Data quality for retailers

Leverage Data Ladder’s solutions for retail to break down data silos, enrich shopper experience, ensure faster delivers, and uncover profitable segments.

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How bad data affects retailers?


Retailers are uncertain about their product data accuracy

80 percent of retailers are not confident in their product data and 86% of consumers are unlikely to buy products from a brand after experiencing inaccurate product information.

High return rates

Inconsistencies and errors in product attributes can mislead shoppers into buying wrong items, leading to high product returns.

Lack of customer personalization

Incomplete or inconsistent data can limit personalization to tailor campaigns for new purchases, cart abandonment, etc.

Late shipping orders

Missing street names, apartment numbers and unverified addresses can lead to missed or delayed orders, increasing customer complaints.

Poor campaign response

Low email sender reputation and deliverability and missed direct mail deliveries due to dirty email and phone data.

Inefficient inventory planning

Silos in point of sale and inventory data can cause large quantities of slow-moving inventory or out-of-stock situations.

Missed sales opportunities

No single customer view leads to little or no opportunity for segmentation and find lucrative revenue opportunities.


DataMatch Enterprise – Achieve a single customer view

Data Ladder’s DataMatch Enterprise offers robust data cleansing, standardization, matching, and various other solutions to enhance the quality of your customer and transaction data. Verify and pinpoint customer addresses for fast order shipments, and reconcile unresolved customer identities to ensure correct invoicing.

Customer Stories

See what retailers are saying...

Business Benefits

What’s in it for you?

Enrich customer experience

Optimize customer in-store and ecommerce experience with better listings and clear categories, and eliminating duplicates.

Ensure faster deliveries

Standardize addresses with prebuilt USPS database and pinpoint delivery coordinates by ZIP+4 values for faster and precise shipping orders.

Streamline inventory levels

Utilize clean data to make accurate forecasts for estimating stock ordering levels in both peak and off-peak demand levels.

Enhance email campaigns

Increase sender reputation, inbox placement rate, open to click ratio metrics of email campaigns by discarding outdated and incorrect addresses.

Uncover profitable segments

Identify lucrative cross-sell, up-sell opportunities through consistent and reliable data on customer purchase history, average order value, and other signals.

Gain a single customer view

Break down data silos to track customer data across various touchpoints for omni-channel marketing, segmentation, and retention purposes.

Want to know more?

Check out DME resources

Merging Data from Multiple Sources – Challenges and Solutions

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