Tables Differences, ratios or lifts for each metric with 95% confidence intervals, so that the size of an effect and its uncertainty are both visible.
Forecast Package Forecasts with prediction intervals, accuracy measured on held-out periods and a statement of the assumptions that would make them unreliable.
Summary and Technical Appendix A short summary for decision-makers and a technical appendix of methods and checks, written to the format your organization uses.
Reproducible Scripts Scripts and output that rerun the analysis from the source data, so that the figures in a report can be regenerated on request.
ILLUSTRATIVE EXAMPLE
Testing a New Onboarding Flow
An illustration of how a controlled test in a company is analyzed when several metrics and a few large accounts complicate the result.
ILLUSTRATIVE EXAMPLE · SUBSCRIPTION SERVICE CUSTOMER RESEARCH · UNITED STATES
The research team of a subscription software company wanted to know whether a redesigned onboarding flow increased the share of new customers who were still active after 30 days.
Customers were randomly assigned to the old or the new flow, so the plan fixed the primary metric, the sample size and the end date in advance. Two things complicated the result: the team also wished to inspect several secondary metrics and customer segments, and a few large accounts distorted the revenue averages. The primary comparison was reported as a difference in retention with its confidence interval, the secondary metrics were labeled exploratory or adjusted for multiplicity, and revenue was summarized by a method that did not hinge on a handful of accounts. The summary for leadership stated what the test could and could not show about longer-term retention.
Outcome: The team received the difference in 30-day retention with its 95% confidence interval, the secondary metric tables, the technical appendix, the summary for leadership and the scripts.
This example does not describe a real client or project. We never share details of actual client work, in line with the confidentiality we promise every researcher. This illustrative example is included to show the type, scope, and standard of work involved in this kind of analysis.
SOFTWARE
Tools Your Analysts Can Rerun
The work is done in the language your analysts already use, so that scripts can be versioned, reviewed and rerun when new data arrive.
HOW WE ASSESS YOUR PROJECT
We Review Your Actual Research
Your assessment is based on a review of your actual research materials and analytical requirements, not a generic project category.
You Submit Your Project Details
Share whatever is available at the current stage, such as the research aim, protocol or proposal, dataset, variable list, manuscript or statistical requirements.
We Review Your Research and Define the Scope
Your statistically trained Research Coordinator reviews the materials to understand the study design, research questions, data structure, analytical requirements and expected deliverables. If clarification is needed, additional documents or information can be requested before the assessment is finalized.
Your Analysis Is Completed and Delivered
Once the scope and fixed project fee are agreed, the in-house statistician completes the work and the Research Coordinator remains the communication point through delivery, with the analysis, deliverables and timeline as agreed.
RESEARCH RESPONSIBILITY
Statistical Support Within Your Own Business Research
OnlineSPSS supplies the analysis and its documentation; the business judgment, the recommendation and the decision itself belong to your team.
Agreed Statistical Support OnlineSPSS provides the agreed methodological, analytical and statistical reporting support, defined in a scope that is confirmed before any work begins.
No Intellectual Contribution OnlineSPSS does not claim any intellectual contribution to your research. Authorship of the report or paper remains yours.
Your Research Decisions The business question, the interpretation, the recommendations and the decisions based on the results remain yours, with overall responsibility.
Confidential Handling Research data and project details are handled confidentially, project information is not published, and an NDA is available where required.
FREQUENTLY ASKED QUESTIONS
Questions From Company Research Teams
How long a test should run, how a forecast is judged and what a drivers model can show are the usual questions from research and insights teams.
What does applied business statistics support cover?
Applied business statistics support for an industry research team covers the design and analysis of surveys and experiments, forecasting with prediction intervals, models of customer and market data and documentation that lets every figure be reproduced. It suits teams whose findings must stand up to leadership, clients or auditors.
How long should an A/B test run?
Long enough to reach the sample size set in advance, and across whole weekly cycles where behavior differs by day. Stopping when the result first looks significant inflates false positives. If early stopping is needed for business reasons, a sequential design with adjusted boundaries allows it.
Is a forecast better judged by its fit or its accuracy?
By its accuracy on later periods that the model has not seen. A model can fit past data closely by capturing noise. Out-of-sample error measures, a comparison with a simple benchmark and prediction intervals show whether the forecast is useful for planning.
Can a churn or satisfaction drivers model show what to change?
It shows which factors move together with churn or satisfaction in your data, not what would happen if one were changed. Drivers that can be tested at low effort are best confirmed in a controlled experiment, and the model’s results are reported as associations, with the customers and period they describe stated.
How do you protect my research data and confidentiality?
Your data and project details are handled confidentially, and project information is not published. Researcher names and institutions are not used publicly without permission. An NDA is available where required and can be arranged before sensitive materials are shared. Read more about confidentiality and data security.
What happens when I request an assessment, and how long does it take?
You share your research question, design and relevant materials, such as a research brief, a survey or test design or a dataset, and a statistically trained Research Coordinator reviews the request and responds the same day. The analysis, deliverables, timeline and one fixed project fee are then confirmed before any work begins, so the timeline follows from the agreed scope.
Still have a question? Find more answers in our full FAQ.
NEXT STEP
Ground Your
Next Business Decision
Describe the decision the research must inform and the data you hold or plan to collect, and we will propose a design and an analysis your team could defend to leadership.
No Commitment Required
Strictly Confidential
Fixed Project Fee
In-House PhD-Level Statisticians
Same-Day Response
Serving Researchers Since 2014