Customer data may be the oil of the digital economy, but trying to swell the scale and scope of incoming data can pose challenges for retailers. Minimizing or overcoming these challenges starts with gaining an understanding of the three pillars of data that are most important to retailers and the common difficulties associated with each one. It ends with deploying easy-to-implement solutions that allow retailers to kick data-related roadblocks to the curb.
Finally harness Big Data, legacy data, and people data to give your business the competitive advantage that you deserve.
Connect Today
When it comes to customer data, quantity doesn’t necessarily equal quality. No matter how much customer data a retailer has, that data can prove problematic in several ways:
PILLAR #1: CUSTOMER DATA
Some 8% to 10% of every database contains duplicate records—and 92% of businesses claim that they have such records in their system.[1] And duplicate records don’t just result in waste and inefficiencies. They also prevent retailers from obtaining and leveraging critical insight into their customer base.
MRZ and OCR technologies instantly identify document type and extract client data for population into relevant systems, like CRM platforms—no manual data entry involved.
Smart facial recognition and comparison algorithms recognize match between a selfie and an ID image, distinguishing changes like facial hair, makeup, hairstyle, and more.
Determines if device user is live rather than using a static image, by distinguishing eye movement to ensure user authentication.
Generates and stores customer due diligence reports and full audit trails. E-commerce business controls all documents and reports and may evaluate them at any time.
eToro: Putting online investment and trade activity within easy reach
Client snapshot: Company’s multi-asset social investment platform features wide array of tools designed to facilitate simple, transparent trade and investment in global markets. Harnessed by more than 23 million registered users in over 100 countries.
Objective:
• Enable fast, seamless account-opening process for potential registrants, with simplicity and speed to match user experience, by eliminating manual ID checks involving time-consuming, costly, error-prone physical inspection of identifying documentation
Solution requirement:
• Features and capabilities to render onboarding as smooth and simple as ongoing use of platform
Solution components/functions:
• Electronic identity verification (eIDV) delivered through apps, SaaS, and web APIs that are readily integrated into existing online platforms
• In processing applications for financial products and/or services, matches applicants’ name, address, date of birth, and email address or telephone number against reputable data streams, such as government agency, credit agency, and utility records.
• Accesses billions of global records in real time, ensuring that customer experience remains uncompromised
• Rapidly assesses applicants’ residency and proof of address, speeding determination of their true identity
• eIDV capabilities can be scaled, delivering as few as 100 or many million checks per year
Results:
• Users receive notification of approval status in seconds rather than minutes (as with manual checks), enabling approved parties to begin exploring and investing on platform
• Auditor report developed by Melissa includes details of how each user was verified. Provides eToro auditors with PDF documentation on Melissa letterhead, confirming that particular user or group of users was vetted and criteria for doing so. Helps eToro maintain proof of compliance for jurisdictions to which it is required to report.
38 years as an independent data quality provider, trusted by thousands of businesses worldwide to fulfill their data quality needs
Single-source vendor of global address management, data quality, and identity verification solutions that help organizations harness accurate data for a more compelling customer view
Exceedingly wide breadth of data: millions of postal addresses, landline and mobile numbers, and email addresses
Nearly three-quarters (73%) of U.S. customers consider the customer experience a key factor in their purchasing decisions, but 54% say companies need to improve that experience [2]—and 70% of consumers leave a company because they believe it doesn’t care about them [3]. Without a 360-degree view of their customers, retailers cannot deliver the caliber of customer experience that cultivates repeat business and supports a sharp competitive edge.
Data that is inaccurate or simply old also hinders retailers’ ability to glean a true understanding of customers’ intentions, preferences, and shopping needs—present and future.
Duplicate records.
Lack of 360-degree customer view.
Bad or outdated information.
ID Check
Biometrics Check
Liveness Check
Compliance Reporting
Understanding the Three Pillars of Retailer Data
car2go: Driving secure online car rental
Objectives
Solution components/functions
Solution requirements (in line with KYC principles)
Outcome
Leading provider in carsharing segment, with more than three million users worldwide, company offers registered customers the option to rent a car from one of 26 locations in eight countries.
Replace manual account-opening process, which required new users to visit a car2go store during opening hours, with option to quickly, easily, and flexibly register online and subsequently complete entire rental transaction in digital form on their smartphone.
Verify addresses in real time using web service
Complete address verification within a few seconds, no matter the country
24/7 support
Secure, encrypted connection via HTTPS
Value-driven
High-quality results
Compliance with data protection guidelines
Dedicated, company-specific “private cloud” server.
