Create an Internship Project: Market Research Report on Which Discounted Gadgets Drive Student Purchases

Hook: Turn a 6-week internship into retail-driving insights — fast

Students, store managers and interns: you know the pain — countless discounted gadgets appear each semester, from smart lamps to pocket micro speakers, yet it’s unclear which discounts actually make students pull out their wallets. This project brief gives retail interns a ready-to-run plan to research which discount types and products drive student purchases, with plug-and-play data collection templates, analysis steps, and presentation guidance you can complete within an academic term or summer internship.

Project at a glance (Most important info first)

Goal: Determine how discount type and product category influence student buying behavior, and recommend optimized promotions for campus and online channels.

• Primary research questions: Which discount formats (percentage off, dollar-off, bundle, limited-time flash, student-exclusive) increase conversion among students for target products like smart lamps and micro speakers?
• Target products: budget smart lamps, Bluetooth micro speakers, budget smartwatches, portable chargers — gadgets widely promoted at CES 2026 and discounted across retailers in early 2026.
• Core methods: short surveys, in-store/online A/B promo tests, observational intercepts, and structured interviews.
• Deliverables: market research report, data CSV, slide deck with 3 promotion recommendations and forecasted lift.

Why this matters in 2026

Post-CES 2026, many consumer tech items (RGBIC smart lamps, mini Bluetooth speakers, affordable smartwatches) reached price points where student budgets matter. Retailers ran aggressive discounts on these categories in late 2025 and early 2026 — for example, headline deals on smart lamps and micro speakers pushed impulse buys. Students now respond not only to price, but to timing, social proof, and campus-specific incentives (student bundles, exclusive codes, or BNPL options). This project captures those trends and tests discount effectiveness in real student populations.

Research design — simple, practical, rigorous

Design the study to be executable in 4–6 weeks by a small intern team (1–4 people). Combine quick surveys with behavioural A/B tests linked to real offers, and validate with observational data.

Step-by-step research flow

1. Define product set (choose 3–6 SKUs across two categories: smart lamps and micro speakers).
2. Design 2–3 discount conditions to test (e.g., 20% off vs $15 off vs bundle + free shipping vs student-only 15% code).
3. Run online A/B tests for digital channels (email, social, campus Discord) and in-store placement tests if possible.
4. Collect short intercept surveys at point-of-sale and online via pop-up surveys after purchase or cart abandonment.
5. Conduct 10–20 structured interviews to understand motivations behind purchase decisions.
6. Analyze results and produce recommendations with projected revenue lift and suggested next actions.

Sample size & sampling strategy

For quick, actionable results: aim for minimums that balance speed and statistical meaning.

• Surveys: 300–500 completed responses across channels (stratify by on-campus vs off-campus students).
• A/B tests: 500–2,000 impressions per variant to detect moderate lift (4–8%) depending on baseline conversion rate.
• Interviews: 10–20 semi-structured interviews for qualitative depth.

Key metrics (what to measure)

• Conversion rate per discount type (click-to-purchase or footfall-to-purchase).
• Average order value (AOV) with and without bundle promotions.
• Incremental lift compared to baseline non-discounted traffic.
• Redemption rate for student codes.
• Price sensitivity index: how often a student reports price as primary driver.
• Intent vs. purchase gap: survey-stated intent vs actual sales.

Actionable data collection templates

Below are ready-to-use templates interns can copy into Google Forms, Typeform, or print for in-store intercepts. Each template includes a rationale and how to use it on day one.

1) Short student survey (for online & in-person)

Use this 8-question survey to capture purchase intent, discount sensitivity and channel preference. Target completion time: 60–90 seconds.

• Q1: Where do you live? (On-campus / Off-campus / With family)
• Q2: Which of the following would you consider buying in the next 30 days? (Smart lamp, Micro speaker, Smartwatch, Portable charger) — multi-select
• Q3: How likely are you to buy if the item has 20% off? (1-5 Likert)
• Q4: How likely are you to buy if the item has $15 off? (1-5 Likert)
• Q5: Would a bundle (lamp + speaker for $X) make you more likely to buy? (Much less likely / No change / Slightly more likely / Much more likely)
• Q6: Which offer would you prefer? (20% off / $15 off / Bundle / Student-exclusive code / Free shipping)
• Q7: Primary reason to buy gadget: (Price / Aesthetics / Brand / Reviews / Utility / FOMO)
• Q8: Where did you hear about the deal? (Instagram / TikTok / Campus flyer / Email / Word of mouth / Other)

2) CSV data export template (use as header row)

timestamp,channel,variant,product_sku,discount_type,discount_value,student_status,age_group,conversion,purchase_amount,redeemed_code,referrer,comments

Instructions: export A/B experiment data into this CSV data export template format daily. Keep comments for anomalies (server outage, stockouts).

3) In-store observational checklist

• Time of day
• Store traffic estimate (low/med/high)
• Promo placement (endcap / shelf / register / demo table)
• Signage clarity (good / ok / poor)
• Staff engagement (proactive / passive / absent)
• Student interactions observed (n) — note ethnic mix, gender, group vs solo
• Sales observed attributable to promo (n)

4) Interview script (10–15 mins)

Use for structured interviews with students who purchased or considered purchase.

