A new report by The Kaplan Group analyzed consumer and small business stress-related searches through 2025. Credit counseling and debt management searches have risen significantly over the past year, while payday loan and debt consolidation searches have declined from prior peaks.
Key Takeaways
- Credit counseling searches rose 26.6 percent year over year, indicating mounting demand for structured repayment help.
- Payday loan searches fell 18.3 percent versus last year, though interest remains elevated.
- Mississippi ranks number 1 by combined search intensity across keywords, leading the top 10 state list by normalized score.
Stress-Related Search Volume
Recent shifts in search behavior reveal where demand for debt and financial help is rising—or falling—compared to last year. The data below spotlights the most notable changes across key credit and stress-related topics.
- Positive momentum
- Credit counseling and non‑profit debt management are both up on a 12‑month basis and show accelerating recent interest.
- Personal loan for debt shows a solid 6‑month pickup despite flat 12‑month change, suggesting a recent turn upward.
- Negative or cooling momentum
- Debt consolidation, small business loan, and payday loan are all down year‑over‑year and have materially lower last‑6‑month averages versus prior, indicating a broad cooldown.
- Mortgage forbearance has one of the steepest declines, consistent with a normalization from earlier peaks.
- Working capital and loan modification are trending lower in the recent 6‑month window.
Geographic Variation in Debt and Credit Search Interest
For each keyword, we scored each state’s search interest. This method highlights not just the state that leads in one topic (like payday loans or bankruptcy), but those where people frequently search about a broad mix of debt and financial stress topics—showing where concern is widespread and persistent.
Top 10 States by Combined Search Intensity
- Mississippi
- Louisiana
- New York
- Kansas
- Oklahoma
- Alabama
- Delaware
- Nevada
- Michigan
- New Jersey
How to interpret:
A high rank means a state often places near the top for many types of debt-related searches, indicating broad-based, elevated interest in financial stress topics.
How Search Behavior Tracks Economic Indicators
We examined the correlations between keyword search trends and macroeconomic indicators, comparing data at time lags from −6 to +6 months. For each keyword-macro pairing, we noted not just the strongest relationship but also whether search trends led or lagged economic shifts.
What to Watch in the Data
- Rate Sensitivity:
When borrowing costs change, so does search interest in debt solutions. Debt consolidation and related “optimize my debt” searches closely track bond yields—with the strongest correlation (about r≈0.6) appearing at a lag of zero to one month. This means consumers typically adjust their search behavior almost immediately after changes in borrowing rates. - Household Stress and the Labor Market:
Searches for credit counseling and bankruptcy rise as jobless claims increase, reflecting rising financial strain. The connection is strong (correlations usually between r≈0.4 and 0.6), and search activity often climbs at the same time or within a month of worsening labor conditions. - Small Business Financial Conditions:
Interest in small business loans also tracks jobless claims, peaking at a correlation of about r≈0.5 with no lag. This suggests small businesses begin searching for funding as soon as employment conditions start to deteriorate, not months in advance.
Conclusion
Consumers are shifting from quick fixes to structured help. Credit counseling and non-profit debt management are up sharply (credit counseling up 26.6 percent YoY), pointing to mounting budget pressure and greater demand for organized payoff plans. Stress is concentrated in specific regions. Southern states led by Mississippi and Louisiana rank highest on combined search intensity.
Methodology
- Data sources
- Search interest and growth metrics came from Google Keyword Planner over the last 12 months and Google Trends indices for the state level data.
- Macro indicators included interest rates and labor metrics used for correlation testing.
- Growth calculations
- For each keyword, we computed latest versus prior year (12‑month change), last 6‑month average vs prior 6‑month average (level change and percent change), and highlighted the latest observed level.
- State ranking score
- We standardized each state’s index within each keyword into a z‑score to normalize scales across keywords.
- A state’s combined interest score is the sum of its z‑scores across all keywords it appears in. We report supporting fields total_keywords, avg_z, sum_index, and avg_index; ranking is based on sum_z, with avg_z as a tie‑breaker.
- Correlation analysis
- For each keyword–indicator pair, we computed Pearson correlations across lags −6 to +6 months to identify the strongest relationship and whether searches lead or lag macro moves.
- We summarized the peak correlation and its lag for interpretation (e.g., optimization terms peaking around r ≈ 0.6 at 0–1 month vs yields; hardship terms r ≈ 0.4–0.6 around contemporaneous lags with jobless claims).
- Quality checks and limitations
- Normalization ensures comparability across keywords but emphasizes relative, not absolute, search intensity by state.
- Correlations are descriptive, not causal, and can shift as new data arrives.
