Google Cloud Platform Case Studies Frank & Oak Relies on Looker to Provide Insights at the Moment of Decision

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	Frank & Oak Relies on Looker to Provide Insights at the Moment of Decision Google Cloud Platform

Frank & Oak Relies on Looker to Provide Insights at the Moment of Decision

Google Cloud Platform

Technology Category	Analytics & Modeling - Real Time Analytics
Applicable Industries	Retail
Applicable Functions	Sales & Marketing Business Operation
Use Cases	Predictive Quality Analytics Inventory Management
Services	Data Science Services
Challenge	Frank & Oak is a lean, early-stage company that strives for maximum efficiency to fuel its rapid growth. A single business intelligence specialist supports a workforce that is expanding to more than 100 people, with analytics requirements that are more challenging than those of a typical retail environment because of the monthly introduction of new collections and the additional tracking required to manage the subscription business. The company started out with a set of discrete internal SQL databases, including a Magento e-commerce database, a custom inventory (warehouse) management system, and a database for web event tracking. In addition, data resides in external sources, such as Desk.com for customer service, MailChimp for email marketing, Google Analytics, and Google AdWords. Before Looker, the data analyst ran manual queries upon request, extracting data from various sources and exporting it to Excel for analysis. Because nontechnical users had no ability to explore or refresh data on their own, waiting for custom queries could create problematic bottlenecks. Also, the specialist spent a disproportionate amount of time writing basic SQL instead of doing the advanced analytics that drive real value for the company. Read More
About Customer	Frank & Oak is a vertically integrated men’s clothier that creates and sells affordable, high-quality merchandise targeted at young creatives. The primary sales channel is an e-commerce website and related mobile apps, with a growing set of pop-up stores and storefronts that let men try on and purchase catalog items for home delivery. The company also has a subscription plan that offers personalized product selections, free shipping, monthly at-home try on, and a percentage back in-store credit for every purchase made. Frank & Oak launches a new collection monthly, unlike typical retailers that refresh collections four times a year. Read More
Solution	When Frank & Oak began using Looker, the company gained the ability to instantly query multiple data sources, including e-commerce, marketing, inventory, and customer service systems. Nontechnical employees can call up dynamic data visualizations and drill down for more detail with a click. And, because the company’s data analyst is freed up from writing routine queries, he can focus on complex analytics using Looker’s modeling layer and an API that lets him export data to R, Python, and Excel for statistical functions such as linear regression and correlation studies. Looker was the obvious choice for Frank & Oak, because it allows everyone in the organization to access and explore data dynamically, using a browser. Currently Looker sits on top of a MySQL database, but the company is in the process of migrating to AWS Redshift tables, with the confidence that Looker will scale as Frank & Oak— and its data — grows. In fact, Looker is designed to take full advantage of fast analytic databases such as Redshift. The data analyst uses the LookML modeling language to build a consistent framework for data discovery across the organization. And because LookML lets him rapidly generate SQL, he also uses it to create the first draft of complex queries that he later refines through manual coding. When groups require special-purpose analytics, he uses a Looker API to export data to Excel, R, and pandas (Python). Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Applicable Industries

Retail

Applicable Functions

Sales & Marketing

Business Operation

Use Cases

Predictive Quality Analytics

Inventory Management

Services

Data Science Services

Challenge

Frank & Oak is a lean, early-stage company that strives for maximum efficiency to fuel its rapid growth. A single business intelligence specialist supports a workforce that is expanding to more than 100 people, with analytics requirements that are more challenging than those of a typical retail environment because of the monthly introduction of new collections and the additional tracking required to manage the subscription business. The company started out with a set of discrete internal SQL databases, including a Magento e-commerce database, a custom inventory (warehouse) management system, and a database for web event tracking. In addition, data resides in external sources, such as Desk.com for customer service, MailChimp for email marketing, Google Analytics, and Google AdWords. Before Looker, the data analyst ran manual queries upon request, extracting data from various sources and exporting it to Excel for analysis. Because nontechnical users had no ability to explore or refresh data on their own, waiting for custom queries could create problematic bottlenecks. Also, the specialist spent a disproportionate amount of time writing basic SQL instead of doing the advanced analytics that drive real value for the company.

