A polished agency-style publication showing category movement, household pressure points, and practical implications from Dootsa survey data.
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https://dootsa.com/insights/dootsa-consumer-shift-q1-2026
Dootsa Research (A01). "Consumer Shift Report · Q1 2026." 10 May 2026. https://dootsa.com/insights/dootsa-consumer-shift-q1-2026
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The panel recorded 3 012 anonymised responses across 8 published survey families; Grocery led category attention at roughly 70%.
Confidence at publication: ±1.8% at 95% confidence (n=3 012)
This public report shows the market signal. A custom Dootsa survey can test brand recall, purchase intent, switching triggers, offer response, and segment-level differences.
This publication summarises how household spending priorities shifted across regions during Q1 2026 so researchers and partners can interpret essentials vs discretionary signals in aggregate.
South African households continued redirecting attention toward essentials during the reporting window, with grocery and transport drawing the largest aggregate response volumes. Participation strengthened across the period while coarse demographic bands remained directionally balanced across major provinces. Snapshot at publication (±1.8% at 95% confidence (n=3 012)): The panel recorded 3 012 anonymised responses across 8 published survey families; Grocery led category attention at roughly 70%.
This window summarises verified, anonymised Dootsa member activity across published surveys on the platform. Roughly 8 published survey families contributed to the aggregate counts shown here. 3 012 responses met the filter for this brief; all figures are rounded and reported in aggregate to protect respondents.
Category mix highlights where respondent attention clustered during the window. Largest signals (aggregate only): Grocery (2 110 responses); Transport (1 730 responses); Mobile Data (1 460 responses); Electricity (1 290 responses) Category labels reflect internal taxonomy—interpret as directional themes, not sales forecasts.
This flow view could not be laid out from the current dataset, so use the accompanying section text for this figure.
Daily participation trended upward over the period on an aggregate basis. Day-level counts can reflect campaign cadence, weather, or holidays—avoid over-fitting a single causal story.
Where demographic attributes are available, Dootsa reports coarse bands only in aggregate. Largest bands in this window (directional): Gauteng (980); Western Cape (720); KwaZulu-Natal (610); Eastern Cape (380). We suppress or generalise patterns that could imply small or identifiable groups.
Creators can improve signal by shortening surveys where possible, front-loading the most material questions, and aligning answer options with how members already think about a category. Strong aggregate engagement in this window suggests members reward clear, respectful research design.
For partners, this brief is best used as a directional read on panel engagement and category salience—not as a substitute for a scoped study with an explicit sampling plan. Contact Dootsa for tailored research design when you need category, region, or audience cuts beyond what public aggregates can support.
Best baseline comparison for categories.
Improves readability for longer labels.
Good for proportional composition.
Clear part-to-whole communication.
Highlights relative size differences.
Useful for profile-style comparisons.
Best for time-series change over time.
Shows spread and anomalies by day.
Expand each published survey to see how respondents answered individual questions. Public view shows percentages only — no individual responses or free-text answers.
Share of responses per choice (rounded %)
Share of responses per choice (rounded %)
Share of responses per choice (rounded %)
Find the first behaviour consumers change when pressure rises and which trade-off they protect.
The public report shows the signal; this follow-up explains the decision pathway brands can act on.
Example question: When grocery costs rise, what do you change first?
Break the headline finding by age, province, income band, and household context.
The next commercial question is not whether the signal exists, but who it matters to most.
Example question: Which group is most likely to switch, pause, or buy down?
Turn the insight into tested creative language and offer hooks before media spend.
A research finding becomes valuable when it improves messaging, offers, and product decisions.
Example question: Which headline feels most believable?
Select the participant demographics this publication covers, pick a follow-up angle, and open a pre-filled Dootsa survey draft with that audience attached.
This brief reports aggregate, anonymised Dootsa member responses for the stated window. Figures combine published survey activity across the platform; no individual or small-cell disclosure. Source surveys: 8 published survey families (aggregate category labels only).. Dootsa surveyed 3 012 South African members between 1 March 2026 and 21 April 2026 via the Dootsa app and web platform. Respondents were stratified across age (18–24, 25–34, 35–44, 45–54, 55+), gender, and province to broadly mirror Stats SA national distributions. Median completion time was 11 minutes. All figures shown are rounded; raw response data is held internally and used only in aggregate. Open-text responses were anonymised before analysis. Margin of error: ±1.8% at 95% confidence.
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