In the context of online pharmacies, accuracy of drug data is essential for the operational frontline, not just a back-office function. It aids in avoiding unnecessary operational costs due to failed deliveries, pricing disputes, and economically protecting them. For Indian e-pharmacies, where practice leads to the regulatory changes, varying pack sizes, and similarly branded products, one of the most effective methods to attain operational efficiency is a comprehensive, reliable, and canonical drug database to help avoid RTO (Return to Origin) and all consequential downstream operational, financial, and reputational impacts.
Importance of RTO as Key Performance Indicator for e-Pharmacies
RTO (Return to Origin) in e-pharmacies has several unique and major issues in comparison to other domains, such as fashion or electronic retail. In addition to other RTO issues such as logistics and customer service cost, reversed orders in e-pharmacies can lead to the loss of expiry controlled, prescribed, and compliance risk medicines (that are billed differently under MRP, government pricing controls, and insurance reimbursement) in addition to the lengthy and costly RTO processing. In India, e-pharmacy RTO rates can go as high as 40% in risk to capture (Cash on Delivery and remote pin orders). RTO negatively impacts the viability of e-pharmacies.
RTO in pharmacies can occur for multiple reasons including;
- Delivery of an incorrect drug or packaging (wrong brand, weaker/stronger pack size).
- Delivery of an unexpected or not agreed upon drug (Cash-on-Delivery price MRP differences and price control MRP).
- Delivery of drugs that require a prescription, or are controlled, and compliance risks.
- Confusing SKUs (sound-alike and look-alike brand).
Inaccurate medication data and its effects regarding RTOs: The routes
The accurate metadata of drugs has three connected ways of lessening RTO: alignment of expectations, compliance with regulations, and clarity in operations.
Expectation alignment: What you see is what you get
If medication listing has incomplete data, e.g. strength (mg), formulation (tablet/syrup), or pack count, customers will feel like they received an “incorrect” product and will cancel or refuse to accept the delivery. According to industry research, approximately 23% of product returns across all divisions of e-commerce is a result of incomplete and wrong product description. This is even more the case with medicines where substitution is a sensitive issue.
Anticipation of clarity with pricing and billing
The pricing of medicines in India involves a mix of government-mandated pricing, retailer profit margins, and real-time discounts. Customers refuse Cash on Delivery (COD) orders if the price presented differs from the price paid at delivery – or from insurers/aggregators. Inaccurate, authoritative Drug Database entries that include MRP, pack sizes, and regulation flags reduce these mismatches.
Gating Based on Regulation and Prescriptions
Many products necessitate prescriptions and have restrictions on sales and listings in registries. To avoid RTOs due to sales attempts for products that cannot be sold due to regulatory reasons or pharmacy out-of-stock as a result of integrating the regulatory data sources based on the CDSCO, NPPA price notices, and formulary in the catalogs, integration of regulatory data sources is a solution.
Characteristics of practical data model (what accurate drug data look like)
To enable the operational teams to work effectively, a practical and simplified dataset is necessary. For each SKU, the following is the minimum necessary data:
- Official generic name, brand name(s), and trade name disambiguation
- Strength and unit (e.g., 500 mg), formulation (tablet, syrup, injection)
- Pack size and net quantity (e.g., 10 x 10 tablets)
- Manufacturer name and license/approval reference (CDSCO number where available). ([CDSCO][4])
- Regulatory flags: prescription required (Y/N), controlled substance, FDC details,
- MRP, NPPA (National Pharmaceutical Pricing Authority of India) applicable price dead, insurance codes / e-claim identifiers
- GTIN / barcode and internal SKU for logistics
- Canonical therapeutic classification (ATC or equivalent) to avoid substitution errors
When this model is applied throughout the catalogue (and made available through a programmatic Medicine database API), it creates a single source of truth for all product details, checkout, and delivery documents.
Operational lever single source stops expectation mismatch.
