TechValidate Research on Google Cloud Data Analytics

43 Case Studies – Page 1 of 2


Google Cloud Data Analytics Case Study

Zeotap

Introduction

This case study of Zeotap is based on a September 2021 survey of Google Cloud Data Analytics customers by TechValidate, a 3rd-party research service.

“Google provides the end-to-end stack for analytics as a managed service right from raw data processing to tiered storage to BI tools. This reduces the operability concerns of the whole stack and the flexibility in choosing and scaling with decent cost control.”

“Cloud Data Fusion provides a unified abstraction to run a classic lambda architecture for your data-driven applications. This enables quick releases of data products with the broader items around metadata management, operability, and monitoring left to CDF.”

NPS: 8/10

Challenges

The challenges Zeotap were experiencing with their previous solution before switching to Data Fusion:

  • Integration projects being slow, complex, and high in overhead and maintenance cost
  • Requiring too much of their team’s time to manage/maintain

Use Case

The Google Cloud products that Zeotap uses:

  • BigQuery
  • Dataflow
  • Dataproc
  • Pub/Sub
  • Data Fusion
  • Composer

Results

Zeotap achieved the following results with Google Cloud Data Analytics:

  • They were able to migrate to Cloud Data Fusion within 1-6 months.
  • They saw a return on their investment after using Cloud Data Fusion within 1-6 months.
  • They realized a cost savings of 10%-30% with Cloud Data Fusion.

Looker Case Study

Volanty

Introduction

This case study of volanty is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Looker has been the most important data viz tool we have been using at our company. The most important reports and analyses are on Looker.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • Spreadsheets (e.g. Google Sheets, Excel)
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Conflicting metrics and/or data mistrust
  • Faced the following business challenges prior to implementing Looker:
    • The complexity of managing multiple platforms (cloud providers, applications, on-prem)
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Productizing and eventually monetizing data by serving it back to customers and partners
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Informing strategic opportunities

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Empowered users to self-serve
    • Freed up their data team to focus on more strategic initiatives
    • Offered better visualizations and dashboards
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker within 1-6 months.
  • Increased their revenue after implementing Looker in the following ways:
    • Improved customer satisfaction
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Productize and eventually monetize data by serving it back to customers and partners
    • Prove return on high-cost investment in data

Looker Case Study

Zoro.Com

Introduction

This case study of Zoro.com is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“We love Looker. It has helped our business save so many hours that used to be spent in SQL and Excel.

Being able to serve real-time data to our users and Executive Team has been key to Looker’s success here at Zoro."

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Conflicting metrics and/or data mistrust
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
  • Faced the following business challenges prior to implementing Looker:
    • The complexity of managing multiple platforms (cloud providers, applications, on-prem)
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics
    • End-user frustrations – self-service, ease of use, and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Productizing and eventually monetizing data by serving it back to customers and partners
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Created data governance at scale
    • Empowered users to self-serve
    • Freed up their data team to focus on more strategic initiatives
    • Lowered end-user frustration
    • Offered better visualizations and dashboards
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker within 1-6 months.
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Productize and eventually monetize data by serving it back to customers and partners
    • Prove return on high-cost investment in data

Looker Case Study

Prisa Noticias

Introduction

This case study of Prisa Noticias is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Leveraging Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class solutions that keep our development teams lean and focused on core competencies.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • Microsoft PowerBI
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
    • Real time analysis
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • The complexity of managing multiple platforms (cloud providers, applications, on-prem)
  • Experienced the following challenges with data before using Looker:
    • End-user frustrations – self-service, ease of use, and action

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Proving return on high-cost investment in data

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Empowered users to self-serve
    • Freed up their data team to focus on more strategic initiatives
    • Broke down data silos -encourage cross-functional data-driven collaboration
    • Provided the users an actionable interface that allows more than just reporting
    • Offered better visualizations and dashboards
    • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker within 1-6 months.
  • Increased their revenue after implementing Looker in the following ways:
    • New Customer acquisition
    • Decreased customer churn
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Productize and eventually monetize data by serving it back to customers and partners

Looker Case Study

Zoro.Com

Introduction

This case study of Zoro.com is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Leveraging Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class solutions that keep our development teams lean and focused on core competencies.”

“Looker empowers our company to focus on strategic initiatives and less time on manual ad-hoc tasks.”

“Looker has allowed the BI Team at Zoro to focus on solutions rather than ETL. The LookML models make it very easy to work with our data in our Zoro Data Platform and build code on top of our existing data.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Conflicting metrics and/or data mistrust
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • Prioritizing and consolidating data processes
    • Unpredictable costs
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics
    • End-user frustrations – self-service, ease of use, and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Productizing and eventually monetizing data by serving it back to customers and partners
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Reducing costs
    • Informing strategic opportunities

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Created data governance at scale
    • Freed up their data team to focus on more strategic initiatives
    • Broke down data silos -encourage cross-functional data-driven collaboration
    • Lowered end-user frustration
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Offered better visualizations and dashboards
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker within 1-6 months.
  • Increased their revenue after implementing Looker in the following ways:
    • New Customer acquisition
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Productize and eventually monetize data by serving it back to customers and partners
    • Prove return on high-cost investment in data

