Cashback Apps Comparison: Portfolio Strategy Guide 2025

Why Most Cashback Apps Comparisons Mislead You

Standard cashback app rankings focus on maximum headline rates without asking the critical question: When do those rates actually apply?

An app advertising “5% cashback” might only offer that rate on electronics during limited promotional windows, while your actual purchases—groceries, gas, dining—earn the baseline 1%. Meanwhile, a category specialist in your highest-spend vertical offers a consistent 3.5% with no hoops to jump through.

This creates a predictable failure pattern: You choose the highest-ranked app based on its best-case rate, use it for three months across your normal shopping mix, and realize you’re earning 60% less than the comparison chart suggested. The guide wasn’t wrong about the app’s capabilities—it was wrong about whether those capabilities matched your spending pattern.

The standard comparison approach assumes apps compete head-to-head, like choosing between two identical credit cards with different rewards rates. In reality, cashback apps operate more like specialized tools in a toolkit. A browser extension excels at capturing spontaneous online purchases. A deal aggregator rewards planned research. A category specialist dominates a specific vertical through exclusive merchant partnerships.

This guide introduces a three-category strategic framework that shows which app types serve which roles, then helps you build a 2–3 app portfolio matched to your actual shopping behavior. No more generic “best app” rankings—instead, you get a decision framework you can apply to your specific situation.

The Three Strategic Categories of Cashback Apps

Understanding these categories is the key to building an effective portfolio. Most users need apps from 2–3 categories, not multiple apps from the same category.

Category 1 – Passive Stackers (Browser Extensions)

Operational model: Auto-activate at checkout with minimal user action required.

Passive Stackers run as browser extensions that detect when you’re shopping at a partner retailer and automatically apply available cashback. You install once, then forget about them. When you land on a supported merchant site, a notification appears: “Activate 2.5% cashback.” One click, done.

Rate profile: Moderate rates (typically 1–3%) across broad retailer networks covering hundreds to thousands of merchants.

Best for: High-frequency online shoppers who value convenience over maximum per-purchase rates. If you shop online 5+ times per month across diverse retailers, Passive Stackers capture more total dollars despite lower individual rates because they don’t require pre-purchase planning.

Major examples: Rakuten, Honey (now PayPal Rewards), Capital One Shopping, TopCashback browser extension.

Pros:

• Zero friction after initial install—captures spontaneous purchases you wouldn’t have optimized otherwise
• Broad merchant coverage increases transaction capture rate
• Often includes coupon-finding features as bonus value

Cons:

• Lower rates than Active Hunters or Category Specialists for any given purchase
• Browser-dependent (must shop on desktop/laptop, not mobile app in many cases)
• Tracking can break with certain privacy settings or ad blockers

Scenario: Sarah shops online 3 times per week across 15 different retailers—clothing, home goods, electronics, books. An Active Hunter might offer 6% on one of those retailers this week, but Sarah would need to check the app before each purchase and risk missing deals on the other 14 stores. A Passive Stacker earning 2% across all 15 retailers captures more total dollars with zero additional effort.

Strategic role in portfolio: Foundation layer. Install one, let it run in the background, then add more specialized apps on top for high-value purchases.

Category 2 – Active Hunters (Deal Aggregators)

Operational model: Requires manual app check before purchase. Offers rotate frequently with time-limited boosts.

Active Hunters reward users who plan purchases and check the app first. You open the app, browse current offers, activate the deal you want, then complete your purchase through the app’s link or upload a receipt afterward. Rates vary dramatically—a retailer might offer 1% baseline, 8% during a weekend boost, then drop back to 2% next week.

Rate profile: Variable (0.5–12%) with promotional spikes that require active monitoring and timing optimization.

Best for: Planned purchases where you can afford the 2–5 minutes of pre-purchase research time. Works best for weekly grocery runs, monthly household stock-ups, and considered purchases (appliances, furniture) where the basket value justifies the effort.

Major examples: Ibotta, Dosh, Fetch Rewards, Checkout 51.

