This article is about giving you an understanding of datasets and what purpose they serve. It will provide you with ideas of how different dataset reports can be used in combination or independently for different purposes and information needs.
We have tried to categorize these dataset reports below based on their use cases:
Lets dive into details and find which reports can be used or combined together for above mentioned purposes:
Product and category performance
Do you want to see your brand performance in terms of handling returns on product and category level?
Financial summary of returns- See how well you are doing financially.
Return request details with current tracking status: See the brand performance for different categories and products by utilizing this dataset.
Return rate by market- See how your brands performing in biggest markets by analyzing market shares and return rates.
Partial and full return statistics: It gives an high level historical view on number of order vs return your brand is handling.
Financial Impact Analysis
Gauge the revenue loss due to returns with the help of following return statistics:
Financial summary of returns: The value of the orders returned, inspected (not refunded) and not refunded by the return request date to help you forecast your refund
Refund transaction report: Get an overview of lost revenue due to refund and store credit per order ID, processed via yayloh
Return shipping label details: Use this to track labels generated in yayloh and cross check with your 3PL shipping label generation invoices.
Collection level report is to see revenue and revenue lost of the each collection.
Marketing campaigns
Do you want to go extra mile in customer satisfaction and want to reach out to customer or run personalised e-mail marketing campaigns? You may start to explore below dataset report/s:
Customer comments A list of all comments made by each customer for each SKU. Utilise customer emails and comments from the 'Customer comments' dataset to run personalised campaigns.
Returns forecast
Sometimes you want to know your incoming returned product to plan your inventory and adjust customer expectations for exchanges. For example, an exchange for a product that is out-of-stock in the warehouse is requested. With this dataset, you can see if it is coming back in stock and will be available for exchange.
Incoming returned products by tracking status: Use this dataset report to monitor incoming returns and plan accordingly to better manage stock and drive customer satisfaction
Return request status: See how many returns your team working on currently, what's done and what's pending. Use this to utilize your headcount efficiently on daily basis.
Possible return based on double sizing: This dataset indicates the products that would be returned in future.
Root Cause Analysis
Do you want know what went wrong? Where is your brand lagging behind? Use the following reports to know:
Customer comments Utilise the information to know what your customer think about the product and find the most common reason a product is being returned. Update size guides and support your design teams by analysing the most frequent return reasons and comments
Product level report: Use this report to analyze the most returned product variants. know your products return rate to zero in the issues with the products.
Top reason by product: See the top reasons of the product being returned along with number of return count.
Top 50 returned products- Find the root cause for top 50 returned products.
Custom analysis
If you are an analytics geek and want to create your own reports, access to:
Daily google export for additional raw data.
Return request details with current tracking status dataset is also rich source of data, which you can use to build your own reports.
Efficiency/Productivity
In case you want to assess the efficiency of your internal teams, see for below reports:
Inspection and refund speed statistics: Monitor your team’s efficiency in processing and handling returns.
Inspection status: Use this to see the efficiency of your Warehouse teams in performing inspections.
Return request status- Find the count of return requests for each status tab. Use this dataset to track the return requests on a daily basis and see how efficiently your teams are handling return requests.