Welcome!

SDN Journal Authors: Destiny Bertucci, Liz McMillan, Pat Romanski, Elizabeth White, Amitabh Sinha

Related Topics: @DXWorldExpo, Mobile IoT, Microservices Expo, Wearables, @CloudExpo, SDN Journal

@DXWorldExpo: Article

Case Study: Skinit Transforms Big Data into Actionable Information

Gains unprecedented visibility into customer behavior

Skinit Inc. is an eCommerce provider of personalized skins and cases for a wide range of consumer products. With over 180 licensed brands, in-house artwork and the ability to completely customize designs, the company reaches a diverse market. Skinit knew it faced an increasingly competitive market where customers were expecting a more personalized experience. Like many eCommerce companies, we had a large amount of data on what was purchased, what pages were visited, where visitors were coming from and so on. However, while we had more and more data every day, we still lacked the ability to connect all these data points and turn them in to knowledge.

The eCommerce Challenge:
Like any eCommerce site, Skinit relied heavily on web analytics data, using both free and high-priced platforms. Unfortunately both provided some challenges, and the marketing team created a "wish list" of capabilities for a new system.

The "wish list" consisted of the following:

1. We needed an analytics system that was light on implementation and high on integrity. The unique capabilities of Skinit's site made implementation management difficult and threatened data integrity. Like many companies, our development team was swamped with other projects so getting implementation on site in a timely manner was a big challenge.

We were looking at various tag managers to solve this issue. While tag managers would have surely relieved some of the implementation burden, we still had concerns about data integrity as we had experienced problems with tagging in the past, particularly with getting the data comparable for year-over-year benchmarking.

2. The data needed to be person-based rather than page-based. All our efforts were spent optimizing and improving the customer journey, and we needed data that supported this. Connecting web-behavior data to sales, CRM and other supplemental data sets was the next logical step.

While data analytics platforms allowed us to get some data in this format, it was limited and difficult to connect when visits did not lead to purchase - and non-purchasers were the target audience for optimization.

3. Data needed to be collected to enhance merchandising and personalization. With such a large catalog, understanding relationships between products was key to helping the customer personalize their device quickly. We wanted to be able to make recommendations to help the customer along. Since the product can have a wide array of attributes such as color, brand, gender affinity, sports market affinity, geography, etc. that aren't necessarily present in page-level meta-data, we needed to be able to pull data from multiple sources to better understand just what made different products appealing to different users.

We looked at third-party recommendation engines, but felt there were some limitations in the models as they were either built to analyze frequency of purchase combinations or frequencies of products viewed. This presented a challenge for us since most customers bought one product at a time, and products viewed together were proven to be self-fulfilling because customers either viewed what we merchandised to them or they left. The challenge was that we didn't feel we knew how to merchandise the right thing to them.

For example, what recommendation should we make to a customer accessing the site from the San Francisco Bay area but viewing Pittsburgh Steeler products? If we based the recommendation on category, the customer would be shown other NFL products for other teams - unlikely to be appealing since it is rare for a fan to have a strong affinity to two teams in a single sport. Do we market another sport such as baseball? And if so, do we assume they are a San Francisco Giants fan or a Pittsburgh Pirates fan? To really elevate the business, we needed a system that could effectively make decisions like these.

4. We needed to be able to quickly identify, track and examine each micro-conversion path for optimization. Ideally, we wanted to be able to quickly identify the most frequent paths to success and the most frequent paths resulting in drop off. For example, if we had a five-step cart process, we wanted to see how many users went from Step 1 to Step 2 to Step 3 to Step 4 to Step 5, and how many deviated from that path and how. Traditional cart funnels clued us in to deviations from this path, but not where or why.

We could conduct this analysis using our paid analytics platform, but we could not integrate it into our business intelligence system, which made the analysis time consuming and limited in scope.

5. Finally, we needed a better way to visualize problems or optimization opportunities throughout the company in order to get teams to act on findings. We looked at session replay technologies, but were concerned about the limitations in filtering or searching these sessions for specific characteristics important to us. This meant we would have to sample records, which was not the time saver we had hoped for.

We added up the cost of all the various services, partners and platforms we could use to meet most of these challenges. Ultimately, Cloudmeter, a leading software solution provider for transforming real-time network Big Data into actionable information for IT and business users, satisfied all of these requirements and cost 30 percent less than the alternate solutions.

The Cloudmeter Results
The no-code implementation meant that the new platform could be up and running quickly without interfering with site performance. Cloudmeter's reactor system also made it easy to add new variables and to push data to different sources. This was extremely important, as we wanted a system that would grow with us as our questions became more sophisticated. The data feeds were easily integrated into our existing business intelligence system, allowing us to tie onsite behavior to other known data points.