Pros:

• Highest potential rates during promotional periods
• Receipt-scanning models work for in-store purchases (major advantage over browser extensions)
• Often include product-specific bonuses beyond merchant rates

Cons:

• Requires intentional effort before each purchase—high friction for spontaneous buying
• Offer variability means inconsistent returns (great week vs. mediocre week)
• Gamification mechanics can create pressure to buy items you don’t need

Scenario: Marcus uses Ibotta for his weekly grocery run at a store offering 5% cashback this week. His average basket is $120, earning $6 for 3 minutes of app interaction. That same week, he makes six spontaneous sub-$20 purchases where checking the app would feel like overkill. Passive Stacker captures those automatically at 1.5%, while Active Hunter sits unused for small transactions.

Strategic role in portfolio: Tactical layer for high-value planned purchases. Pair with a Passive Stacker to avoid leaving money on the table during spontaneous shopping.

Category 3 – Category Specialists

Operational model: Deep partnerships in specific verticals (travel, dining, gas, groceries) with exclusive offers unavailable on generalist platforms.

Category Specialists focus on one spending vertical and negotiate higher rates through volume commitments with merchants in that space. A dining specialist partners with thousands of restaurants but offers zero coverage for electronics, travel, or groceries. Users link a credit/debit card, then earn cashback automatically when they transact at partner locations.

Rate profile: High rates (3–8%) in focused categories, with zero coverage elsewhere.

Best for: Users with concentrated spending in one vertical. If 40%+ of your discretionary spending falls into one category (dining out, fuel, travel), a specialist will dramatically outperform generalist apps in that space.

Major examples: Drop (dining and subscriptions), Upside (gas stations), Seated (restaurant reservations), Hopper (travel).

Pros:

• Highest rates in their specialized category due to exclusive merchant partnerships
• Automatic activation via linked card (low friction after setup)
• Often include non-cashback perks (priority reservations, loyalty status) in their vertical

Cons:

• Zero value outside their category—creates portfolio complexity
• Geographic limitations (gas specialist might cover 60% of stations in your city, 20% in a neighboring state)
• Some require specific behaviors (Seated requires reservation, not walk-in)

Scenario: Elena spends 60% of discretionary income on dining out (4–6 restaurant visits per week). A generalist app offers 1.5% on dining. Drop offers 5% at 40% of her regular restaurants. Over a year, that difference on $4,800 dining spend is $168 vs. $72—a $96 gap that justifies managing a second app despite the complexity.

Strategic role in portfolio: Power-up for concentrated spending. If you have an obvious high-spend category, add the dominant specialist in that space. If your spending is evenly distributed, skip this category entirely.

The 5-App Comparison Matrix: Strategic Positioning

This table shows how five major apps occupy different strategic niches. Notice that direct “apples to apples” comparison is misleading—they’re designed for different use cases.

Key observations:

Retailer exclusivity matters: Some merchants only partner with one platform. Target might offer cashback through Ibotta but not Rakuten, while Best Buy appears on Rakuten but not Drop. This structural reality makes portfolio approaches more effective than loyalty to a single app.

Redemption models create friction hierarchy: PayPal transfers (instant liquidity) > direct deposit (3–5 day delay) > gift cards (spend locked to specific retailers). Apps offering only gift card redemption effectively reduce your return by 5–15% due to restricted optionality.

Thresholds interact with usage frequency: A $25 minimum is irrelevant for weekly users but creates 6–12 month delays for casual monthly shoppers. Time-to-redemption affects real returns through opportunity cost and abandonment risk.

The Hidden Cost of “Free Money”: Redemption Friction Analysis

Advertised cashback rates assume you’ll actually redeem your earnings. In practice, redemption friction reduces effective returns by 15–40% for typical users through three mechanisms: minimum thresholds, expiration policies, and payment rail limitations.

Minimum Thresholds Erode Effective Returns

Most cashback apps require $10–$25 in accumulated earnings before you can withdraw. For infrequent users, this creates multi-month delays between earning and receiving funds.

Time-to-redemption affects real present value. Money you’ll receive in 18 months is worth less than money you receive today, even ignoring inflation. A $50 balance that takes 15 months to reach threshold is worth approximately $47 in present value terms at a 3% discount rate—a 6% haircut on your “guaranteed” returns.

Abandonment risk is substantial. Consumer fintech research suggests 20–35% of cashback app users never reach the redemption threshold on at least one of their accounts. These balances simply expire or sit dormant indefinitely. You earned the cashback—but never converted it to spendable value.

