VikaSquareTalk to us
Menu
Services

Business analysis

Make a clearer decision with the evidence you have.

Scope a public-source competitor comparison, a descriptive dashboard or a separate forecasting feasibility review around a specific business question.

Discuss what you need ↗
Illustration comparing recorded observations with an estimate and uncertainty, without measured values
Illustrative analysis · no measured business results

Frame an analysis around a decision

DecisionName what the work should help decide
Public comparisonCompare a defined set of offers
DashboardTrack measures that support a decision
Forecast checkTest whether records support a prediction

Each route needs relevant evidence, clear assumptions and a named reviewer.

START WITH A DECISION

What do you need to understand?

The work begins with a question, the people who will use the answer and the evidence available. A short, agreed scope sets the geography, comparison set or data sources, period and review steps before analysis starts.

A scope we can review

Keep each kind of analysis clear.

Compare a defined set of competitors

We agree which businesses and geography to include, then review dated public sources such as their published service pages, product descriptions and customer-facing journeys. The comparison can cover stated offers, product or service scope, and visible steps from first contact to purchase or enquiry. It is a bounded sample, not an exhaustive view of a market.

Separate observations from interpretation

Notes identify what a source directly says or shows, what may follow from that evidence, and what remains unknown. Public pages do not reveal every price, customer experience, sales result or internal process. We do not infer market share, demand, rankings or performance from a small comparison.

Describe activity with a dashboard

A descriptive dashboard summarises agreed measures in supplied records, such as activity over time or the status of work. We first define each measure, its source, reporting period and known data-quality limits. A dashboard describes the records it receives; it does not by itself explain causes or predict what will happen.

Assess machine learning and forecasting feasibility

A forecast needs a defined outcome to estimate, suitable historical data and a way to check predictions against data not used to fit the model. A feasibility review can examine data coverage, consistency, time span, important changes and a sensible evaluation approach. If the evidence is not suitable, the result may be a recommendation not to forecast. Feasibility is not a forecast or a promise of accuracy.

WHAT TO AGREE FIRST

Boundaries, sources and review.

For competitor work, agree the geography, named comparison set, public source types and observation dates. For reporting or forecasting, agree the business question, outcome or measure, date range, data owner and review contact. The agreed scope records exclusions and unresolved questions as well.

WHAT YOU CAN PROVIDE

Context and permission to use the evidence.

Share the decision to make, relevant business context and any customer-owned records needed for the work. Data should be supplied through an agreed, appropriate channel; do not send credentials or sensitive records in an initial enquiry. We confirm access, permitted use, definitions and review responsibilities before working with customer data.

DELIVERABLES

Useful working material, with its limits attached.

Depending on the agreed scope, outputs may include a dated source log, comparison table, dashboard specification or view, data-quality notes, and a written summary of observations, inferences, unknowns and next questions. You review factual context and definitions before the findings are treated as decision input. The work supports a decision; it cannot guarantee a business result.

PUBLIC SOURCES

Use sources within their stated terms.

Competitor research uses accessible public material and records where and when it was observed. It does not involve private accounts, access controls, personal data collection or scraping content where the source or applicable terms do not permit it. Sources can change, be incomplete or describe an offer differently from how it is delivered.

DATA AND PREDICTION

Evidence sets the limit.

Reporting depends on accurate definitions and supplied records. Gaps, inconsistent entry, small samples or changes in how a business operates can make a measure misleading. Forecast feasibility depends on the outcome, data volume and quality, relevant history and a fair evaluation design. Neither a chart nor a model proves that an action caused a result.

Start with the question you need answered.

We can discuss the evidence, scope and review needed to make the work useful.

Talk to VikaSquare ↗
WhatsApp