Data Annotation for ML Projects – 5 Most Effective Ways to Label Data
Managing rich and consistent product data is the biggest challenge for online merchants. eCommerce companies seek a strategic combination of human skills and technologies for a robust product data entry process.
eCommerce trends are fast changing against the backdrop of COVID that badly hit economies and forced populations to stay indoors. Touchless shopping channels have gained preference over others to make purchases. This accelerated growth in online shopping has compelled eCommerce players to put their catalogs in shape to capitalize on the opportunities offered by new market dynamics.
Catalogs bridge the gap between visitors and products, ultimately impacting the buying decisions of customers. Product data, visual or textual is a key performance driver for any eCommerce catalog. That makes accurate product entry an imperative for higher conversions, sales and business growth – a factor that online merchants cannot ignore.
Data entry errors in purchase orders and invoices resulted in a massive goof up in the procurement process of AT&T in 2002. A key production line was shut down and eventually the company went out of business.
Ever expanding product range latched to soaring data size, and challenges of regulating complicated product categorization is a nightmare for eCommerce merchants. The answer to these challenges is robust and accurate data entry process, which revitalizes your eCommerce catalog management.
Using advanced data capture tools like OCR, MICR, OMR etc. ensures accuracy in eCommerce product data entry.
Technologies that streamline data transfer across stages in eCommerce catalog management:
Custom built automated data entry solution unearth product details from intricate texts. Prioritize automated data entry for:
Programmable bots and macros used to automate data capture process right from receipt generation to order dispatch helped an energy supplement food manufacturer in Europe to meet the 20-minute order entry timeline.Read how →
Data profiling allows you to effectively review if your data is complete, correct, unique, reasonable and consistent, thereby reducing errors progressively.
Domino’s, the eCommerce company selling pizza, had a team of 35 data scientists but still struggled to manage 17TB of data from more than 14000, locations. Data profiling helped them integrate 85,000 structured and unstructured data sources and have that single view of customers and global operations. It improved their business performance from logistics to financial forecasting.
With soaring data size, automated data profiling workflows are critical for eCommerce players to flag incorrect data and send it for review without manual intervention.
Unique data profiling for eCommerce companies:
Validate data and format consistency to check if fields like SKU, item number, etc. have requisite number of, and correct digits.
Check what records and fields are potential error sources; giving you insights about what systematic issues exist in your data.
Validating complex relationships across data tables and maintaining referential integrity amongst fields in real-time.
Quality ecommerce product data entry to boost your business’s growth.
For moving your eCommerce catalog database across systems you need strong data import/export rules.
Steps to import/export catalog data:
Suppliers aren’t obliged to ensure data standardization. Due diligence of format checks, authenticity checks, spell checks etc. becomes online retailer’s responsibility when product data comes into central database from multiple suppliers.
Leveraging manual data entry may ensure data standardization at the entry point through in-field validations, however, use of scripts and macros enriches third-party data in-real time. Include data consistency as a KPI to evaluate supplier performance and maintain relationship.
Advanced attribute mapping ensures in-depth customization. Collecting your eMarketplace platform’s API meta-field data enables you to link attribute fields across eMarketplaces & the platform.
Here is how you can accurately map catalog headers to requisite field names:
Practical field-level mapping when building a good catalog:
Maintaining a product-variant matrix might not sound challenging, but volume of product data and intricate product hierarchy adds complexity to it. Therefore product-variant matrix accuracy must be validated on a regular basis.
Best practices to ensure accuracy of a product-variant matrix:
Before allocating variants to products; create a variant group. It is one of the most important elements in product-variant matrices.
Product-variant matrix allows multiple ordering variant combinations:
Discovering errors and correcting them is not enough. Identifying the error and capturing the source of error is required to address errors happening repeatedly in entering accurate product information.
Potential sources of data errors that can affect eCommerce catalog:
Two-fold approach to drive analysis:
Prime eMarketplaces like Amazon clearly mentions in their selling polices and seller code of conduct, and violation of any of those principles can take away your privileges to sell. Align your data entry procedures not just along a given eMarketplaces’ guidelines, but also along the changes that eMarketplaces regularly make in the guidelines.
Adhere to eMarketplaces’ guidelines strictly:
E-retail sales are expected to grow up to $4.8 billion by 2021. It is because buyers are skeptical about purchases from brick and mortar and prefer buying products from online channels. Digital product catalogs are critical to the success of online retailers. Ecommerce players should make catalog data entry a vital aspect of their go-to-market strategy.
The online catalog of your eCommerce business requires frequent and real-time updates. It is imperative to hire data entry professionals with a robust and agile data entry process that ensures timely updates, accurate data entry, and careful quality review.
eCommerce data entry solutions are a combination of human skills and automated tools backed with RPA techniques. These solutions are designed to smartly enter product data to online catalogs meant for eCommerce shopping platforms including Magento, BigCommerce, etc. and online marketplaces such as Amazon, eBay, Sears, etc. They not only possess expertise in data processing, but also have strong knowledge of eCommerce catalog management.
Real-time data entry of 36 contents for more than 1000 food product images in 550 various angles helped the customers of an e-retailer to make evidence-based decision when purchasing from thousands of food products.Read how →
eCommerce catalogs govern customer journey over online stores, and virtual catalogs represent the eCommerce website. From the moment a customer lands onto an online store to making the final checkout; it is the accurate product data information of your eCommerce catalog that helps them make evidence-based purchase decision and improves the satisfaction level. Higher customer satisfaction is the proof of effective catalog which in turn positively impacts your conversions and sales.
Strong catalogs compel customers to buy and keep them loyal to your online store, not allowing them to leave at any stage in your sales funnel. But building a high performing eCommerce catalog is not a cakewalk. Robust and accurate product data entry can script a successful journey towards building a successful eCommerce business.
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