This article originally appeared on YourStory.

Data is crucial for ecommerce businesses to thrive. The abundance of data from customer interactions, online transactions, and market trends plays a significant role in driving ecommerce growth.

However, there’s a dilemma. How can ecommerce businesses effectively leverage their data amid privacy and reliability concerns?

These businesses have a staggering amount of data at their disposal—store data, ads data, customer data, inventory data, purchase and order data, fulfilment data, etc. While having a lot of data is great, its real value is in the insights it can provide to ecommerce brands. Brands must ensure their data is reliable to extract accurate insights and make well-informed decisions.

For instance, an ecommerce business owner wants to analyse their data. The first step is logging into all the platforms they use—their website, various marketplaces like Flipkart and Amazon, ad platforms like Meta and Google, and more—and downloading the data.

To utilise this data effectively in the ecommerce equation, brands can use a simple formula that gives them a comprehensive overview of their business performance. The data needs to be well-organised, and the entire process requires a lot of effort. Even a small mistake in the calculations could result in drawing incorrect conclusions.

While sophisticated algorithms play a crucial role in ecommerce data analysis, the outcomes depend a lot on the quality of the underlying data. Even the best algorithms will generate inaccurate or misleading results without clean data.

One of the biggest challenges for ecommerce brands is getting a clean set of data. Why? Firstly, the data is vast. We have first, second, and third-party data scattered across various platforms and systems.

Secondly, it’s heterogeneous and exists in different forms—some are structured (CSV) and others unstructured (PDF). Brands can’t perform data analysis on this data; it has to have some structure for algorithms to work on it.

Adding to the challenges of getting clean data is how it’s acquired. Ecommerce brands use many methods for extracting data like APIs and browser extensions. While these methods get the job done, they also add additional layers of complexity, requiring robust mechanisms for data integration and standardisation.

Moreover, relying on manual data gathering, analysis, and reporting increases the risk of errors and inefficiencies. The manual handling of data consumes valuable time and resources. It also undermines the reliability and integrity of insights derived from such data.

In response to such challenges, many ecommerce brands have developed custom data management systems—built for specific needs and requirements. However, building and maintaining such systems require significant investments in resources and expertise.

From infrastructure costs to personnel training—creating a custom data management system demands a lot more than just technical skills. Companies must deal with the complexities of data governance, security, and compliance, ensuring their systems adhere to regulatory standards and best practices.

Additionally, ecommerce brands must prioritise data privacy to safeguard sensitive information and maintain customer trust. Brands can ensure data remains secure at rest and in transit by utilising encryption technologies, such as AES, thereby eliminating the risk of unauthorised access.

Moreover, ecommerce brands also face increasing scrutiny due to data privacy regulations. It's essential to comply with certifications like the EU’s General Data Protection Regulation (GDPR), Singapore’s Personal Data Protection Act 2012 (PDPA), and other regional standards to build customer trust and demonstrate a commitment to protecting their personal information.

With the Digital Personal Data Protection (DPDP) Act of 2023 in India, ecommerce companies must adhere to strict data collection, processing, and storage guidelines. The legislation emphasises transparency and accountability, requiring companies to notify users about the purpose and duration of data collection, further highlighting the importance of reliable data management practices. 

Moreover, as new rules and regulations on data privacy emerge, businesses must adapt their data management strategies to ensure compliance while maintaining operational efficiency. Failure to adhere to these regulations jeopardises customer trust and exposes companies to potential legal repercussions. 

With these developments, ecommerce brands must prioritise adopting certified tools and technologies that comply with prevailing data privacy regulations. Companies can mitigate the risk of non-compliance and enhance the security and reliability of their data management processes by investing in certified solutions.

Authored By Prem Bhatia, Co-Founder and CEO, of Graas.