Web service validates addresses in stages, starting with application of data validation tools and followed by deployment of international identity verification solution. In a few seconds, data validation system checks data entered by customer to ensure plausibility and correctness.
If data passes validation process, customer’s identity is checked via inspection of personal data (name, address, and date of birth), then compared and verified against reference data.
New customers can still register at a car2go store, but can also register online via smartphone—a simpler, faster process for car2go and its clients alike.
Reduction in manual validation costs.
LONG ON RECORDS, SHORT ON SCOPE AND ACCURACY
There are just as many ways for retailers to rectify customer data problems as there are customer data problems themselves, including:
TURNING THE (CUSTOMER DATA) TABLES
to understand weak points in information capture/collection across multiple channels in which merchants engage.
Profiling data
to prevent bad data from entering retail systems in the first place.
Employing a data quality firewall
—including correcting bad addresses, eliminating non-working telephone numbers and email addresses, and updating the addresses of customers who have moved.
Periodically cleaning batches of data
Melissa offers solutions that let retailers easily improve the accuracy and scope of their customer data.
PILLAR #2: PRODUCT DATA
DOUBLE DATA, DIFFERENT DIRECTIONS
Why Melissa?
Melissa works with retailers to ensure the integrity and completeness of all their data, improving sales and the customer experience while reducing errors and costs.
BETTER DATA, BETTER SALES, BETTER CUSTOMER EXPERIENCE
This sparks customer confusion, an inability to get a complete view of customers, and costly order inaccuracies.
Duplicate product information—or multiple variations of information.
A lack of product information taxonomy brings duplicate SKU numbers into retailers’ database, again leading to confusion and order errors. What’s more, without product data taxonomy, online shoppers may be presented with similar products that are really the same item, with the identical negative consequences.
Absence of product data taxonomy
An abundance of product data—and no way to classify it—also causes more than one type of headache.
REINING IT IN
Getting product data under control doesn’t need to be a complicated process. Retailers should:
to identify all duplicates—including products that appear to be somewhat different, but are not.
Profile product data
including artificial intelligence (AI) and machine reasoning/machine learning.
Utilize product categorization tools,
Solutions from Melissa help retailers eliminate “data doubles” as well as to keep product information properly organized and classified.
PILLAR #3: Location DATA
NO STANDARDS, NO CERTAINTY
The integrity of location data isn’t guaranteed. Often, retailers must grapple with:
PUTTING DATA IN ITS ‘PLACE’
Ensuring the accuracy of location data means:
Unstandardized addresses that contain multiple address fields, unstructured big data, and/or different abbreviations, diacritics, and language sets.
Unverified addresses. Retailers need to determine whether an address actually exists, and/or whether deliveries can be accepted there, but don’t always have a way to do so.
Geocoding glitches. Googling frequently yields latitudinal and longitudinal coordinates for addresses that don’t exist.
But accurate location data is a must.
On average, bad data, including bad location data, costs businesses $9.7 billion to $14.2 billion annually [4].
Couriers like UPS and FedEx now require shippers to shell out nearly $29 for every address correction—an expense that can quickly add up.
Orders that don’t reach the right customer or are claimed by the wrong recipient can burn big holes in e-commerce businesses’ pockets. There’s the cost of the lost product and the initial shipping cost, plus the price of the replacement and the expense of shipping it. That’s not to mention the potential to lose an irate customer to the competition.
Geocoding promotes location data accuracy by converting text-based street addresses or other location descriptors into precise latitudinal and longitudinal coordinates. Reverse geocoding involves the opposite conversion, also pushing the location data accuracy envelope.
Leveraging geocoding or reverse geocoding.
The CASS certification program was developed by the United States Postal System to test the accuracy of address-matching software and improve the accuracy of postal coding, such as ZIP+4 Code® and five-digit ZIP Code coding.
Utilizing a Coding Accuracy Support System (CASS)-certified address verification solution for U.S. addresses.
For example, in Canada, Canada Post SERP; in Germany, Deutsche Post; and in the United Kingdom, Royal Mail.
For global address verification, choosing a provider that is certified or partners with the postal authority in which the retailer does business
Look to Melissa for solutions that pave the way for easy location data verification.
Flexible technology that works with internal CRM and data systems. Multiple tool options—APIs, web services, SaaS, and plug-ins for popular platforms like Salesforce, Dynamics CRM, Magento, Shopware, and Excel—plus service bureau
Unlimited technical support
120-day guarantee—because ensuring data quality should never cost more money than it saves
More than 1 trillion addresses processed by industry-leading solutions
scroll
for more
Sources: 1 To come, 2 PWC, 3 Superoffice, 4 Gartner