Illustrative example: You earn $2/month through an app with a $25 minimum. Time to redemption: 12.5 months. If you forget about the app around month 9 (common), that $18 earned becomes $0 received. Even if you persist, the present value of $25 in 12 months is closer to $24 at conservative discount rates—and that assumes you immediately spend or invest it rather than letting it sit as gift card balance.

Portfolio implication: Apps with lower minimums ($5–$10) provide faster redemption cycles and lower abandonment risk. If comparing two otherwise equal apps, favor the one with a $10 threshold over $25—the difference might add 8–12% to effective returns through reduced time delays.

Expiration Policies and Payment Rails

Expiration windows: Cashback typically becomes “pending” after purchase, then “available” after 30–90 days (merchant return window). Some apps then impose additional expiration: available balance expires if unredeemed within 6–12 months. This creates a narrow window between “balance becomes available” and “balance expires,” especially problematic when combined with high minimums.

Payment method impacts liquidity:

• PayPal/Venmo (instant): True cash equivalent. Withdraw to bank or spend immediately. No friction loss.
• Gift cards (high friction): Spending locked to specific retailers. Effective 5–15% discount due to restricted optionality—you might not have naturally shopped at that retailer, or you’re forced to spend sooner than optimal.
• Bank transfer (moderate friction): 3–5 business day delay. Minor present value loss plus cognitive cost of waiting/tracking.

Geographic restrictions: Many cashback apps are US-only, or offer limited redemption options for international users. Canadian users might face $50 minimums instead of $25, or only gift card redemption where US users get PayPal. Always check geo-specific terms before assuming an app will work in your market.

Checklist: Red flags in app terms—watch for:

• Pending period >90 days (excessive merchant protection)
• Available balance expiration <12 months (creates narrow redemption window)
• Gift cards as only redemption option (locks value to specific retailers)
• Different minimums by payment method (e.g., $10 gift card vs. $50 cash—nudges toward less valuable redemption)
• Geo-restrictions not clearly disclosed until after signup

International users: If outside the US, verify redemption rails before investing time. Many apps either don’t operate in your country, offer reduced merchant networks, or restrict redemption to gift cards rather than cash transfers available to US users.

Building Your Optimal 2–3 App Portfolio

The goal is maximum returns with minimum complexity. Most users hit diminishing returns after 2–3 apps—additional apps add cognitive load and account management burden that exceeds marginal earnings.

The Decision Matrix: Matching Apps to Shopping Behavior

Self-assessment framework: Answer three questions to determine your optimal portfolio.

1. Shopping frequency—how often do you make purchases?

• High frequency (5+ purchases/week, mostly online): Passive Stacker is essential foundation. You’re making too many transactions to manually optimize each one.
• Medium frequency (2–4 purchases/week): Passive Stacker + Active Hunter combo captures both spontaneous and planned purchases.
• Low frequency (<5 purchases/month): Single Active Hunter or Category Specialist might suffice. Avoid portfolio complexity that exceeds your transaction volume.

2. Category concentration—where do you spend most?

• Evenly distributed across categories: Generalist apps (Passive Stacker + Active Hunter). No single vertical dominates enough to justify a specialist.
• 60%+ in one category (dining/gas/groceries/travel): Add Category Specialist for that vertical. The rate difference will compound significantly on concentrated spending.
• Two dominant categories: Consider Passive Stacker + two Category Specialists, skipping Active Hunter entirely.

3. Tolerance for app-switching friction—how much optimization effort will you sustain?

• High tolerance (enjoy deal-hunting): Full three-app portfolio. You’ll actually use the Active Hunter consistently.
• Medium tolerance (willing to optimize big purchases only): Passive Stacker + Category Specialist. Automatic activation models reduce ongoing effort.
• Low tolerance (want set-and-forget): Single Passive Stacker or card-linked Category Specialist. Accept slightly lower returns in exchange for zero maintenance.

