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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchTo analyze Jumia products in Excel, first verify what each row represents and where the data came from, then clean and document the fields before calculating measures, building PivotTables, and adding dashboard filters. A public Jumia product-analysis case study describes this workflow and reports several relationships between price, discounts, ratings, and reviews. Its results are specific to that dataset—not proof of how all Jumia products or customers behave.
What the Jumia Excel dashboard case study covers
The public case study describes cleaning product data, creating calculated measures, summarizing results, and presenting them in an interactive Excel dashboard. Its analysis discusses price, discounts, ratings, review volume, and measures such as discount amount and rating or price categories.
The public description does not establish that the underlying rows represent all Jumia listings, transactions, or a representative sample. It also does not establish the workbook’s complete field list or collection date. Treat the project as an example workflow, and verify the specific file you have before relying on its columns or findings. A listed price is not sales revenue, and a review count is not a count of purchases.
Start by establishing what the data can answer
Before making charts, record the dataset’s provenance and scope. These details determine whether comparisons are meaningful and what conclusions are safe to report.
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- Source and collection date: Identify where the rows came from and when they were collected.
- Geography and categories: Note which market and product groups are covered, if known.
- Row meaning: Confirm whether each row represents a product listing, a product variant, or something else.
- Time basis: Determine whether prices, discounts, and ratings are a one-time snapshot or measured across a period.
- Coverage: State what is missing or unknown, including whether the data is complete or sampled.
If any of these are unknown, say so in the dashboard notes. Do not imply that a product-level file measures Jumia-wide orders, revenue, customers, or seller performance.
Audit and clean the workbook before analysis
Inspect the actual file rather than assuming it has the same fields or problems as another version of the project. Keep a short transformation log so that someone else can understand how the analysis was produced.
- Check for blank rows, missing values, and duplicate records. Decide whether to retain, remove, or flag each case, and document the rule.
- Verify data types: prices and discounts should be numeric, ratings should be numeric where available, and category or product labels should be treated consistently.
- Check currency and number formats. A currency symbol or thousands separator stored as text can prevent valid calculations.
- Review rating values for plausible ranges and inspect unusual values rather than silently deleting them.
- Standardize category labels only when they clearly refer to the same category; retain an audit trail of changes.
Make calculations from the cleaned fields, and record whether each measure uses original or transformed values. If a price or rating is missing, do not silently replace it with zero: zero can be mistaken for a real value and distort averages.
Define measures from the fields you actually have
Calculated columns are useful only when their inputs and rules are clear. The case study discusses discount amounts and rating or price categories, but an exported file may not contain all required fields. Use a measure only when its source fields are present and interpretable.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problems- Discount amount: If both regular and discounted prices exist, define the calculation explicitly—for example, regular price minus discounted price—and confirm the two fields use the same currency and basis.
- Discount percentage: If the regular price is nonzero and the fields are comparable, calculate the reduction as a percentage of regular price. State the formula and how invalid or missing inputs are handled.
- Price band: Set and report the band thresholds. Avoid implying that arbitrary bands are official Jumia price segments.
- Rating group: State the rating cutoffs and preserve the raw rating for readers who need the original scale.
- Review volume: Keep review count distinct from rating. It can indicate how much review evidence is attached to a listing, but it does not establish how many people bought the product.
Do not create a measure for sales, revenue, or conversion from listing price, rating, or reviews alone. Those concepts require appropriate transaction or platform data.
Summarize with PivotTables before choosing charts
Use PivotTables to check the shape and size of the data before designing the dashboard. Where fields permit, compare product counts and price, discount, rating, and review measures by category or documented price band.
- Show the number of products behind each category or band, not just the average.
- For ratings, show the rating distribution and review counts alongside any average. A small group can produce a fragile average, and a perfect rating based on very few reviews should not appear equivalent to a rating supported by many reviews.
