Data Entry India

About Data Entry India

Data Entry India is a New Delhi-based data entry and data processing outsourcer, operating since 2006 as a division of Data Outsourcing India, an Indian IT/BPO company. With over 18 years in the business and a self-reported client base of 2,000+, this is a focused, mid-market offshore provider built around one core proposition: converting raw, unstructured data into usable, organized formats at offshore cost levels. The service portfolio is broad within its category. On the core data entry side, the company handles manual, online, and offline data entry; image data entry; form processing; double-key data entry (where two operators enter the same data independently to catch errors); image indexing; and data capturing from both hardcopy documents and digital files. For appraisal-industry clients, it offers WinTotal appraisal data entry, a niche capability worth noting if you operate in real estate or property appraisal workflows. The e-commerce track is a clear specialty. The team handles product data entry and catalog processing across major platforms, Amazon, eBay, Magento, Shopify, and OpenCart. Specific services include product listing creation, promotional product entry, product image editing and resizing, e-commerce content management, and order processing. For a retailer or online seller dealing with large SKU volumes and slow internal catalog operations, this is the kind of focused, platform-specific experience worth probing further, particularly whether they have dedicated teams per platform or generalist agents switching between them. Web research services cover web data scraping, data mining, mailing list compilation, research and analysis outsourcing, and offshore web research. These shade into knowledge process work, sourcing, compiling, and validating structured data from the web for outreach lists, market research, or lead databases. The data quality service line includes data cleansing and scrubbing, de-duplication, standardization, enrichment, verification and validation, mailing list cleanup, email validation, and email appending. These are valuable services if your core problem is a dirty CRM or unreliable contact database, though outcomes depend heavily on source quality and the vendor's validation methodology. OCR and proofreading services handle the conversion of scanned or image-based documents into editable formats, a common requirement for companies dealing with legacy paper records, insurance forms, or legal documents. Data conversion services extend this to document, PDF, Word, Excel, HTML, and other format transformations, plus document scanning and indexing. Photo editing is a full sub-practice: photo enhancement, image masking, clipping path services, photo cutouts, background removal, photo retouching, and image resizing. For e-commerce sellers in particular, bulk product image editing is often a hidden operational bottleneck, and having it bundled with catalog data entry under one vendor can simplify coordination. The company is ISO certified and states GDPR data protection compliance. ISO certification matters for buyers who need an auditable quality management framework; GDPR compliance is relevant if you're passing European resident data through the vendor, though I'd want to verify the specific ISO standard (likely ISO 9001 for quality management) and understand the practical data handling workflow: who accesses the data, on what devices, and what happens when an operator's engagement ends. For sensitive contact data or personally identifiable information, these questions are not optional. Pricing is handled via quotation request, and the site mentions a free trial, standard practice in the Indian data entry market. Engagement models include a 'hire full-time data entry teams' option, which suggests a dedicated FTE or per-seat model alongside project-based work. The free trial is a useful risk-reduction tool; I'd treat it as a quality test, not a sales formality, run a sample of your actual data, not sanitized test data. The company explicitly supports all file formats, both hardcopy and digital, which matters if your process involves a mixed input environment. Languages and timezone specifics aren't listed, but as a New Delhi-based team, expect IST (UTC+5:30) delivery, which means turnaround is effectively overnight for US clients sending data end-of-day, and same-day for UK/European clients. Who fits this vendor best? Small to mid-sized e-commerce businesses with high catalog or product listing volume; companies with large backlogs of unstructured or scanned documents; marketers dealing with dirty contact lists; real estate or appraisal firms needing WinTotal-specific support; and any organization that needs a cost-efficient offshore data operations team without the complexity of a full-service BPO engagement. The 2,000+ client figure, if accurate, is meaningful for a data entry specialist, it suggests process repeatability across a range of client types. What I'd verify before signing: First, the ISO certification number and scope, confirm it covers the actual data entry operations, not just a parent entity. Second, their QA process in detail, double-key entry is a good signal, but ask about error rate targets, how QA scores are reported back to clients, and what happens when error rates exceed the agreed threshold. Third, the staffing model for dedicated teams, team-lead-to-agent ratio, how replacements are handled, and whether your account gets a named point of contact. Fourth, data security specifics: where data is stored, access controls, whether operators work from office or remotely, and what the offboarding process looks like for data deletion. Fifth, platform experience depth for e-commerce, ask for examples of similar SKU volumes and complexity to yours, and whether they've handled product attributes for your specific category. The sales deck likely shows low per-record or per-hour pricing and a long client list. What matters more is accuracy rate on your specific data type, rework policy, and whether the reporting gives you visibility into daily output and error patterns. Cheap data entry becomes expensive when you have to clean up inaccurate records downstream.