1. Intro & consent: explain 10-minute interview for research; offer small incentive.
2. Warm-up: Which gadgets do you usually buy for your dorm? (open)
3. Recall: Do you remember any recent gadget promotions? Which ones? (probe: lamp, speaker)
4. Discount preference: Which discount felt most compelling and why?
5. Decision factors: rank Price, Reviews, Design, Brand, Peer recommendation.
6. Channel preference: where do you prefer to see student discounts?
7. Close & thanks: is there anything retailers could do to make you buy more?

Analysis plan — from raw numbers to recommendations

Keep analysis pragmatic: focus on actionable conclusions, not only p-values.

Quantitative steps

• Calculate conversion rates by variant and product (conversions / exposures).
• Compute relative lift: (variant_conv - control_conv) / control_conv.
• Use chi-square or two-proportion z-test to check significance for conversion differences; include confidence intervals.
• AOV and revenue-per-visit: multiply conversion rate by average order value to get revenue per impression for each promo.
• Segment by student_status, residence (on/off campus), and referrer to spot high-return segments.

Qualitative steps

• Code interviews for recurring themes: price, aesthetics, social proof, urgency.
• Extract 3–5 verbatim quotes to use in the executive summary (anonymous).
• Combine observational notes (placement & staff behavior) to explain any in-store anomalies.

Timeline & team roles (4–6 week sprint)

1. Week 0: Kickoff — finalize SKUs, secure approvals and promo codes.
2. Week 1: Build surveys/forms, set up A/B variants on digital platforms, train staff for in-store intercepts.
3. Weeks 2–3: Data collection — run experiments, collect surveys and interviews.
4. Week 4: Clean data, run analysis, draft report.
5. Week 5: Prepare slide deck, practice presentation with stakeholders.

Roles: Project lead (intern), data analyst (intern or manager), field interviewer (1–2 interns), store liaison (manager).

Real-world example: Applying the brief to smart lamps and micro speakers

Imagine you test two promotions on a popular RGBIC smart lamp and a best-selling micro speaker:

• Variant A: 20% off (no student code)
• Variant B: Student-exclusive 15% + free shipping (requires student verification)
• Variant C: Bundle (lamp + micro speaker for $X)

Hypothetical findings (based on trends observed in early 2026 retail promotions):

• Conversion: Variant A = 3.0%, Variant B = 4.5%, Variant C = 5.2%.
• AOV: Variant A = $38, Variant B = $35 (lower AOV but higher conversion), Variant C = $62 (highest revenue-per-visit).
• Insight: Student-exclusive offers drive higher conversion than headline % discounts because they pair psychological ownership ("this is for me") with scarcity. Bundles drive the biggest revenue lift when aligned to dorm-room kit messaging.

From these results, interns can recommend a campus-focused bundle campaign for move-in week with influencer-styled UGC and a student-code flash sale during exam week.

Presentation & recommended deliverables

Your final package should include:

• One-page executive summary with topline recommendation and expected ROI (use a forecast table).
• Slide deck (10–12 slides): background, methods, key metrics, topline results (visuals), 3 recommended promotions, implementation plan and estimated lift.
• Raw CSV and cleaned dataset + analysis notebook (Google Sheets or Jupyter) so stakeholders can validate.
• Appendix: survey instrument, interview notes and consent forms.

Advanced strategies — stand out with modern twist (2026-forward)

• Micro-influencer campus seeding: partner with campus creators to post unboxings and discount codes. Early 2026 shows micro-creator promotions amplify student code redemptions.
• Social commerce experiments: test in-stream checkout on TikTok/Instagram for impulse gadgets; measure time-to-purchase vs redirect to site.
• AI-driven personalization: use simple rule-based personalization (bundle suggestions by cart contents) and A/B test against generic pages.
• Student verification friction trade-off: weigh the lift from student-only prices against the drop from extra verification steps.

Pro tip: In early 2026, limited-time flash discounts tied to campus events (move-in, finals) outperformed standing student discounts by creating urgency — but combos and UGC maintained higher long-term AOV.

Ethics, permissions and logistics

Always request approval from campus authorities for on-site research and follow retailer privacy rules for customer data. Use anonymized IDs in CSVs and get explicit consent for interviews. Offer fair incentives: $5–$10 gift card or a small freebie is typical for students.

Common pitfalls & how to avoid them

• Avoid running multiple promo experiments in the same channel simultaneously — overlapping promotions confound attribution.
• Track stockouts — if an item is out during a promo, record it in comments.
• Don’t overcomplicate surveys; keep them under 90 seconds for better completion rates.

Next steps — quick checklist for day one

1. Select 3 SKUs and get SKU-level pricing and margin data from the buyer.
2. Create the student survey in Google Forms and a QR code for in-store use.
3. Set up A/B landing pages or coupon codes with distinct codes per channel (IG20, STUD15, BUNDLEX).
4. Schedule 10 interview slots and recruit with targeted campus posts and flyers.

Wrap-up: What success looks like

By the end of the project you should be able to answer: Which discount type maximizes conversion? Which promotion drives the highest revenue-per-visit? Which channel or campus activation yields the best ROI? Provide clear recommendations: a primary promo to scale, a secondary experiment to validate, and a merchandising change (placement, signage, staff talking points) that can improve conversion by an estimated percent.

Ready to run this internship project? Use the templates above to start data collection today. A 4–6 week sprint can deliver a clear promotional playbook your retailer can scale for the next campus season.

Call to action

Download the survey and CSV templates, or contact your retail manager to get SKU access and promo codes. If you’re an intern or teacher planning this project — start the kickoff this week and share results with us for a peer review and presentation tips.

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