We created a data feed where the primary unit was the customer. Whether they converted or not, we were able to capture each navigation path using custom logic, from how they came to the site, found the product and what cart actions they took. Each of these paths could be aggregated and searched. For example, we could quickly identify the common navigation paths for a customer who clicked on a recommended product and added it to cart, or users that added an invalid coupon code. Since this data was layered into our BI system, we would examine onsite behavior differences by things like gender or market segment.

We were able to capture product metadata from the page and combine that with things like searched keywords to understand relationships between products for merchandising. We found common behavior paths in different customer segments and information, and how to quickly identify those segments - from geographic region, search interest or loyalty.

Finally, the combination of Cloudmeter Stream with web session replay added a layer of efficiency to our analysis. Not only could we email sessions throughout the team - allowing customer service, technology or marketing to see issues first hand, but we could also gain a level of insight into a problem in a much shorter time period. In the past, when an anomaly in the data was observed, it would trigger a time consuming deep dive. Through "data forensics," we tried to piece together theories for the change. Now, when we observe something unusual in the data, we immediately search sessions in Cloudmeter Stream containing the behavior anomaly and usually gain immediate insight into the cause. This simple yet powerful step frees up our analytics team to spend more time on strategy and optimization rather than on constant investigation.

As a result, Skinit is in the process of re-designing the eCommerce platform based on the insights we have learned from Cloudmeter. We expect to see some big gains from the new site, but more importantly, I think we are all excited to find the next place to continue optimization.