- Inspect missing-value counts so that readers can see whether a comparison excludes products without a rating, price, or discount.
- Use consistent filters and definitions across summaries so that comparisons are not based on different subsets without explanation.
Averages are a starting point, not a complete description. When the data supports it, include distributions or ranges so that a handful of extreme values does not hide the pattern among most listings.
Build an interactive dashboard that answers a decision
Choose a few views that help a reader compare products in the file; do not add charts merely because Excel can create them. The case study describes an interactive dashboard, but the workbook itself has not been independently inspected here, so the exact layout and controls may differ from one copy to another.
- Use a category comparison for product counts and the price or rating measures available.
- Use a price-band or discount view only if the source fields and calculation rules support it.
- Include review volume when showing ratings, so readers can judge how much review evidence sits behind a score.
- Add slicers or filters only for fields that exist and have consistent values in the dataset.
- Label currency, rating scale, date or snapshot period, and the denominator behind percentages or averages.
- Make missing data visible, rather than allowing blanks to disappear without explanation.
Keep the underlying PivotTables and calculations traceable. A dashboard should make the analysis easier to explore, not conceal how the results were derived.
Interpret the case study’s reported relationships cautiously
The case-study author reports a weak relationship between discounts and reviews, almost no linear relationship between ratings and reviews, and a stronger negative relationship between price and rating. The author also notes that perfect ratings can occur alongside very small review counts and that discounting did not inherently correspond to worse perceived quality in that analysis. These are reported observations from the case-study dataset; they have not been independently recalculated here and should not be generalized to all Jumia listings or shoppers.
Correlation describes association, not cause. For example, a relationship between price and rating does not show that price caused a rating difference. Category mix, product type, seller, review volume, timing, and other factors may affect what appears in a comparison. Do not turn a correlation into a sales-effect recommendation without additional evidence.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Keep product-file findings separate from Jumia company results
Jumia’s public filings provide business context, but those company-level figures are not findings from the Excel product dataset. Jumia Technologies AG’s 2025 Form 20-F says that more than 91% of items sold in 2025 were offered by third-party sellers, and describes categories including phones, electronics, home and living, fashion, beauty, and other goods. Those facts do not establish the composition or representativeness of the case-study workbook. See the 2025 Form 20-F.
The same filing describes platform ranking inputs such as seller tenure, seller score, revenue, product visibility, add-to-cart rate, and items sold, as well as promotional planning and Sponsored Ads. These are company-described mechanisms; they should not be presented as columns or factors measured by the product-analysis workbook unless that file actually contains relevant data.
Jumia’s interim report for the six months ended June 30, 2026 reported 6.4 million annual active customers as of that date, 12.1 million physical-goods orders during the half-year, and $427.5 million in GMV for the half-year. GMV was up 25.0% year over year from $341.9 million; the report gave growth of 27.1% when adjusted for perimeter effects related to Jumia’s Algeria exit. These are dated company-level operating figures, not product-level dashboard results. The report also described strength in fashion, beauty, and home and living, while phones were affected by memory-chip and CPU shortages and Gulf air-freight disruption; comparisons reflected the Algeria exit and recast prior periods. See Jumia’s second-quarter 2026 management discussion.
Jumia said it discontinued quarterly disclosure of total payment volume and payment-gateway transaction KPIs effective Q1 2026, in connection with its shift toward physical goods and the 2025 discontinuation of the standalone JumiaPay App, except in Egypt for legacy payment partnerships. Older payment metrics should therefore not be treated as current primary KPIs without that context. See Jumia’s Q1 2026 results release.
Quick Recap
What to include when you report the results
- Dataset source, collection date, geography, coverage, and what one row represents.
- Cleaning rules, exclusions, and definitions for calculated measures.
- Counts and denominators for category comparisons, averages, and percentages.
- Missing-data treatment and any limitations on interpreting ratings or reviews.
- A clear distinction between observed association and causal explanation.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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