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E-commerce and Data Quality: 5 major issues

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In 1985, Coca Cola launched an improved version of its iconic drink, soberly named “New Coke”. Everything pointed to a huge success: the taste was validated by a consumer panel, the quantitative studies were highly positive and the marketing budget was huge. ” I have never been as confident as I am today, “, said Roberto Goizueta, CEO of Coca Cola, the day before the launch of the new product.

The launch of the “New Coke” product is now considered one of the biggest commercial failures of all time.
BigCommerce explain that this failure is mainly due to “poor data quality” ».

In fact, a series of errors and approximations skewed the decision making process.


Thirty years later, we live in a world where the amount of data produced on a daily basis has probably multiplied by several billion. Data quality has become a critical element in business, especially when most or all of the business is done online.
The momentum is not about to slow down:  according to Gartner, 65% of companies are expected to complete their transition from an intuition-based model to a Data-Driven one by 2026. What are the challenges of data quality and e-commerce? What are the best practices to leverage the full potential of Data for business performance?


6 KPI for Data Quality

Data Quality refers to the tools, processes and techniques used to measure the accuracy and usefulness of a set of data for business purposes. The definition of “quality” differs depending on the industry, but Data Quality analyzes data sets based on six key criteria:

  • Accuracy : Is the entire data correct?
  • Uniqueness : is each entry unique? Are there duplicate entries?
  • Completeness: Is all the data needed for the decision available?
  • Usefulness: Is the data actionable? Is it useful for decision making?
  • Reliability: Is the data trustworthy? How does it compare to data from authority sources?
  • Timeliness (or freshness): Is the data current?

If you want to learn more, you can browse our Data Quality glossary. By definition, e-commerce implies the management of a higher volume of Data than in a physical store (or Brick & Mortar).

In fact, each transaction is associated with an email address, a phone number, a name, a postal address, a Facebook or Gmail account, etc. This allows you to track consumer buying behavior to streamline marketing decisions and boost your sales, whether it’s for first-time purchases, cross- or upselling, or to build customer loyalty.

E-commerce: data quality’s 5 major challenges

Data quality affects the entire e-commerce value chain, from product recommendation to inventory management, including the performance of promotional campaigns, proper delivery of packages and after-sales service. The stakes are high.


#1 Data Quality to recommend the right products

According to Invespcro, 54 % of e-retailers believe that product recommendations are “the key factor” to improve the average customer basket. Many retailers use specific tools to recommend the right product to the right customer at the right time.

The problem is that these tools use raw data, and any error would cause systemic bias that can derail the entire recommendation strategy. A female customer who is recommended male products (or the other way around), recommendations for products already purchased or out of season, etc.

Reliable data on the profile, purchase history and location of the customer will allow machine learning algorithms to become more relevant, and even turn product recommendations into a powerful sales driver.


#2 The importance of quality data for better inventory management

Accurate data on your customers’ buying behavior will allow you to better anticipate orders, whether you’re estimating the time needed for a “refill” purchase for consumable products, or identifying a seasonal factor.

This will allow you to adjust your inventory accordingly to avoid stock-outs or the accumulation of stocked products at a high cost.


#3 Reliable data to avoid delivery errors

Data quality directly impacts the logistics performance of online stores (and physical stores). An error in the postal address or a field in the wrong format is all it takes to trigger a chain of problems: undelivered packages (or packages delivered to the wrong address), returns, manual processing of the database to identify the error, increased demand for customer service, negative reviews on specialized platforms and social media, customer loss, brand image damage, etc.

Remember that 87% of French people check customer reviews before making a purchase decision (Ifop). Obviously, your potential customers will be scared away by reviews about packages that don’t arrive at the right address. Which brings us to the next point…


#4 Reliable data to authenticate customer reviews

Is that unflattering but prominent review writen by a “real” customer that actually bought from you? If your database is shaky, checking it will be laborious, and you won’t have arguments to answer this review and reassure your potential customers.
Reliable data allows you to match different elements of the review with the purchase history, characteristics of the purchased product, origin (supplier), possible delivery incidents, and customer interaction with customer service or after sales service, etc.


#5 Quality data = high ROI marketing campaigns

E-mail addresses and phone numbers are both valuable and sensitive information in your data capital. All it takes is one poorly calibrated emailing (or text message) campaign to trigger a series of opt-outs, with the loss of hard-earned leads through massive LeadGen efforts. Data cleaning is both a prerequisite for marketing campaigns (curative on existing data through deduplication, correction and enrichment) and an ongoing process through real-time validation of first-hand data as it is entered. The goal is also to capitalize on each interaction with customers and prospects to qualify, enrich and update the database.


Data Enso’s expertise at the service of e-retailers

Whether in a phygital configuration (physical point of sale and e-commerce) or Pure Player (exclusively digital activity), Data Enso uses its technology and expertise to turn your Data capital into a major competitive advantage.

We support e-commerce professionals throughout the entire process, from auditing their systems to implementing appropriate solutions to:

  • Improve the reliability of the collected data: : data entry assistance, real-time automatic correction
  • Make sure that the data collected is accurate : email, phone and company verification tool in real time
  • Enhance databases : collect company information sheets with few initial fields to complete
  • Optimize collection systems by reducing the number of steps to complete
  • Clean and correct existing data with our batch solution.

Discover our solutions for e-merchants or test us!