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Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →To analyze Jumia products in Excel, first establish what each row represents and where the data came from; then clean and document the fields, calculate clearly defined measures, summarize them with PivotTables, and build a dashboard around comparisons the dataset can actually support. A public case study describes this workflow for Jumia product data, but its reported results are specific to that dataset—not a measure of all Jumia products, shoppers, or sales.
What the Jumia Excel case study covers
The public project, Building an Interactive Excel Dashboard for E-commerce Product Analysis, describes cleaning product data and presenting analysis in an interactive Excel dashboard. Its discussion includes product price, discount, rating, review volume, and derived measures such as discount amount and rating or price categories. The project is a useful example workflow, not an official Jumia dashboard.
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The available case-study description does not establish that its rows are a complete or representative sample of Jumia transactions. Treat a listed price as a listed price, not revenue; treat reviews as reviews, not purchases. Before interpreting any chart, confirm the workbook’s actual fields, row meaning, source, collection date, geography, category coverage, and whether prices and ratings are snapshots or span a period.
Prepare the data before analyzing it
1. Establish scope and provenance
Record the source and collection date, the countries and product categories covered, and what one row means—for example, a product listing rather than an order. If a field’s meaning or time frame is unknown, mark it as unknown instead of inferring it from its label. Check that the workbook version you have actually contains the fields needed for the analysis; files may differ.
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2. Audit fields and clean consistently
Inspect blanks, duplicate records, data types, currency and number formats, rating ranges, and unusual values. Decide how to handle each issue and document the decision. For instance, removing a duplicate listing can change item counts, while excluding products with no rating changes the population behind an average rating. Keep the original values or a recoverable copy so transformations can be checked.
Make sure numeric values are stored as numbers rather than text, and do not combine currencies or rating scales without a documented conversion. Check outliers against the source before removing them; an unusual price may be an error, but it may also be a valid product.
3. Define calculated measures
Use derived columns only when the source contains the required inputs. Write down each formula, its units, thresholds, and whether it uses original or cleaned values. A discount amount and a discount percentage are different measures; specify which one is being calculated and how the underlying price fields are defined. For price bands and rating groups, state the cutoffs so readers can reproduce the categories.
For rating analysis, retain review count alongside the rating. A high average based on very few reviews is not comparable to the same average based on many reviews. If data is missing, make that visible rather than silently treating a blank as zero.
Summarize with PivotTables before choosing charts
Build summaries that match the fields and coverage you have. Depending on the workbook, useful comparisons may include product category, listed-price band, discount, rating distribution, and review volume. These are possible analytical dimensions, not guaranteed columns in every Jumia export.
- Show the number of products in each group as well as averages or other summary statistics.
- For ratings, show the distribution and the number of reviews or rated products behind the result where available.
- For price and discount comparisons, state the currency, the discount definition, and the number of items included.
- Make missing or excluded values visible so a reader can see which records are absent from a summary.
Small groups can produce unstable averages. A category with a few products should not be presented as though its average were as dependable as one based on a much larger group.
Build an interactive dashboard people can interpret
Choose a small set of charts that answers specific questions, such as how listed prices vary across categories or how ratings and review counts are distributed. Add slicers or filters only for fields that exist and are meaningful in the dataset. Label chart units, the covered period, and the denominator—for example, whether a rating average uses all products or only products with ratings.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsKeep the dashboard tied to the cleaned data and its documented definitions. A filter should not obscure how many records remain in view; show counts so users can tell whether a striking result reflects a broad group or just a handful of listings. The case study describes an interactive dashboard, but the workbook itself has not been independently inspected here, so its exact layout, filters, formulas, and Excel compatibility are not established.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Interpret the reported findings 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 coincide with very small review counts in the dataset and that discounting did not inherently correspond to worse perceived quality in that analysis. These are reported observations from that project’s data, not general findings about Jumia shoppers or product quality.
Correlation describes association, not cause. A relationship between price and rating does not show that price caused a rating, and a relationship between discounts and reviews does not establish that a discount generated reviews. To interpret such patterns, examine the underlying distributions and sample sizes and account for the dataset’s scope. The case-study material does not establish a causal effect or a sales impact.
Keep product-level analysis separate from Jumia’s company results
Jumia’s public filings provide useful context, but company-wide figures cannot validate or be substituted for a product-listing workbook. Jumia Technologies AG’s 2025 Form 20-F says more than 91% of items sold in 2025 were offered by third-party sellers. It describes categories including phones, electronics, home and living, fashion, beauty, and other goods such as fast-moving consumer goods. Those facts describe the marketplace, not the composition of the case-study dataset.
The filing also describes ranking inputs and platform tools, including seller tenure, seller score, revenue, product visibility, add-to-cart rate, items sold, commercial planning for promotional events, and Sponsored Ads. These are company-described mechanisms; they should not be assumed to appear as columns in the Excel case study.
In its report for the six months ended June 30, 2026, Jumia 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. GMV was up 25.0% year over year, or 27.1% when adjusted for perimeter effects related to Jumia’s Algeria exit. The report describes a shift in category mix, with strength in fashion, beauty, and home and living, while phones faced memory-chip and CPU shortages and air-freight disruption through the Gulf; comparisons reflect the Algeria exit and recast prior periods. These are company-level operating measures, not results from a product-level Excel dataset. See Jumia’s second-quarter 2026 management discussion for the period and adjustments.
Jumia also said it discontinued quarterly disclosure of total payment volume and payment-gateway transaction KPIs effective Q1 2026, in connection with its focus on physical goods and its 2025 discontinuation of the standalone JumiaPay App, except in Egypt for legacy payment partnerships. Older payment metrics should not be presented as current primary KPIs without that context, as described in its Q1 2026 results release.
Quick Recap
What to include when reporting your own analysis
- Identify the source, collection date, geography, categories, and meaning of a row.
- Describe cleaning choices and calculated-measure definitions, including thresholds and exclusions.
- Report counts and denominators beside averages or relationships, especially for ratings and reviews.
- Label prices, discounts, time periods, and currency precisely.
- Describe correlations as associations; do not claim causation or sales effects without evidence that supports them.
- Separate observations from your workbook from company-level facts reported by Jumia.
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.
