The evidence behind better decisions.
Original African consumer data. Historical perspective. Intelligence built for action.
Africa's markets are changing. Consumer expectations, financial pressures and purchasing behaviour are evolving in ways that conventional economic statistics and corporate data do not always fully capture.
For organisations making important decisions, understanding these changes requires more than public information or occasional market surveys.
Kasi continuously develops proprietary African consumer intelligence, connecting original observations across markets, time and consumer groups.
Our evidence helps organisations understand what is changing, investigate why it matters and make more informed decisions.
Who generates the evidence?
Artificial intelligence has transformed how organisations find, process and communicate information.
It can summarise research, analyse datasets, generate charts and identify patterns at remarkable speed.
But faster analysis does not automatically mean better evidence.
When the underlying information is incomplete, outdated or unavailable, AI cannot reliably fill the gap simply by generating a more convincing answer.
Kasi starts with original evidence.
We continuously collect and organise proprietary consumer observations across African markets.
We combine that evidence with applied AI, analytical methods and experienced researchers to produce intelligence grounded in actual consumer responses.
AI accelerates what we can do with evidence. Kasi invests in creating and maintaining the evidence itself.
The future of decision intelligence is not AI versus research. It is original data, intelligent technology and accountable human judgment working together.
Built over time. Developed across markets. Designed to support analysis.
- African markets
- 20
- Market coverage across Africa's largest consumer economies.
- Consumer datasets
- 500
- Consumer, financial, retail, brand and thematic intelligence.
- Data points
- 100M
- Accumulated observations and responses across Kasi research programmes.
- Interviews a year
- 120,000
- Continuing primary data collection supporting Kasi intelligence programmes.
- Historical series for selected indicators
- 7+ years
- Supporting longitudinal analysis where definitions and methods are sufficiently comparable.
These figures describe Kasi's broader intelligence assets. Coverage, historical depth and update frequency differ across datasets and countries.
Measure what is changing.
Kasi continuously measures consumers, markets and economic conditions to identify the signals that matter to decision-makers.
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Kasi Consumer Confidence Index
A monthly read on how African consumers feel about their finances, job security and spending intentions across 20 markets.
+4.8Expansion
Africa-wide composite
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Retail Demand
Category-level demand momentum for FMCG and retail, drawn from point-of-purchase and consumer panel data.
Improving
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Financial Wellbeing
Household financial pressure: savings, debt stress and discretionary capacity.
Under pressure
Household level
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Purchase Intent
Intent-to-purchase signals ahead of spend, segmented by category and income band.
Stable
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Consumer Basket Index
The cost and composition of a representative household goods basket across markets.
112.4+1.7 pts
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Other trackers
Further trackers are in development.
Ask about the tracker roadmap
How Signals are built
Signals are built from continuous primary data collection across Kasi's research infrastructure in 20 African markets, combined with external economic data and, where relevant, client data. Each signal is trended monthly to show the direction of travel.
Methodology and market coverage are available on request.
Read Our MethodologyUnderstand consumers beyond traditional demographics.
Consumer Confidence & Expectations
How are consumers feeling about their economic prospects? Are expectations improving or deteriorating? Which groups are experiencing the greatest changes?
Applications: Economic monitoring, strategic planning and consumer sentiment analysis.
Cost of Living & Household Pressure
How are households experiencing affordability challenges? Which financial pressures are most widely reported? How are these changing over time?
Applications: Consumer resilience, affordability analysis and market planning.
Financial Behaviour & Financial Freedom
How do consumers approach saving, borrowing, investing and financial security? Where do needs and behaviours differ across groups?
Applications: Banking strategy, product development and financial-sector research.
Consumer Basket & Retail Demand
What are consumers purchasing? How do category patterns differ? Where are consumer demand signals strengthening or weakening?
Applications: FMCG strategy, category planning and retail intelligence.
Share of Wallet
How are households allocating spending across needs and priorities? What trade-offs emerge under financial pressure?
Applications: Consumption analysis, product strategy and consumer segmentation.
Banking & Brand Intelligence
How do consumers perceive financial institutions and brands? Which factors influence consideration, preference and customer experience?
Applications: Competitive positioning, customer strategy and brand intelligence.
