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Data Analysis Patterns for Market Research

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Data Analysis Patterns for Market Research

Measurement contract

Define the quantity before collecting numbers:

  • product/service inclusion and exclusion;
  • buyer, user, payer, and transaction type;
  • geography and treatment of imports/exports;
  • historical period, forecast horizon, and as-of date;
  • revenue, expenditure, gross output, value added, units, capacity, users, or another measure;
  • stock versus flow;
  • gross versus net, taxes included/excluded, and channel level;
  • currency, exchange-rate convention, base year, and nominal/real basis;
  • industry and product taxonomy with version;
  • denominator ID used in every share or rate.

If two estimates do not share this contract, they are not directly comparable.

TAM, SAM, and SOM

Treat all three as conditional scenario constructs.

Definitions

  • TAM: value or volume of all in-scope demand under the stated market definition and time basis.
  • SAM: subset of TAM serviceable under explicit product, geography, regulatory, channel, capacity, and customer constraints.
  • SOM: subset of SAM obtainable within a stated time horizon under explicit competitive, operational, sales, retention, and capacity assumptions.

Never present SOM as a guaranteed share or TAM as an objective universal truth.

Top-down method

Use disjoint components:

text
TAM_top = sum(value_i * in_scope_fraction_i)

Each component needs a unique coverage key, source IDs, period, unit, and denominator. Do not apply a broad percentage to an unrelated aggregate merely because the resulting number looks plausible.

Bottom-up method

For a recurring-use market:

text
component_i =
    customer_count_i
  * addressable_fraction_i
  * annual_quantity_per_customer_i
  * price_per_unit_i

TAM_bottom = sum(component_i)

Alternative physical-capacity models may use installed base, utilization, replacement cycle, throughput, or transactions. Keep dimensions explicit so the resulting unit can be checked.

SAM and SOM

text
SAM_s = TAM * serviceable_fraction_s
SOM_s = SAM_s * obtainable_share_s

The fractions belong to scenario s. At minimum, use distinct downside and upside cases; a base case is usually useful. For each case, list assumptions, evidence, constraints, and horizon. Do not assign probabilities without a validated probabilistic model.

Preventing double counting

Common failures:

  • adding manufacturer revenue to distributor or end-customer spend;
  • adding domestic production, imports, and sales without subtracting exports, inventories, or overlapping channels;
  • summing parent and subsidiary revenue;
  • adding product bundles and their included components;
  • combining gross output and value added;
  • counting the same establishment in multiple segment labels;
  • adding annual transactions to installed-base stock;
  • applying overlapping geography or customer filters independently.

Controls:

  1. assign a unique coverage key to every component;
  2. use mutually exclusive, collectively understood segments;
  3. define a single denominator ID;
  4. draw money and product flows through the value chain;
  5. reconcile supply, use, trade, inventory, and channel margins;
  6. show an ``unallocated/unknown'' residual rather than forcing totals;
  7. test the sum against an independent control total.

Supply-use tables distinguish products from industries and the origin/use of goods and services. Use the OECD Supply and Use Tables and national accounts methodology when the value chain spans intermediate and final demand.

Reconciliation

Keep methods separate:

text
absolute_gap = abs(TAM_top - TAM_bottom)
midpoint = (TAM_top + TAM_bottom) / 2
gap_percent = absolute_gap / midpoint

Investigate gaps in this order:

  1. definition and denominator;
  2. geography, period, currency, and price basis;
  3. taxonomy and segment concordance;
  4. gross/net, taxes, channel margins, imports/exports;
  5. missing or duplicate coverage;
  6. source revision and sample limitations;
  7. price, volume, penetration, and utilization assumptions.

Do not average the methods until their scopes are demonstrably compatible. If uncertainty remains, report both or retain a range.

Growth and forecasts

Historical growth

text
YoY_t = value_t / value_(t-1) - 1
CAGR = (end / start)^(1 / periods) - 1

CAGR compresses the path. Always show start/end values and period count. It is undefined when the start is nonpositive and can hide volatility, breaks, and revisions.

