Case Study: eCommerce Strategy to Execution
Written by Jared Hillam
From Strategy to Execution on Snowflake and Looker
The eCommerce vendor is a pioneer in the beauty subscription service delivering 4 to 5 full- size products valued at over $100 for just $21 a month to its consumers. They provide brands with an all inclusive 360 digital marketing campaign across multiple platforms, including access to a pool of high profile influencers, putting products directly into the hands of prestige beauty consumers at no cost.
Intricity is a team of specialized Data Management, Data Warehousing, and Business Intelligence experts. The team members at Intricity have been handpicked over the course of 20 years, and represent the top talent globally in data-oriented disciplines.
Challenge and Wins
Due to the eCommerce vendor’s market execution they were growing between 10-20% per month and onboarding new enterprise scale systems would help them keep pace. Data acquisition between these systems acted as strategic processes for tracking customer activities. However, they acted independent of each other. Thus, accurately visualizing and understanding customer activities required the eCommerce vendor to conform the data across these various applications manually. This created tons of bottlenecks for understanding what was actually happening in their organization. To compound the problem the eCommerce vendor was acquiring Magento as their e-commerce platform which was going to expand the complexity of their solution.
Win 1: Engaging with the C-Suite to Develop a Strategy
Intricity partnered with the CEO and his direct reports at the eCommerce vendor to develop a Data Warehousing and Business Intelligence strategy which allowed the data to be componentized for a wide variety of analytical use cases. These use cases traversed the subject matters of Sales/Finance, eCom, Customer Support, Marketing, Product, and Inventory.
This partnership with the C-Suite went far beyond the initial strategy phases but delved into many other exploratory opportunities to leverage data as a strategic asset across the C-suite.
Win 2: Development of a Solid Data Model and Metadata Layer
The data model Intricity and the eCommerce vendor designed produced a level of analytical flexibility and reuse that they had never experienced previously. The organization could traverse the customer experience in a variety of subject matters and domains despite data being sourced from different systems. This model coupled up with Looker’s metadata layer provided a widely adoptable solution which could be shared by technical experts and everyday consumers of information.
Win 3: Integrated Data Share of Kustomer
The eCommerce vendor uses Kustomer to manage their customer service experience. Since the eCommerce vendor was a Snowflake customer they were able to adopt Kustomer’s data share and integrate it into their analytics. Intricity developed a series of Looker views to interrogate the Kustomer Data Share and expose it to their user base.
Win 4: Integration Leveraging Snowflake as the Transformation Engine
Intricity leveraged Alooma and Python to develop the data stream and it’s transformations. This really paid off when AWS had their big outage in 2017, as Alooma successfully buffered all the updates and loaded them as AWS came back online.
Intricity developed the Python scripts to have all the transformations occur in Snowflake, leveraging Snowflake’s horsepower to transform their complex data feeds.
As the Google acquisition of Alooma came to fruition, their feature set and support began to wane, Intricity began an Alooma migration to FiveTran which provided more maturity and better support. This migration enabled the eCommerce vendor to stay current with the latest replication features.
Win 5: Compelling Custom Visualizations
Intricity partnered closely with the the eCommerce vendor’s management to develop data visualizations which provided deep and meaningful value for their teams that were consuming data. One such visualization was developed jointly with the CEO which allowed a view of customer events across all the process swim lanes. This provided full perspective of the customer lifecycle within the organization. This is one of many custom visualizations which the eCommerce vendor uses today in their Looker environment.
Who is Intricity?
Intricity is a specialized selection of over 100 Data Management Professionals, with offices located across the USA and Headquarters in New York City. Our team of experts has implemented in a variety of Industries including, Healthcare, Insurance, Manufacturing, Financial Services, Media, Pharmaceutical, Retail, and others. Intricity is uniquely positioned as a partner to the business that deeply understands what makes the data tick. This joint knowledge and acumen has positioned Intricity to beat out its Big 4 competitors time and time again. Intricity’s area of expertise spans the entirety of the information lifecycle. This means when you’re problem involves data; Intricity will be a trusted partner. Intricity's services cover a broad range of data-to-information engineering needs:
What Makes Intricity Different?
While Intricity conducts highly intricate and complex data management projects, Intricity is first a foremost a Business User Centric consulting company. Our internal slogan is to Simplify Complexity. This means that we take complex data management challenges and not only make them understandable to the business but also make them easier to operate. Intricity does this through using tools and techniques that are familiar to business people but adapted for IT content.
Intricity authors a highly sought after Data Management Video Series targeted towards Business Stakeholders at https://www.intricity.com/videos. These videos are used in universities across the world. Here is a small set of universities leveraging Intricity’s videos as a teaching tool:
Talk With a Specialist
If you would like to talk with an Intricity Specialist about your particular scenario, don’t hesitate to reach out to us. You can write us an email: email@example.com
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