Reachable benefits and KPIs we can track
Implementation of a canonical Indian Medicine database or a validated India Drug Database will lead to a positive impact on:
- RTO rate (especially COD cancellations and delivery refusals)
- Customer service requests regarding the “wrong product” issue
- Increased accuracy of stock levels as a result of reduction of returns and mis-labelled stock
- Increased speed of resolution for disputed deliveries (due to less investigations)
PIM (product information management) research for your industry indicates companies that manage to improve their product data record returns in the low-double digits and improve customer retention; in the context of pharmacy the improvements are often higher and the impact on customer retention even larger due to the more rigid regulation around acceptance and safe handling of medications.
Effective Implementation Patterns (Operational Playbook)
1. Always Start with Authoritative Registries
Always ingest CDSCO approvals, NPPA price lists, and your hospital formulary(s) as baseline records, to avoid selling unapproved or mispriced products. This will prevent RTOs due to regulatory rejection or mispriced products.
2. Normalize and Disambiguate SKUs
A common issue facing pharmacists is the accumulation of duplicate SKUs due to the same molecule being categorized under different brand names and different pack descriptors. The creation of a SKU normalized layer will provide clarity to warehouse pickers, frontend users, and invoicing systems by consolidating the mapping of barcodes, GTINs, and Manufacturers’ codes to a single product.
3. Medicine Database API for Single Source Updates
programmable clean data is accessible to pull from a single record across the storefront, mobile app, seller dashboard, and logistics system. Important fields (prescription flag, MRP, pack-size) must be pushed to the checkout to ensure customers receive the relevant information prior to payment confirmation.
4. Business Rules & Pre-Checks
Implement a business rule that requires verification for high-risk SKUs (new drugs, restricted items) before they can be ordered using cash on delivery, prescription uploads are mandatory for flagged products, and provide pin code level checks for cold-chain constrained products before an order is accepted.
5. Constant settling of differences with outside institutions
Every night, subscriptions to updates to the CDSCO/NPPA should be reconciled in order to capture approvals, changes in price, or FDC additions that will cause delivery inconsistencies. Automated alerts concerning any modified pharmaceuticals in your catalogue help you avoid surprises in the last mile.
Illustrative (anonymized) example
Let us imagine an anonymized e-pharmacy network in one of the regions that has combined a verified pharma database India feed with 8,000 normalized pack sizes. They achieved the following in a period of 3 months:
- 12-15% decrease in COD cancellations attributed to “wrong product/strength”.
- About 18% decrease in customer service calls concerning price.
- 50% lower time spent in reconciling the returns concerning faster reverse logistics processing.
Improved clarity, MRP mismatch correction, and the display of prescription flags at checkout (all attributable to one, single, authoritative dataset powering the storefront and operations) are the reason for these improvements.
Choosing the right data provider
As you compare data providers or create an internal source, consider:
- Coverage: Indian Medicine Dataset coverage for finished doses, FDCs, and branded generics
- Update cadence: Daily or real-time updates with CDSCO/NPPA
- Data model: Regulatory flags, GTIN, MRP, pack size, and manufacturer license numbers
- API stability along with SLAs for latency and error rates
- Proven integrated references for e-pharmacy/hospital procurement
A quality feed is not simply many rows of names, but rather the operational glue that inhibits RTO.
Last Recommendations
- Consider drug data as product safety: take the time to implement the canonical Drug database India and place it everywhere it needs to go in your front ends and in your logistics systems.
- To prevent last-mile surprises, display at checkout (strength, pack size, prescription requirement, MRP).
- To prevent regulatory mismatch, automate reconciliation with CDSCO and NPPA.
- For consistent access to the same data, use API-driven distribution across all systems. For this, consider third-party Medicine database API providers if an in-house solution is not possible at once.
When online pharmacies have accurate data about the drugs available, it leads to immediate improvements in operational efficiency, such as lower failed deliveries, reduced costs associated with reverse logistics, and increased trust from patients. These improvements lead to lower RTO and increased profitability.
