Why Data Quality Matters in Retail
We’ve seen unprecedented change over the past few years in the retail landscape and in consumer buying behavior, driven both by the COVID-19 pandemic and by retailers’ digital transformation efforts. A recent report by McKinsey notes that “…in a matter of 90 days we have vaulted forward 10 years in consumer and business digital adoption.”1 And there is no sign that the speed of change is slowing — if anything, it is accelerating.
Besides grappling with changing consumer behavior and their digital transformation initiatives, retailers must continue to look for opportunities for growth even as they face tougher competition, disruptions to supply chains and ever-more stringent regulatory requirements.
To boost revenues, reduce costs and comply with regulations in this demanding environment, retailers need to:
• Anticipate customer behavior and preferences
• Deepen their insight into which channels perform best for which customer segments and which products
• Increase customer engagement and loyalty
• Ensure the data they have on customers is accurate and protected
• Deliver a successful digital transformation
At the heart of all this is data. However, to be of value, the data needs to be fit for business purpose.
Although retailers are rich in data, many struggle with fragmentation and data that’s locked away in various enterprise applications. These application silos create multiple versions of the data with varying standards which makes it difficult for the business — sales, marketing, customer service and operations — to gain a complete and trustworthy view of its business-critical data, such as customer data or master data.
Data that is not cleansed, standardized and verified impacts the business in a number of ways, such as:
• Inability to identify customers and provide personalized offers across channels
• Slow response to identify additional or alternative suppliers
• Lack of trust in the results from AI/ML initiatives
• Delays in new product launches
• Ineffective pricing and promotion initiatives
• Non-compliance with data privacy regulations
• Delays and cost overruns with digital transformation strategies
Informatica® Cloud Data Quality empowers retailers to take a holistic approach to managing data quality so they can quickly identify, remediate and monitor data quality problems in business-critical data. By transforming your data quality processes into a collaborative effort between business users and IT, the solution creates a true data-centric environment that ensures success of your data-driven digital transformation initiatives.
This translates into business initiatives such as better customer experiences, increased cross-sell and upsell, and improved products and services that drive increased sales. It can also result in innovations that open up new markets and decisive insights that are put into action faster.
Informatica Cloud Data Quality leverages our many years of experience working with customers to identify and resolve their data quality problems. Because Informatica Cloud Data Quality is part of the Informatica Intelligent Data Management Cloud™, you can quickly identify and resolve data quality issues without any additional IT coding or development. As a result, you can leverage its security, reliability and backup so you can focus on operational excellence instead of investin iin additional infrastructure. Business users can readily specify, validate and test re-usable data quality rules in a streamlined and collaborative environment.
Key Benefits
Create Exceptional Customer Experiences
Customers demand a great experience. If they don’t have the best experience with your organization, they won’t just seek out a replacement product or service — they’ll also share their negative experience across their peer network. Poor customer experience can stem from delays in resolving problems, out of stocks, irrelevant offers, inconsistent product information and delayed or failed deliveries.
With delayed or failed deliveries, the damage is two-fold: in addition to customer disappointment and frustration, retailers must deal with increased costs for re-shipping or restocking. Smart organizations understand today’s reality. They realize that the difference between offering a stellar experience and a sub-par experience is trusted, reliable data.
To properly ensure that you’re aligned with your customers, you need to have the most accurate, up-to-date data possible across the organization. With Informatica Cloud Data Quality, you’ll be able to ensure that team members throughout your organization are running customer experience applications and master data management tools with the best quality data available, allowing you to truly improve every experience for your customers.
“66% of retailers say inaccurate inventory data creates buy online/pick up in-store (BOPIS) inconsistency.”2
Deliver Consistency and Relevance Across Channels
The omnichannel vision of a unique and personal customer experience powered by information is as exciting as it is frightening. The surge in online shopping since the onset of the COVID-19 pandemic includes many first-time consumers who opted to buy online and pick up in store
(BOPIS). These new digital consumers are also moving beyond the desktop and trying mobile apps for shopping and payments. And much like their savvier omnichannel shopper counterparts, they expect consistency across all the channels they use.
Retailers now know that a lot of customers start their purchase journey online and complete in store. For these customers, any inconsistency between what was expected and what was experienced can lead to disappointment, reputational damage and lost sales. Then too, consumers — sophisticated or not — want personalized recommendations and offers wherever and whenever they shop.
While it’s certainly possible to support more than one channel using disparate systems, this approach will never let you make progress toward true omnichannel retailing. Within all these systems there are variations in the data, duplicate data, missing data and data that is not verified. This type of data is the nemesis of integrated thinking, streamlined operations and intelligent insights. Whether you are working with customer or third-party data, product or supplier data, transaction data or data from IoT devices, Informatica Cloud Data Quality can cleanse, standardize, de-duplicate, verify and enrich your data so you can deliver an enhanced and consistent experience across all channels and devices.
“Between 12% and 21% of survey respondents said they switched to brands that sent them relevant messages or promotions in their preferred channel.”3
More Robust Compliance
As consumers become increasingly concerned about their privacy, a wave of data protection laws now also impacts how companies collect, store, share and manage their sensitive data. Two examples of these data protection laws are the General Data Protection Regulation (GDPR) legislation, with its global implications for every company that does business in the European Union or with citizens of the EU, along with the California Consumer Privacy Act (CCPA) which secures new privacy rights for California consumers.
For many regulations, compliance is largely a data-driven discipline. But in large retailers, data environments have become much more complex, with data locked in many silos, and data quality and governance applied inconsistently.
Data protection regulations often come down to three criteria: One is knowing where all your sensitive data lives and where it is used. The second is your ability to prove that you’re using it legally. And the third is whether you can prove that you’re securing it.
The metrics of data protection success are clear: you want to avoid fines and damage to your organization’s reputation. Without data quality, achieving these metrics becomes much, much harder. For example: if a data field or column is poorly labeled or its metadata doesn’t conform to business rules, you won’t see that it contains personally identifiable information (PII) — and you won’t secure it.
Deeper Insights
The most common challenge retailers face with customer, product, inventory and sales data is not its quantity or timelessness — it is the quality of that data. The reality of your data warehouse is that you can’t just keep dumping information into it, hoping it will sort itself out. If you want to leverage your data for research, analysis building and training AI algorithms, the data has to be of sufficient quality. Without high-quality data feeding your analytics applications, any decisions around identifying customer trends, pricing, promotions, assortment management or inventory optimization will be flawed.
That’s why data quality is so critical to analytics and AI/ML. Bringing together insights across different data sources — structured and unstructured, static and streaming, each with its own data schema — puts a high demand on the quality of the data being combined. Data quality problems that inhibit analytics in a single silo become exponentially worse as you combine that data with more and more data sources.
Informatica Cloud Data Quality provides advanced data profiling and discovery, along with prebuilt data quality rules for matching and standardizing data. The integrated solution provides a centralized set of reusable rules and tools for managing quality across all analytics projects.
This eliminates redundant data quality tools and enables data scientists to accelerate the development of models and algorithms to mine data and give you data and analytics that you can trust.
Next Steps
See first-hand how the next-generation data quality solution works and try it free for 30 days: https://www.informatica.com/trials/cloud-data-quality.html
1Retail reimagined: The new era for customer experience, McKinsey, 2020
3Retail reimagined: The new era for customer experience, McKinsey, 2020
