Introduction

Consumers today share data across multiple channels as they research, review, and purchase products online. For retailers, this creates a vast, complex volume of data that they must navigate to extract essential business insights.

A recent study by Retail Systems Research reveals that most of the customer data retailers rely on is inaccurate, incomplete, and scattered across isolated storage centres, hindering their ability to make timely, data-driven decisions.

We explore the business case for data quality in retail.

The Challenge

Retail business leaders face a significant hindrance to their success – the lack of a single view of customers across channels. This hurdle affects their revenue-generating marketing campaigns, customer interactions, and stock control practices, with 54% citing it as their biggest challenge.

The Risk

With poor data quality, retailers risk investing in technology that provides inaccurate insights for various interconnected business processes and decisions. This poses a massive threat to the effectiveness of numerous retail functions.

The Impact on Key Areas

The consequences of poor data quality are evident in various areas of retail:

1. Loyalty Programs: 34.69% of respondents reported challenges with loyalty programs due to inadequate data quality.
2. Cross-Selling and Up-Selling: 24.49% experienced issues in cross-selling and up-selling efforts due to data quality problems.
3. Multichannel Marketing: 22.45% cited poor data quality as a challenge in executing multichannel marketing campaigns.
4. Order Fulfillment: 20.41% faced challenges in order fulfilment due to data inaccuracies.

What Defines Data Quality?

In the retail industry, the major problems affecting data quality include inaccurate information, missing demographic and contact details, inconsistent formatting, insufficient integration of data sources, duplicate records, and incomplete customer linking within the same household. Accurate data is crucial for driving marketing efforts to maximize revenue and cater to customer preferences effectively.

Understanding Customers Through Loyalty Programs

Loyalty programs offer valuable insights into customer buying patterns and behaviour. By linking customer loyalty cards to purchasing patterns, retailers can gain actionable insights into customer preferences, interactions, and opportunities for encouraging repeat purchases.

Data Quality Solutions for Retailers

Effective data analytics underpins successful loyalty programs. Retailers must access, integrate, and improve vast amounts of customer data daily. Implementing a data quality solution as the foundation of their technological infrastructure enables retailers to extract timely, reliable business insights. With accurate and standardized customer information, retailers can:

• Execute personalized omnichannel campaigns for increased revenue and conversions.
• Decrease campaign costs by removing duplicate records and verifying customer contact details.
• Enhance customer retention and loyalty through targeted offers based on accurate insights.
• Improve fraud detection with precise records of buyer behaviour.

Conclusion

In the digital age, data quality is paramount for success in the retail industry. Retailers must focus on quality rather than quantity to harness the power of data-driven decision-making and stay ahead in a competitive market. By investing in data quality solutions, retailers can unlock the true value of their enterprise information asset, creating a seamless and personalized customer experience that drives business growth.

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