How Roamler Automates Its In-Store Data Collection

Discover how crowd-supported solution provider Roamler reduces errors and shorterns turnaround times by 91% with Klippa’s DocHorizon Platform.
Case Study Roamler
Sector
FMCG & Retail Software
Team
300+ employees
Solution
Klippa DocHorizon
Use case
Mobile scanning

About Roamler

Founded in 2011, Roamler is a leading Dutch company specializing in crowd-supported solutions. By connecting organizations with a network of skilled professionals, Roamler excels in in-store data collection for major FMCG brands, retail chains, and consumer goods manufacturers across Europe.

The Challenge: Outdated and Time-Consuming Processes

Roamler’s business revolves around gathering critical in-store data for its clients. This traditionally involved employees physically visiting retail stores to scan product labels, price tags, or menu cards.

However, the workflow had its challenges:
Time-consuming: An employee visited multiple stores, and photographed and scanned price tags, food packages, or menu cards for later cataloging and analysis.

Inefficient: After the photos were taken, they were sent to a BPO provider. Here, a back-office employee manually extracted the data from the pictures and copied it into a spreadsheet.
Hard to scale: As Roamler expanded across Europe, this manual process became increasingly unsustainable.
Prone to errors:  Manual data extraction led to inaccuracies and delays, which impacted the overall quality of service.
Roamler realized they needed a more efficient, scalable solution to streamline their data collection process and minimize errors.
“With Klippa’s technology, we have transformed the way we approach data extraction, giving way for Roamlers to work faster, more reliably, and incredibly efficiently.”

The Solution: Automating In-Store Data Collection with Klippa

Roamler turned to Klippa for a smarter way to handle their in-store data collection. Klippa’s DocHorizon Platform provided the perfect fit, offering automation across various document workflows: price tag scanning, product label extraction, and more.

The process works as follows:
Image capturing: A Roamler employee captures an image of the required product information in-store.
Data extraction: Klippa’s technology automatically extracts key data from the image, such as price, product description, and supplier information.
Data conversion: The extracted data is transformed into structured, machine-readable output for further processing.

The Benefits for Roamler

91% Reduction in Document Processing Time

What once took 2-3 minutes per document can now be completed in seconds, increasing throughput without additional labor.

Up to 99% Data Accuracy with HITL

With a Human-in-the-Loop, Roamler can now trust that the data is highly accurate, drastically reducing errors.

Scalability Across Europe

The solution effortlessly scales, allowing Roamler to handle a growing volume of data without compromising on quality.

Multilingual Support

Klippa’s ability to process documents in multiple languages has allowed Roamler to expand across various European markets.

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