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How to Get Accurate Product Data Entry for your Ecommerce Catalogs

How to Get Accurate Product Data Entry for your Ecommerce Catalogs
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.

Impact of Incorrect Product Data Entry

Product data entry challenges

Source: sana-commerce.com

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.

Source: hbr.org

How to Get Accurate Product Data Entry for your Ecommerce Catalog Management

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.

1. Automate data transfer to digital catalogs

Automate data transfer to eCommerce catalogs

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:

  • Optical Character Recognition (OCR) allows you to accurately extract product prices, product features, manufacturer details etc.
  • Barcodes help maintain product hierarchy & accurately update product inventory in real-time.

Custom built automated data entry solution unearth product details from intricate texts. Prioritize automated data entry for:

  • Repetitive and bi-direction data entry between multiple sources and catalog.
  • Reports associated with catalogs for respective eMarketplaces.
  • Workflows that facilitate flows of crucial data between internal and external environment.

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 →

2.Conduct data profiling

Conduct data profiling

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:

Quality ecommerce product data entry to boost your business’s growth.

Consult our Experts →

3. Build robust import/export rules

Build robust import/export rules

For moving your eCommerce catalog database across systems you need strong data import/export rules.

Steps to import/export catalog data:

  • Begin by importing/exporting individual catalog contents like data source connections, database schemas, logical models, drill-through reports etc.
  • For importing/exporting specific elements from your catalogs, ensure that descendant elements are also selected according to robust field-mapping rules. Automated data entry solutions prove extremely helpful conducting import/export tasks while adhering to pre-defined rules.

4. Normalize third-party ERP data

Always normalize third-party data prior mapping to ERP

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.

5. Ensure accuracy in field-level mapping

Ensure accuracy in Field-level mapping

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:

  • Review all data fields for mapping accuracy.
  • Identify fields with mismatch data.
  • Ensure that catalog headings are unique for each field.
  • Set rules detect and delete duplicates for previously mapped fields.
  • Analyze fields that can accept multiple values and tagged fields.

Practical field-level mapping when building a good catalog:

Catalog Field Mapping Part 1 Catalog Field Mapping Part 2

Source: Salesforce.com

6. Investigate product-variant matrix accuracy

Regularly investigate product-variant matrix accuracy

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:

  • Have flexibility to configure matrices globally or product-wise.
  • Allow admin rights to configure matrices only to important stakeholders.
  • Product-variant figures must tally with inventory numbers.
  • For data mismatch, reconciliation & identification of root cause of discrepancies must be done.
Variant Groups Details

Source: Americommerce.com

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:

variant matrix details

Source: Americommerce.com

7. Have a strong error identification, prevention and correction framework

Have a strong error identification, prevention and correction framework

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:

  • Data acquisition error: Error caused by inexperienced/ill-trained data entry operators.
  • Attribution error: Fields are attributed wrong values making data inconsistent or incomplete.
  • Variations: Catalog data doesn’t correspond to actual inventory figures.
  • Data manipulation errors: Errors don’t creep in during the capture phase only. To suit catalog visibility requirements, you may have to manipulate original data, and while doing so you create an entry for errors.

Two-fold approach to drive analysis:

Data Quality checklist
  • Error cluster analysis: Narrow down the error sources by analyzing inaccurate data sets.
  • Monitor progress for error patterns: Make data surveillance and improvement a routine to make effective and accurate error identification and prevention a part of your data entry process.
  • Data-quality checklist: Conduct a robust data quality check for product data entered in to any eMarketplace catalog. Strong data-quality checklists act as a harbinger of successful catalogs, weak checklists degrade product information quality, resulting in even removal of your products from eMarketplaces.

8. Follow eMarketplaces’ guidelines

Follow eMarketplaces’ guidelines

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:

  • Validate data authenticity and relevance to deliver trustworthy customer experience.
  • Listings, images, product tags, product features in your catalog should not be misleading.
  • Understand how you can list your products on an eMarketplace, I.e., to list your products on Amazon, you must use excel-based inventory files.
  • Check what are listing regulations for specialized products that require additional information.
  • Check if the eMarketplace aids in image capturing and creating digital catalogs through eCommerce data entry service-providers.

Employ Data Entry Professionals with Domain Expertise

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 →

Conclusion

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.

About Author:

 heads the digital content for Hi-Tech BPO, an India based firm recognized for the leadership and ability to execute innovative approaches to data management. Hi-Tech delivers data solutions for all the aspects of enterprise data management; right from data collection to processing, reporting environments, and integrated analytics solutions.

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