Thematic & Emerging Consumer Issues
How do consumers respond to emerging technologies, sustainability, media, social issues and changing market conditions?
Applications: Innovation, scenario planning and strategic research.
See which markets and channels actually exist.
Kasi maps physical markets through on-the-ground collection, geo-tagged evidence, GIS and data science.
The aim is to reveal which markets and channels actually exist, so decisions rest on ground reality rather than assumptions.
Discuss Ground-Market Intelligence- Retail census and outlet-universe development
- Outlet mapping and cooler and asset verification
- Trade-visibility audits and distribution intelligence
- Out-of-home advertising verification and geo-intelligence
- White-space analysis
Credible intelligence begins with understanding where the evidence comes from.
Kasi uses structured primary consumer data collection across selected African urban markets.
For relevant survey programmes, respondents are recruited through businesses and recruitment locations strategically selected to reach consumers with different socioeconomic backgrounds and lifestyles.
Demographic quotas, including age, gender and income, are used to manage the composition of participating respondents.
Some respondents may participate in more than one survey wave.
Our data lifecycle
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01
Recruitment
Identify recruitment locations and eligible participants according to the applicable study design.
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02
Quota management
Monitor participation against specified demographic and market quotas.
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03
Data quality review
Apply the fieldwork checks, validation procedures and review processes defined for the survey programme.
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04
Indicator development
Organise observations, calculate relevant indicators and document definitions and coverage.
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05
Analysis and interpretation
Examine trends, segments and comparisons, while accounting for data limitations.
Understanding the sampling approach
Kasi's relevant consumer survey programmes use structured nonprobability sampling rather than random selection from a complete population sampling frame.
Consequently, conventional probability-sample margins of error and confidence intervals should not automatically be attached to these results.
Quotas help manage sample composition but do not eliminate selection bias or guarantee population representativeness.
Findings are interpreted in light of their recruitment design, sample composition, question wording, geographic coverage and historical comparability.
Transparency is part of responsible intelligence.
Read Our MethodologySerious analysis requires more than a large dataset.
Institutional users need to know what an indicator measures, how it was produced and whether it is suitable for their intended application.
Kasi's documentation framework addresses:
- Indicator definitions and calculation methods
- Country and geographic coverage
- Collection periods and update frequencies
- Respondent recruitment and quota design
- Available weighting information
- Data validation and quality-control procedures
- Questionnaire and methodological changes
- Historical comparability and known limitations
- Appropriate interpretation and permitted analytical use
Historical continuity matters.
A long series is valuable only when analysts understand whether observations remain comparable across time. Material changes in survey questions, respondent composition, geographic coverage or calculation methods can affect interpretation.
Kasi identifies relevant methodological changes in applicable technical documentation and advises users to assess their implications before comparing periods or building models.
Responsible analytical use
Consumer indicators can provide useful signals, but they do not automatically establish causation, predict economic outcomes or guarantee commercial performance.
For forecasting, investment and credit-risk applications, institutions should independently validate relationships against relevant observed outcomes.
Consumer intelligence that complements conventional economic and financial data.
Economists
Incorporate consumer sentiment and financial pressure indicators into economic research and monitoring.
Banks & Risk Teams
Investigate whether consumer financial behaviour contributes useful information to internal risk analysis.
Asset Managers & Investors
Evaluate consumer indicators as potential inputs to investment research, historical backtesting and economic regime analysis.
Corporate Strategy Teams
Connect external consumer developments to market planning, product priorities and internal performance analysis.
Universities & Research Institutions
Study African consumer behaviour using licensed historical and thematic data.
Kasi consumer intelligence has been distributed through established financial information channels, including Bloomberg-related initiatives and Refinitiv Eikon. Specific data availability, distribution arrangements and usage rights vary by platform and product.
Different ways to work with the same evidence base.
- Intelligence Reports Purchase ready-made market and consumer analysis.
- Rapid Insights Get tailored answers to specific business questions using existing Kasi data.
- Intelligence Office Access ongoing analyst-led intelligence support.
- DataHub License proprietary datasets for approved institutional applications.
- Strategic Research Commission new evidence when existing data cannot adequately answer your question.
What intelligence is missing from your next decision?
You may need a historical indicator, a tailored analysis, a licensed dataset or a new research programme.
Start with the business question.