Looker Case Study

Tour Radar Gmb H

Introduction

This case study of TourRadar GmbH is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Looker empowers our company to focus on strategic initiatives and less time on manual ad-hoc tasks.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • Spreadsheets (e.g. Google Sheets, Excel)
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
  • Faced the following business challenges prior to implementing Looker:
    • Prioritizing and consolidating data processes
  • Experienced the following challenges with data before using Looker:
    • End user frustrations – self-service, ease of use and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Productizing and eventually monetizing data by serving it back to customers and partners
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Reducing costs

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Created data governance at scale
    • Empowered users to self-serve
    • Lowered end-user frustration
  • Saw a return on their investment in Looker in 12+ months.
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands: strongly agree
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Prove return on high-cost investment in data

Looker Case Study

Mercadolibre

Introduction

This case study of Mercadolibre is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Leveraging Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class solutions that keep our development teams lean and focused on core competencies.”

“Looker empowers our company to focus on strategic initiatives and less time on manual ad-hoc tasks.”

“Implementing Looker allowed to empower users with data.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • MicroStrategy
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Conflicting metrics and/or data mistrust
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • Prioritizing and consolidating data processes
    • Unpredictable costs
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics
    • End-user frustrations – self-service, ease of use and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Reducing costs

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Empowered users to self-serve
    • Broke down data silos -encourage cross-functional data-driven collaboration
    • Lowered end-user frustration
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
  • Saw a return on their investment in Looker within 7-12 months.
  • Increased their revenue after implementing Looker in the following ways:
    • Reduced development costs
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems:
    • Prove return on high-cost investment in data

Looker Case Study

Productboard

Introduction

This case study of Productboard is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Looker empowers our company to focus on strategic initiatives and less time on manual ad-hoc tasks.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • GoodData
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
  • Faced the following business challenges prior to implementing Looker:
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • End-user frustrations – self-service, ease of use, and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Empowered users to self-serve
    • Brokedown data silos -encourage cross-functional data-driven collaboration
  • Increased their revenue after implementing Looker in the following ways:
    • Improved customer satisfaction
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make the company more data-driven by giving their team secure access to the data they need

Looker Case Study

Docker

Introduction

This case study of Docker is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Looker empowers our company to focus on strategic initiatives and less time on manual ad-hoc tasks.”

“Looker is great at providing the entire company with access to data in a transparent manner to make data-driven decisions.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • Spreadsheets (e.g. Google Sheets, Excel)
    • Tableau
    • Mixpanel
  • Pain points that led them to begin looking for a new analytics platform:
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
  • Faced the following business challenges prior to implementing Looker:
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Informing strategic opportunities

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Empowered users to self-serve
    • Broke down data silos -encourage cross-functional data-driven collaboration
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker within 7-12 months.
  • Increased their revenue after implementing Looker in the following ways:
    • New Customer acquisition
  • Looker allowed them to:
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need

Looker Case Study

Mercadolibre

Introduction

This case study of Mercadolibre is based on a July 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Leveraging Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class solutions that keep our development teams lean and focused on core competencies.”

“Looker empowers our company to focus on strategic initiatives and less time on manual ad-hoc tasks.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • MicroStrategy
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Conflicting metrics and/or data mistrust
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • Prioritizing and consolidating data processes
    • The complexity of managing multiple platforms (cloud providers, applications, on-prem)
    • Consolidating digital assets
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics
    • End-user frustrations – self-service, ease of use, and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Reducing costs
    • Informing strategic opportunities
    • Proving return on high-cost investment in data

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Created data governance at scale
    • Empowered users to self-serve
    • Broke down data silos -encourage cross-functional data-driven collaboration
    • Lowered end-user frustration
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Provided the users an actionable interface that allows more than just reporting
    • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
  • Saw a return on their investment in Looker within 1-6 months.
  • Increased their revenue after implementing Looker in the following ways:
    • Reduced development costs
    • Improved customer satisfaction
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Prove return on high-cost investment in data

Looker Case Study

Ad Adapted

Introduction

This case study of AdAdapted is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Leveraging Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class solutions that keep our development teams lean and focused on core competencies.”

“Looker empowers our company to focus on strategic initiatives and less time on manual ad-hoc tasks.”

“Utilizing Looker allowed everyone on various teams to make use of all our data in the same place at the same time with ease.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
  • Faced the following business challenges prior to implementing Looker:
    • Agility to build & transform to meet customer demands
    • Competitive differentiation
  • Experienced the following challenges with data before using Looker:
    • End user frustrations – self-service, ease of use and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Productizing and eventually monetizing data by serving it back to customers and partners
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Informing strategic opportunities
    • Proving return on high-cost investment in data

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Created data governance at scale
    • Empowered users to self-serve
    • Freed up their data team to focus on more strategic initiatives
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Provided the users an actionable interface that allows more than just reporting
    • Offered better visualizations and dashboards
    • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker immediately.
  • Increased their revenue after implementing Looker in the following ways:
    • New Customer acquisition
    • Reduced development costs
    • Improved customer satisfaction
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Productize and eventually monetize data by serving it back to customers and partners
    • Prove return on high-cost investment in data

