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Why Data Quality is Important for Online Retailers?

By Chirag Shivalker|24th Apr 2020
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Importance of Data Quality for Online Retailers

Customer experience, both online and offline, directly gets affected by the quality of customer data. High quality data empowers online retailers with a single and accurate view of their customers, whereas low quality customer data brings in lot of inconsistencies and customer dissatisfaction. Customers today want to be considered and treated as an individual, but low quality or dirty data ensures that most of the retailers are unable to do so.

Online retailers fail to understand that only adopting data driven business models does not help them succeed. Data cannot drive your business if it is irrelevant, inaccurate and inconsistent. Data cleansing and enrichment helps online retailers to maintain data quality and decide what to sell – whom to sell, where to sell and when to sell. Statistic suggests that customers are loyal to individual experience and less loyal to brand:

  • 82% consumers in the USA stopped doing business with a company due to a poor customer experience.
  • 71% of consumers are lost due to poor customer service.
  • 68% of customers leave, because they noticed that the retailer was indifferent to them.
  • 47% of customers willingly take their business to a retailer within a day of experiencing poor customer service.
  • 66% of customers switch brands due to poor customer service/experience.

Why data quality is important for online retailers?

Maintaining the quality of customer data is beneficial to online retailers in various aspects right from product recommendations to maintaining inventory and avoiding failed deliveries engaging customers to running successful product promotion campaigns. This should not come to you as surprise, as the leaders you follow from your industry like Amazon, Walmart, and eBay; have been successfully maintaining the quality of their customer data. Data cleansing and enrichment is the answer.

On cleaning the customer data, all outdated information is updated whereas incorrect customer information is omitted. This not only improves the data quality, but also increases overall productivity. Ensuring the team is working on correct information will reduce unexpected costs associated to it and having consistent data will make sure your brand reputation remains intact.

Let’s check out the impact of data quality on other areas of online retailing:

1. High quality data for product recommendations

Forester suggests that 74% of businesses aim to be data-driven but only 29% succeed, as others have limitations in using quality data for analytics and derive insights. The quality of data used gives insights about:

  • Understanding or misunderstanding what customers buy and will buy next.
  • Being able or unable to identify accurate patterns in data, including skew and outliers.
  • Being able or unable to understand the customers who are interacting with the call-center or impacted by operational issues.

Even analytics solutions or machine learning algorithms use raw data to help you yield meaningful business insights. Just one error in the data of a visitor can derail your entire product-recommendation strategy. A female customer if is recommended male products may dissatisfy her and make her uncomfortable too.

If the quality of data an online retailer uses is good; assessing when users visit the site, where visitors are located and additional information about their preferences and likes becomes accurate. Online retailers can apply the best quality of data from across distributed platforms to achieve the best know how of their customer’s browsing or shopping history.

2. Quality data to empower inventory management

Quality customer data ensures that your online store stocks up adequately for the products your customers will buy. Not only this, it also ensures that you do not pile up products and end up paying to store more than what is required.

Cleansed data helps your retail store to predict what your customers buy, and how their preferences change seasonally to adjust your inventory accordingly. Incorrectly entered historic customer data can lead to inaccurate analytics, resulting in wasted money on inventory. Cleansing such customer data takes care of such errors and saves investment on inventory.

3. Cleansed data stops failed or delayed deliveries

Online retail industry has become hyper-competitive which requires delivery of merchandise at supersonic speed – and it is critical. No wonder Amazon introduced same day delivery for prime-members. They realized that the speed of delivery is potent enough to make all the difference when it comes to satisfied customers and unsatisfied customers. Customer’s accurate address details ensure timely delivery of purchased goods. Inaccurate data or in absence of data, orders will be delivered to a wrong address, or it will result in a failed delivery.

Accurate Most of the retailers have failed miserably to cope up with same day delivery strategy. But they were smart enough to lure in customers by facilitating them to order online and pick up in store, or order online and have the order shipped from the store nearest to their location; or order from an in-store kiosk for in-store pickup or home delivery. These facilities did make a huge difference; but the credit for it certainly goes to accurate customer data which ensured the fastest possible delivery times. It also enabled seamless and flawless multichannel and Omnichannel experience.

Retailers should remember that failed and late deliveries eat up into their sales margins and has a negative impact on customer loyalty. It also leads to damaged brand reputation, when customers express their views through social media platforms. Retailers aware of the importance of data quality avoid such unpleasant instances by prioritizing data quality.

4. Data quality ensures accurate product reviews

Ecommerce or online stores are the only place where our customers cannot see or touch the products. This makes it important for such customers to have access to and read accurate product reviews. These are the reviews written and posted by customers who purchased your products, and hence online retailer is required to ensure accuracy of these reviews. Weeding out fake reviews and the ones in unacceptable language; retailers need accurate and consistent data.

Quality data helps online retailers to cross-check if the customer who wrote the review bough the product, and the details/features of the product are included in the review align accurately with those of the product.

Data quality; a differentiator from competitive standpoint

For retailers, to survive and thrive, it is more than important to assess, improve and monitor the quality of customer data to ensure its accuracy and completeness. Their profit margins literally depend on it. However; most of online retailers are not equipped with the tools, technology, skills and resources required to cleanse and enrich customer data.

Data cleansing and enrichment proves to be time-consuming and tedious and hence retailers don’t pay due heed to achieve high quality customer data. On top of it, removing duplicate records and enriching it with correct, relevant and real-time information is an additional task for their in-house teams.

Third party data cleansing and enrichment solutions have attained immense popularity by saving time and money for retailers. Hands on with latest data cleansing techniques and years of experience, they clean, de-duplicate, standardize, normalize, verify and validate data of any size. Well trained and experienced data professionals go to the extent of checking the records manually as and where required, clean and update databases at regular intervals – irrespective of the volume and complexity.

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