Skinit Selects Cloudmeter to Increase Visibility into Customer Behavior

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Cloudmeter Provides Skinit with Unprecedented Ability to Understand and Improve the Online Customer Experience, Drive Website Conversions, and Increase Customer Loyalty

Cloudmeter, a provider of leading software solutions for transforming real-time network Big Data into actionable information for IT and business users, today announced that Skinit, the industry leader in consumer personalization for electronic devices, is successfully using Cloudmeter’s technology in order to gain unprecedented visibility into customer behavior.

Skinit places great emphasis on the experience it provides to its customers. The company’s online ordering and customization tools enable its customers to personalize over 2,000 different devices, including cell phones, laptops, PDA devices, cameras, medical equipment, gaming devices, and many more. Because personalization lies at the core of Skinit’s business model, the company relies on customer insight to optimize the online experience, which leads to satisfied customers and ultimately improved website conversion rates.

Since implementing Cloudmeter Stream, the company is able to realize the following benefits:

  •     Obtain valuable customer experience information to optimize website navigation and terminology
  •     Gain the ability to replay individual user sessions to understand the true cart experience
  •     Provide the flexibility to easily modify website analytics overtime
  •     Eliminate lag time between changes to website and ability to capture the newly relevant data

“The future of online business belongs to organizations that truly understand their customers' experience and behavior,” said Ronit Belson, COO of Cloudmeter. “Cloudmeter Stream is the first product on the market capable of unlocking the Big Data ‘Gold Mine’ in customers networks. We are pleased that Skinit selected our technology to gain an unparalleled level of insight and understanding--and ultimately achieve their goal of improving their customers' experience.”

Cloudmeter Plays Well with Skinit’s Existing BI Solutions

Skinit’s previous method of gathering insights into how visitors use the company’s website, presented challenges due to its inability to connect customer data (transactional data, behavioral demographics, and web behavior data) to its SAP Business Intelligence (BI) system. Before implementing Cloudmeter Stream, Skinit’s customer data essentially existed on an ‘island’ with no connection to its other critical systems. While the technology was capable of building predictive analytics around data, the behavioral insights that the technology provided ended once the customer reached the Skinit website. This means Skinit’s existing tools weren’t able to record valuable customer information until after customers made a purchase. As a result, the company missed a huge amount of data generated by all of the customers who didn't complete transactions. And those are the people that Skinit aims to focus on the most. It is critical that Skinit has the ability to turn all of its website visitors into purchasers.

“Our cost savings come from having the raw data and being able to do a lot of the predictive analysis, benchmarking, and more all by ourselves, rather than relying on multiple vendors with each responsible for one little part,” said Kate Bartkiewicz, web analyst and manager of business intelligence at Skinit, Inc.

With Cloudmeter, Skinit is able to access raw data and feed it into its BI system in a way that links it to all the other data they are collecting--without having to create custom code. The wealth and quality of information made available by Cloudmeter’s technology allows Skinit to gain unparalleled insight into its customers' experience and ensures that its website is optimized in a way that meets their needs. Furthermore, Cloudmeter's zero coding approach and ease of implementation allows Skinit to focus its efforts on analyzing the results, rather than spending time and resources getting the data in.

“Being a web analyst is like being a forensic scientist − you have to recreate the scene of the crime in order to find the source of a problem. With Cloudmeter, I don't have to do this anymore since I have full visibility into all of our website activity,” said Bartkiewicz.

The Cloudmeter Difference

No other infrastructure carries the breadth of valuable information as an organization’s network because everything related to the business travels through it. Until now, this type of data has been difficult to analyze due to limitations of today’s technologies, such as not being able to capture all the information related to the customer experience, risk to production systems, etc. With Cloudmeter, customers can essentially ‘harvest’ this valuable information by leveraging ultralight agents that passively mine in real-time Big Data streams generated by web applications, all with no impact on production systems.

About Cloudmeter
Cloudmeter transforms real-time network data into actionable information for IT and business users, helping organizations understand and optimize their end-users’ experiences. The company’s products, Cloudmeter Insight and Cloudmeter Stream, use ultralight agents that passively mine Big Data streams generated by web applications without introducing risk or degrading performance.

Cloudmeter Insight is the most advanced End-User Management SaaS solution, which uniquely incorporates visual session replay for exceptionally detailed problem analysis. Cloudmeter Stream combines state-of-the-art data capture with event processing, and seamlessly integrates real-time information with many databases, business intelligence and Big Data products to help organizations conquer their most demanding analytics needs.

Cloudmeter is a venture-funded start-up based in Mountain View, California that works with companies whose web presence is critical to their business, including name brand customers such as Netflix, SAP, Saks Fifth Avenue and Skinit.

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Julie Tangen
Kulesa Faul for Cloudmeter
(831) 251 3450

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Julie Tangen
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