Three sample portfolios:

Portfolio A: High-Frequency Generalist

• Primary: Rakuten (Passive Stacker) for broad online coverage
• Secondary: Ibotta (Active Hunter) for weekly grocery runs
• Use case: Someone who shops online 6+ times/week across many retailers, plus one focused weekly grocery trip
• Expected lift: 15–25% higher returns vs. Rakuten alone, due to Ibotta’s superior grocery rates

Portfolio B: Category-Concentrated

• Primary: Capital One Shopping (Passive Stacker) for baseline coverage
• Secondary: Drop (Category Specialist) for dining (50% of discretionary spending)
• Tertiary: Upside (Category Specialist) for gas (long commute)
• Use case: Someone with 70% of spending in two predictable categories
• Expected lift: 30–50% higher returns vs. generalist alone, due to specialist rates on concentrated spending

Portfolio C: Low-Frequency Optimizer

• Single app: Fetch Rewards (Hybrid Hunter) with any-receipt model
• Use case: Casual shopper making 4–6 purchases/month, wants simplicity
• Trade-off: Accepts 10–20% lower maximum returns in exchange for zero portfolio complexity

Decision tree logic:

• If shopping frequency >5/week → Start with Passive Stacker
• If 60%+ spending in one category → Add Category Specialist for that vertical
• If shopping frequency >2/week AND willing to pre-plan → Add Active Hunter for high-basket purchases
• If none of above → Single app (Passive Stacker OR Category Specialist in highest-spend category)

When to Consolidate vs. When to Stack

The 80/20 rule for cashback apps: Two well-chosen apps typically capture 80% of optimal earnings. The third app adds marginal value that might not justify the complexity.

Complexity costs are real:

• Cognitive load: Remembering which app to use for which purchase
• Account management: Tracking balances across multiple platforms, managing multiple redemption cycles
• Opportunity cost: Time spent optimizing could be invested in higher-value activities

Break-even framework (qualitative): Add a third app only if it would generate $10+/month in additional cashback. Below that threshold, the juice isn’t worth the squeeze for most people.

Illustrative calculation: If App #3 would capture 20 additional transactions/month at an average 2% rate uplift over your existing coverage, and your average transaction is $30, that’s 20 × $30 × 0.02 = $12/month. Worth adding. If it would capture 10 transactions at 1.5% uplift, that’s 10 × $30 × 0.015 = $4.50/month. Probably not worth the complexity.

When retailer exclusivity forces multi-app approach: Some high-value merchants only partner with one platform. If your single largest merchant (e.g., Amazon for many users) offers cashback through App A but not App B, you might need both apps regardless of complexity preference. In this case, the portfolio decision is made for you by structural market constraints.

Portfolio maintenance schedule:

• Monthly: Check balances, redeem anything at threshold
• Quarterly: Review which apps you’re actually using vs. which have gone dormant
• Annually: Re-evaluate portfolio based on changed shopping patterns (new job = different commute = different gas spending)

Signs you should consolidate:

• You have 4+ active cashback apps
• One or more apps consistently has <$3/month activity
• You’re missing cashback opportunities because you forgot which app covers which merchant
• Redemption thresholds on secondary apps aren’t being reached within 6 months

5-Country Cashback App Landscape

Cashback app availability and functionality varies significantly by market. This table provides context for non-US readers and highlights key differences in market maturity, regulations, and available options.

Key observations by market:

United States: Highest app diversity and merchant coverage. Competition drives better terms (lower minimums, more redemption options). Most global apps start here before expanding internationally.

United Kingdom: Strong consumer protection via FCA oversight creates transparency requirements. GDPR compliance is non-negotiable, which limits certain tracking techniques used by US apps. Airtime Rewards (mobile bill credits) is unique to UK market.

Canada: Smaller population and merchant density creates challenges. Many retailers offer cashback through only 1–2 apps, reducing portfolio flexibility. Higher redemption minimums ($50 CAD common) create longer time-to-payout for casual users.

Australia: Geographic isolation leads to focus on domestic and Asian merchants rather than European/American retailers. Gift card redemption more prevalent due to payment infrastructure differences. Strong growth in urban centers (Sydney, Melbourne) but limited rural coverage.

India: Mobile-first infrastructure creates different UX patterns (apps optimized for spotty connectivity, low-end devices). UPI payment rails enable instant bank transfers unavailable in many Western markets. Heavy concentration in e-commerce (Flipkart, Amazon India) with less brick-and-mortar coverage.

Cross-border limitations: Most cashback apps are geo-locked. A US resident traveling to UK cannot earn cashback through US apps on UK purchases, and vice versa. VPN use to circumvent geo-restrictions violates most app terms and risks account termination.

Currency conversion impacts: International shoppers using home-country apps for foreign purchases face currency conversion fees that can erase 2–4% of cashback value. Always calculate net returns after conversion costs.