About Customer

Frank & Oak is a vertically integrated men’s clothier that creates and sells affordable, high-quality merchandise targeted at young creatives. The primary sales channel is an e-commerce website and related mobile apps, with a growing set of pop-up stores and storefronts that let men try on and purchase catalog items for home delivery. The company also has a subscription plan that offers personalized product selections, free shipping, monthly at-home try on, and a percentage back in-store credit for every purchase made. Frank & Oak launches a new collection monthly, unlike typical retailers that refresh collections four times a year.

Solution

When Frank & Oak began using Looker, the company gained the ability to instantly query multiple data sources, including e-commerce, marketing, inventory, and customer service systems. Nontechnical employees can call up dynamic data visualizations and drill down for more detail with a click. And, because the company’s data analyst is freed up from writing routine queries, he can focus on complex analytics using Looker’s modeling layer and an API that lets him export data to R, Python, and Excel for statistical functions such as linear regression and correlation studies. Looker was the obvious choice for Frank & Oak, because it allows everyone in the organization to access and explore data dynamically, using a browser. Currently Looker sits on top of a MySQL database, but the company is in the process of migrating to AWS Redshift tables, with the confidence that Looker will scale as Frank & Oak— and its data — grows. In fact, Looker is designed to take full advantage of fast analytic databases such as Redshift. The data analyst uses the LookML modeling language to build a consistent framework for data discovery across the organization. And because LookML lets him rapidly generate SQL, he also uses it to create the first draft of complex queries that he later refines through manual coding. When groups require special-purpose analytics, he uses a Looker API to export data to Excel, R, and pandas (Python).

Impact #1	C-level executives monitor Looker dashboards, the head of finance feeds data into financial models with a click, the inventory team stays on top of supply at the warehouse, the marketing team assesses the results of A/B testing at a glance, and the customer service group instantly drills down to transaction-level details. Every department at Frank & Oak relies on Looker to help streamline and strengthen its day-to-day business.
Impact #2	Frank & Oak’s data analyst helps teams prepare for meetings by putting together a dashboard with reusable Looks that are relevant to a specific topic. Team members interactively explore variables and drill down to answer key questions on the spot.
Impact #3	A single BI specialist can support the needs of all the departments in a rapidly growing company and still have abundant time left to perform the advanced analytics that only he can do. By using Looker to create data models and reusable queries, he has made it possible for even nontechnical staff to do data discovery on.

Impact #1

C-level executives monitor Looker dashboards, the head of finance feeds data into financial models with a click, the inventory team stays on top of supply at the warehouse, the marketing team assesses the results of A/B testing at a glance, and the customer service group instantly drills down to transaction-level details. Every department at Frank & Oak relies on Looker to help streamline and strengthen its day-to-day business.

Impact #2

Frank & Oak’s data analyst helps teams prepare for meetings by putting together a dashboard with reusable Looks that are relevant to a specific topic. Team members interactively explore variables and drill down to answer key questions on the spot.

Impact #3

A single BI specialist can support the needs of all the departments in a rapidly growing company and still have abundant time left to perform the advanced analytics that only he can do. By using Looker to create data models and reusable queries, he has made it possible for even nontechnical staff to do data discovery on.

Benefit #1	Improved the sign-up rate for subscriptions
Benefit #2	Accelerated the rate at which customers make purchases
Benefit #3	Reduced the time required to solve customer issues

Benefit #1

Improved the sign-up rate for subscriptions

Benefit #2

Accelerated the rate at which customers make purchases

Benefit #3

Reduced the time required to solve customer issues

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Overview

Frank & Oak Relies on Looker to Provide Insights at the Moment of Decision

Operational Impact

Quantitative Benefit