Consumer Spending Tracker

Use This Skill When

• The user wants a current read on consumer demand.
• The task requires combining spending data, traffic, mix, and promotions into a coherent demand view.
• The analysis needs to separate healthy demand from discount-led activity.

Required Inputs

• target: subsector, retailer, category, or broader consumer basket
• signals: card spending, traffic, units, basket size, promotions, category mix, channel checks
• time horizon: weekly, monthly, quarterly, or seasonal
• consumer lens: discretionary, staples, value channel, premium channel, online, or store-based
• If the signal set is patchy, label the read as provisional and explain which demand components are less visible.

Workflow

1. Define the demand slice and measurement frequency.
2. Review spending, traffic, and basket separately.
3. Assess promotions and mix to judge quality of demand.
4. Compare value versus premium behavior if relevant.
5. Separate nominal spending growth from real unit demand.
6. Conclude on demand direction, quality, and likely next pressure points.

Output Requirements

• Focus on demand quality, not just top-line spending growth.
• Separate price, units, traffic, and mix.
• Call out whether activity is healthy, promotion-led, or trade-down-led.
• End with the most informative next datapoints.

Output Template

Quality Checks

• Confirm spending, traffic, and mix are not collapsed together.
• Check that nominal growth versus real demand is considered.
• Verify promo intensity is addressed before calling demand healthy.
• Make sure channel or category segmentation is explicit when needed.

Guardrails

• Do not equate higher nominal spending with stronger real demand.
• Do not ignore promotions and discounting.
• Do not generalize one retailer or channel to the whole consumer sector without caution.
• Do not fabricate card or traffic data.

Example Prompts

• Build a consumer spending tracker for US discretionary over the next quarter.
• Tell me whether current retail demand is healthy or promo-driven.
• Use spending and traffic data to assess staples versus discretionary demand quality.