Privacy regulations: GDPR (EU/UK), PIPEDA (Canada), and emerging state-level US regulations affect app tracking capabilities. European apps typically offer less granular tracking but stronger privacy protections than US counterparts.

Common Mistakes That Kill Cashback Returns

These operational errors cause tracking failures and missed earnings, even when you’re using the right apps.

Mistake 1: Using retailer’s native app instead of cashback link

Retailer mobile apps bypass cashback tracking. If you click through a cashback app link, then complete purchase in the Amazon app, tracking breaks. Solution: Complete purchase in mobile browser (through cashback link) or use desktop with browser extension. Accept the slightly clunkier UX for guaranteed tracking.

Mistake 2: Clearing cookies or using private browsing mode

Most cashback tracking relies on cookies. Private browsing, aggressive cookie auto-deletion, and certain browser privacy settings break the tracking chain. Solution: Whitelist cashback app domains in your privacy settings, or use a specific browser profile for shopping with standard privacy settings.

Mistake 3: Ignoring exclusions buried in fine print

Common exclusions that surprise users:

• Sale/clearance items (many apps exclude discounted merchandise)
• Gift cards (even when purchased from a partner retailer)
• Taxes and shipping fees (cashback applies to product cost only)
• Specific brands within a retailer (luxury brands often opt out of cashback programs)

Solution: Before celebrating that 8% cashback rate, check the exclusions section. The effective rate on your actual purchase might be 0% if you’re buying excluded items.

Mistake 4: Letting balances expire below redemption threshold

If you earn $3/month through an app with a $25 minimum, redemption takes 8+ months. If the app has a 6-month “available balance” expiration window, you’re in a race you’ll lose. Solution: Consolidate to fewer apps with lower minimums, or set quarterly calendar reminders to check balances and make deliberate purchases to cross thresholds before expiration.

Mistake 5: Assuming all cashback is taxable income (US context)

The IRS generally treats cashback as a purchase discount (not taxable income), similar to using a coupon. However, signup bonuses and referral bonuses may be taxable. The distinction matters for users earning $600+ annually. Solution: Track bonus earnings separately from purchase cashback if you’re near reporting thresholds. Not tax advice—consult a professional for your specific situation.

Troubleshooting checklist when cashback doesn’t track:

• Did you click through the app/extension before purchasing? (If no → tracking won’t work)
• Did you complete purchase in same browser session without closing? (If no → cookie connection broken)
• Did you use coupon codes from outside the cashback app? (Many apps void cashback if you apply unauthorized codes)
• Did you return items from that order? (Cashback reverses when items are returned)
• Is purchase type excluded per app terms? (Check exclusions list)
• Did you wait the full pending period before assuming failure? (Can be 60–90 days)

How to Evaluate New Cashback Apps

New apps launch constantly, often with aggressive promotional rates to acquire users. This framework helps you separate legitimate newcomers from bad deals or risky platforms.

Framework for assessing new entrants:

1. Category focus—does it fill a gap or duplicate existing coverage?

If you already have a strong Passive Stacker and the new app is another browser extension with similar merchant coverage, it likely adds no value. Only consider if it’s a Category Specialist in a vertical you don’t yet cover, or offers exclusive merchants unavailable through current apps.

2. Redemption terms—realistic or suspicious?

Red flags:

• Minimum threshold >$50 (creates long time-to-payout and high abandonment risk)
• Gift cards as only redemption option with no cash alternative
• Pending periods >120 days (far exceeds standard merchant return windows)
• Vague language about “up to X%” without clear baseline rates

Green flags:

• Multiple redemption options including PayPal or direct deposit
• Clearly stated baseline rates (not just promotional maximums)
• Reasonable minimums ($5–$25)
• Transparent pending/available timelines

3. Retailer exclusivity—do they have unique merchant partnerships?

The only valid reason to add a new app to an existing portfolio is access to merchants not covered by current apps. Check: Does this app offer cashback at retailers where you currently earn nothing? If yes, there’s a case for addition. If it’s just duplicating coverage with slightly different rates, consolidation is smarter.

4. Data permissions and privacy—what are you trading for cashback?

Read the privacy policy, even briefly. Red flags:

• Selling browsing data to third parties beyond anonymized aggregation
• Permission requests for contacts, camera, microphone unrelated to core function
• Vague data retention policies (“we keep data as long as needed”)

Remember: You’re trading tracking data for cashback. That’s the core value exchange. But excessive permissions suggest the app’s real business model is data monetization, not merchant partnerships.