Scenario forecast

text
value_(t+1,s) = value_(t,s) * (1 + growth_rate_(t,s))

Build rate paths from named drivers rather than copying a paid headline forecast. Separate:

  • historical observed period;
  • nowcast or estimate period;
  • conditional forecast period.

For each scenario, state demand, price, supply, regulation, competition, capacity, and timing assumptions. Use different paths, not merely different labels.

Sensitivity

One-way sensitivity varies one input while holding others fixed. Report:

  • tested range and rationale;
  • resulting endpoints;
  • switching value where the decision changes;
  • nonlinearities or constraints;
  • interactions omitted by one-way analysis.

Scenario analysis explores coherent joint states. It is not a confidence interval. Statistical prediction intervals require a specified model, error process, diagnostics, and coverage interpretation.

The 2023 OMB Circular A-4 provides primary guidance on characterizing uncertainty, sensitivity, and transparent assumptions. The UK Green Book 2026 provides additional public-sector appraisal guidance. Adapt principles proportionately; do not imply that a market report is a regulatory appraisal.

Units, currencies, and price bases

Nominal and real

  • Nominal/current-price values reflect prices in each period.
  • Real/constant-price values remove price change using an identified deflator and base/reference year.
  • Never combine nominal and real values in one total or growth rate.
  • Match nominal values to nominal assumptions and real values to real assumptions.

Record:

text
real_value_base_year = nominal_value_t * price_index_base / price_index_t

Identify the index, geography, category, vintage, and whether it is appropriate for the market. A broad CPI may be unsuitable for a specialized B2B input.

Chained measures

Chained-dollar components may not add to published aggregates. BEA's chained-dollar guidance explains why. Use published contributions to growth or current-dollar composition rather than forcing additivity.

Currency conversion

Record:

  • source and target currency;
  • spot, period-average, or period-end convention;
  • rate date/period and source;
  • order of currency conversion and deflation;
  • effects of high inflation or multiple exchange-rate regimes.

Do not mix converted flows using period-end rates with balances using averages without explanation.

Stock and flow

A stock is measured at a point in time; a flow over an interval. Installed base, employees on a date, and capacity are stocks. Revenue, transactions, and shipments during a year are flows. A stock-to-flow conversion requires an explicit turnover, utilization, or replacement-cycle assumption.

Shares and concentration

text
share_i = in_scope_measure_i / same_scope_total
HHI = sum((100 * share_i)^2)
CR4 = sum(four_largest_shares)

Before computing:

  • define product and geographic scope;
  • use one share metric and denominator;
  • include the same period and channel level;
  • account for unknown/residual firms;
  • disclose whether values are revenue, units, capacity, or active users;
  • avoid false precision when company and total estimates use different methods.

The 2023 U.S. Merger Guidelines describe HHI as one indicator in case-specific merger analysis. The 2024 EU Market Definition Notice addresses product/geographic scope, non-price parameters, dynamic and digital markets, alternate share metrics, and evidence. A market report's HHI is descriptive and is not a legal conclusion.

Survey and interview synthesis

Survey estimate

For a probability sample, report the design-based or model-based estimator, weights, design effect, and appropriate uncertainty. Do not infer population precision from sample size alone.

For a non-probability sample, disclose recruitment and model assumptions. Use careful labels such as ``among respondents'' unless a validated adjustment supports broader inference.

Interview themes

Use a structured coding frame:

text
theme_id | definition | inclusion rule | exclusion rule |
supporting excerpts | disconfirming excerpts | roles represented

Report a theme as qualitative evidence. Do not translate mention counts into market prevalence.

Confidence labels

Confidence is an analyst assessment, not a substitute for uncertainty:

  • High: directly observed, well-defined primary evidence with compatible scope and low material revision risk.
  • Medium: triangulated evidence with manageable assumptions or limitations.
  • Low: sparse, conflicting, indirect, modeled, or scope-mismatched evidence.
  • Not assessed: opinion or recommendation where an evidence-confidence label is inappropriate.

Always state the reasons. Multiple low-quality sources do not automatically produce high confidence.