More Stories By Kate Bartkiewicz

Kate Bartkiewicz is Web Analytics and Manager of Business Intelligence at Skinit, Inc., a provider of consumer personalization products for electronic devices.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@CloudExpo Stories
The dynamic nature of the cloud means that change is a constant when it comes to modern cloud-based infrastructure. Delivering modern applications to end users, therefore, is a constantly shifting challenge. Delivery automation helps IT Ops teams ensure that apps are providing an optimal end user experience over hybrid-cloud and multi-cloud environments, no matter what the current state of the infrastructure is. To employ a delivery automation strategy that reflects your business rules, making r...
The 22nd International Cloud Expo | 1st DXWorld Expo has announced that its Call for Papers is open. Cloud Expo | DXWorld Expo, to be held June 5-7, 2018, at the Javits Center in New York, NY, brings together Cloud Computing, Digital Transformation, Big Data, Internet of Things, DevOps, Machine Learning and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding busin...
In a recent survey, Sumo Logic surveyed 1,500 customers who employ cloud services such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). According to the survey, a quarter of the respondents have already deployed Docker containers and nearly as many (23 percent) are employing the AWS Lambda serverless computing framework. It’s clear: serverless is here to stay. The adoption does come with some needed changes, within both application development and operations. Tha...
SYS-CON Events announced today that Synametrics Technologies will exhibit at SYS-CON's 22nd International Cloud Expo®, which will take place on June 5-7, 2018, at the Javits Center in New York, NY. Synametrics Technologies is a privately held company based in Plainsboro, New Jersey that has been providing solutions for the developer community since 1997. Based on the success of its initial product offerings such as WinSQL, Xeams, SynaMan and Syncrify, Synametrics continues to create and hone in...
Smart cities have the potential to change our lives at so many levels for citizens: less pollution, reduced parking obstacles, better health, education and more energy savings. Real-time data streaming and the Internet of Things (IoT) possess the power to turn this vision into a reality. However, most organizations today are building their data infrastructure to focus solely on addressing immediate business needs vs. a platform capable of quickly adapting emerging technologies to address future ...
In his general session at 21st Cloud Expo, Greg Dumas, Calligo’s Vice President and G.M. of US operations, discussed the new Global Data Protection Regulation and how Calligo can help business stay compliant in digitally globalized world. Greg Dumas is Calligo's Vice President and G.M. of US operations. Calligo is an established service provider that provides an innovative platform for trusted cloud solutions. Calligo’s customers are typically most concerned about GDPR compliance, application p...
Modern software design has fundamentally changed how we manage applications, causing many to turn to containers as the new virtual machine for resource management. As container adoption grows beyond stateless applications to stateful workloads, the need for persistent storage is foundational - something customers routinely cite as a top pain point. In his session at @DevOpsSummit at 21st Cloud Expo, Bill Borsari, Head of Systems Engineering at Datera, explored how organizations can reap the bene...
Kubernetes is an open source system for automating deployment, scaling, and management of containerized applications. Kubernetes was originally built by Google, leveraging years of experience with managing container workloads, and is now a Cloud Native Compute Foundation (CNCF) project. Kubernetes has been widely adopted by the community, supported on all major public and private cloud providers, and is gaining rapid adoption in enterprises. However, Kubernetes may seem intimidating and complex ...
In his session at 21st Cloud Expo, Michael Burley, a Senior Business Development Executive in IT Services at NetApp, described how NetApp designed a three-year program of work to migrate 25PB of a major telco's enterprise data to a new STaaS platform, and then secured a long-term contract to manage and operate the platform. This significant program blended the best of NetApp’s solutions and services capabilities to enable this telco’s successful adoption of private cloud storage and launching ...
The past few years have brought a sea change in the way applications are architected, developed, and consumed—increasing both the complexity of testing and the business impact of software failures. How can software testing professionals keep pace with modern application delivery, given the trends that impact both architectures (cloud, microservices, and APIs) and processes (DevOps, agile, and continuous delivery)? This is where continuous testing comes in. D
You know you need the cloud, but you’re hesitant to simply dump everything at Amazon since you know that not all workloads are suitable for cloud. You know that you want the kind of ease of use and scalability that you get with public cloud, but your applications are architected in a way that makes the public cloud a non-starter. You’re looking at private cloud solutions based on hyperconverged infrastructure, but you’re concerned with the limits inherent in those technologies.
Nordstrom is transforming the way that they do business and the cloud is the key to enabling speed and hyper personalized customer experiences. In his session at 21st Cloud Expo, Ken Schow, VP of Engineering at Nordstrom, discussed some of the key learnings and common pitfalls of large enterprises moving to the cloud. This includes strategies around choosing a cloud provider(s), architecture, and lessons learned. In addition, he covered some of the best practices for structured team migration an...
With tough new regulations coming to Europe on data privacy in May 2018, Calligo will explain why in reality the effect is global and transforms how you consider critical data. EU GDPR fundamentally rewrites the rules for cloud, Big Data and IoT. In his session at 21st Cloud Expo, Adam Ryan, Vice President and General Manager EMEA at Calligo, examined the regulations and provided insight on how it affects technology, challenges the established rules and will usher in new levels of diligence arou...
Most technology leaders, contemporary and from the hardware era, are reshaping their businesses to do software. They hope to capture value from emerging technologies such as IoT, SDN, and AI. Ultimately, irrespective of the vertical, it is about deriving value from independent software applications participating in an ecosystem as one comprehensive solution. In his session at @ThingsExpo, Kausik Sridhar, founder and CTO of Pulzze Systems, discussed how given the magnitude of today's application ...
The “Digital Era” is forcing us to engage with new methods to build, operate and maintain applications. This transformation also implies an evolution to more and more intelligent applications to better engage with the customers, while creating significant market differentiators. In both cases, the cloud has become a key enabler to embrace this digital revolution. So, moving to the cloud is no longer the question; the new questions are HOW and WHEN. To make this equation even more complex, most ...
As you move to the cloud, your network should be efficient, secure, and easy to manage. An enterprise adopting a hybrid or public cloud needs systems and tools that provide: Agility: ability to deliver applications and services faster, even in complex hybrid environments Easier manageability: enable reliable connectivity with complete oversight as the data center network evolves Greater efficiency: eliminate wasted effort while reducing errors and optimize asset utilization Security: imple...
Mobile device usage has increased exponentially during the past several years, as consumers rely on handhelds for everything from news and weather to banking and purchases. What can we expect in the next few years? The way in which we interact with our devices will fundamentally change, as businesses leverage Artificial Intelligence. We already see this taking shape as businesses leverage AI for cost savings and customer responsiveness. This trend will continue, as AI is used for more sophistica...
In his Opening Keynote at 21st Cloud Expo, John Considine, General Manager of IBM Cloud Infrastructure, led attendees through the exciting evolution of the cloud. He looked at this major disruption from the perspective of technology, business models, and what this means for enterprises of all sizes. John Considine is General Manager of Cloud Infrastructure Services at IBM. In that role he is responsible for leading IBM’s public cloud infrastructure including strategy, development, and offering m...
Digital transformation is about embracing digital technologies into a company's culture to better connect with its customers, automate processes, create better tools, enter new markets, etc. Such a transformation requires continuous orchestration across teams and an environment based on open collaboration and daily experiments. In his session at 21st Cloud Expo, Alex Casalboni, Technical (Cloud) Evangelist at Cloud Academy, explored and discussed the most urgent unsolved challenges to achieve f...
In his session at 21st Cloud Expo, Raju Shreewastava, founder of Big Data Trunk, provided a fun and simple way to introduce Machine Leaning to anyone and everyone. He solved a machine learning problem and demonstrated an easy way to be able to do machine learning without even coding. Raju Shreewastava is the founder of Big Data Trunk (www.BigDataTrunk.com), a Big Data Training and consulting firm with offices in the United States. He previously led the data warehouse/business intelligence and B...