5. Company backing and longevity indicators—will they exist in 12 months?

Check:

• Recent funding rounds or public financial statements (suggests runway)
• Age of company (apps <6 months old are higher risk for shutdown)
• User reviews mentioning redemption failures (suggests cash flow problems)

If an app offers implausibly high rates with no clear merchant revenue model and thin user reviews, it might be growth-hacking toward acquisition rather than building sustainable business. That’s fine—ride the promotional rates—but don’t accumulate large balances you can’t redeem if they shut down.

Testing approach for new apps:

Week 1: Install, link payment methods, complete setup. Make one small test purchase ($10–$20) to verify tracking works correctly.

Week 2–4: Monitor whether test purchase moves from pending to available on expected timeline. Check if tracking attribution is reliable.

Month 2–3: If test worked, gradually increase usage. Don’t accumulate >$50 balance until you’ve successfully completed at least one redemption cycle.

Month 4+: If app has proven reliable (tracking works, redemption succeeds, no surprise term changes), integrate into regular portfolio.

External validation sources:

• Consumer Financial Protection Bureau (CFPB): US federal agency publishes guidance on fintech app privacy and consumer protection standards
• Federal Trade Commission (FTC): Issues alerts about specific apps with deceptive practices
• TrustPilot / Better Business Bureau: User reviews can flag systematic redemption failures or customer service problems

Look for patterns across reviews, not individual complaints. Every app has some failed transactions (user error, technical glitches). You’re looking for systematic issues like “app stopped paying out” or “balance disappeared after company acquisition.”

Final Recommendation: Start Here

Default beginner portfolio: One Passive Stacker + One Category Specialist in your highest-spend category.

Why this combination:

• Passive Stacker provides broad coverage with zero ongoing effort
• Category Specialist maximizes returns where you spend most
• Two apps are manageable for beginners without overwhelming complexity
• Combination captures 70–85% of optimal earnings for typical users

Step-by-step first 30 days:

Days 1–3: Setup

1. Choose Passive Stacker: Install Rakuten or Capital One Shopping browser extension
2. Choose Category Specialist: If dining = Drop, if gas = Upside, if groceries = Ibotta
3. Link payment methods, verify accounts, complete any signup bonuses

Days 4–30: Baseline testing

• Shop normally, using Passive Stacker for all online purchases
• Use Category Specialist for purchases in its coverage area
• Track earnings manually in a simple spreadsheet: Date | Merchant | App Used | Amount Earned

Day 30: Evaluate results

Calculate total earnings across both apps. Ask:

• Minimum threshold question: At current earn rate, how many months to reach redemption minimum? If >6 months on either app, consider switching to lower-minimum alternative.
• Effort-to-reward ratio: Is Category Specialist delivering $10+/month? If yes, keep. If no, evaluate whether the extra app is worth <$10/month.
• Coverage gap check: Are you making significant purchases ($100+/month) at merchants not covered by either current app? If yes, that’s your signal to potentially add App #3.

Success metrics—minimum $/month to justify ongoing use:

• Passive Stacker: $5/month minimum. Below this, you’re not shopping online frequently enough to justify even a zero-effort app.
• Active Hunter: $10/month minimum. The pre-purchase effort requires higher returns to break even on time investment.
• Category Specialist: $8/month minimum. Slightly lower than Active Hunter due to automatic activation, but still needs meaningful returns to justify portfolio slot.

When to add App #3:

Only if you can clearly articulate: “This app would earn me $10+ per month on purchases currently earning $0 through my existing apps.” Vague “might help” or “covers one extra store” doesn’t meet the bar.

Example: You’re earning $15/month through Rakuten + Drop portfolio. You notice you spend $200/month at gas stations not covered by either app. Upside covers 70% of those stations and would earn ~$8–$12/month. Clear case for addition. This is a coverage gap, not portfolio bloat.

30-day checkpoint decision:

• Earning $20+/month combined: Portfolio is working. Continue current approach, redeem when you hit thresholds.
• Earning $10–$20/month: Portfolio is decent. No urgency to optimize further unless you enjoy the process.
• Earning <$10/month: Either your shopping frequency doesn’t justify cashback apps, or you’ve chosen wrong apps for your spending pattern. Re-evaluate using the decision matrix in section above.