Looker Case Study

Prisa Noticias

Introduction

This case study of Prisa Noticias is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • Microsoft PowerBI
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
    • Real time analysis

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Uses the following bi platforms along with Looker:
    • No other bi platforms

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Empowered users to self-serve
    • Freed up their data team to focus on more strategic initiatives
    • Broke down data silos -encourage cross-functional data-driven collaboration
    • Provided the users an actionable interface that allows more than just reporting
    • Offered better visualizations and dashboards
    • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker within 1-6 months.
  • Increased their revenue after implementing Looker in the following ways:
    • Offering a premium analytics upsell
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems

Looker Case Study

Reliance Operations & Maintenance Services

Introduction

This case study of Reliance Operations & Maintenance Services is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“For the average user, using Looker to create Looks or Dashboards is easy.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Spreadsheets (e.g. Google Sheets, Excel)
  • Pain points that led them to begin looking for a new analytics platform:
    • Conflicting metrics and/or data mistrust
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • The complexity of managing multiple platforms (cloud providers, applications, on-prem)
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Broke down data silos -encourage cross-functional data-driven collaboration
    • Provided the users an actionable interface that allows more than just reporting
    • Offered better visualizations and dashboards
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker within 1-6 months.
  • Increased their revenue after implementing Looker in the following ways:
    • Improved customer satisfaction
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems

Looker Case Study

Disney

Introduction

This case study of Disney is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“The implementation of Looker, let us improve our data-driven strategy for the region.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • Prioritizing and consolidating data processes
    • Unpredictable costs
  • Experienced the following challenges with data before using Looker:
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Created data governance at scale
    • Empowered users to self-serve
    • Freed up their data team to focus on more strategic initiatives
    • Lowered end-user frustration
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker in 12+ months.
  • Increased their revenue after implementing Looker in the following ways:
    • New Customer acquisition
    • Reduced development costs
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Productize and eventually monetize data by serving it back to customers and partners
    • Prove return on high-cost investment in data

Looker Case Study

Do Something

Introduction

This case study of DoSomething is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

Challenges

The business challenges that led the profiled organization to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • Qlik
    • Sisense
    • Spreadsheets (e.g. Google Sheets, Excel)
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Conflicting metrics and/or data mistrust
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • Prioritizing and consolidating data processes
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics
    • End-user frustrations – self-service, ease of use, and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed organization uses:

  • Uses the following bi platforms along with Looker:
    • Google Data Studio
    • Spreadsheets (e.g. Google Sheets, Excel)
  • Priorities as a data leader:
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Reducing costs
    • Informing strategic opportunities

Results

The surveyed organization achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Offered better visualizations and dashboards
    • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
  • Increased their revenue after implementing Looker in the following ways:
    • Reduced development costs
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands

Looker Case Study

Karius Inc

Introduction

This case study of Karius Inc is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Able to transform our data lake into a data insights engine and ultimately enable faster time to insights for the company.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Domo
    • Google Data Studio
    • Spreadsheets (e.g. Google Sheets, Excel)
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Conflicting metrics and/or data mistrust
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
    • Multiple sources of truth
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • Prioritizing and consolidating data processes
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Uses the following bi platforms along with Looker:
    • Spreadsheets (e.g. Google Sheets, Excel)
  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Informing strategic opportunities
    • Proving return on high-cost investment in data

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Empowered users to self-serve
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Provided the users an actionable interface that allows more than just reporting
    • Offered better visualizations and dashboards
    • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
  • Saw a return on their investment in Looker immediately.
  • Increased their revenue after implementing Looker in the following ways:
    • Improved customer satisfaction
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Productize and eventually monetize data by serving it back to customers and partners
    • Prove return on high-cost investment in data

Looker Case Study

Vitta

Introduction

This case study of Vitta is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Implementing Looker allowed our business teams to be independent and autonomous to explore data.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Microsoft PowerBI
    • Metabase
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • End user frustrations – self-service, ease of use and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Uses the following bi platforms along with Looker:
    • Microsoft PowerBI
  • Priorities as a data leader:
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Informing strategic opportunities

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Empowered users to self-serve
    • Freed up their data team to focus on more strategic initiatives
    • Lowered end-user frustration
    • Provided the users an actionable interface that allows more than just reporting
  • Saw a return on their investment in Looker within 7-12 months.
  • Increased their revenue after implementing Looker in the following ways:
    • Decreased customer churn
    • Reduced development costs
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Productize and eventually monetize data by serving it back to customers and partners
    • Prove return on high-cost investment in data

Looker Case Study

Snapcommerce

Introduction

This case study of Snapcommerce is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“At the time of signing several members of upper management and our c-suite team had reservations about a new BI tool and the data work we had to invest in getting up and running. I vouched for the tool and ensured they would absolutely see the ROI once we could get it set up. Simultaneously, the data team was being absolutely swamped in adhoc requests to fix discrepancies, reporting errors, create slight modifications on existing reports, and teach the organization how to navigate SQL.

It’s been about a year now, and the only requests I get now are more and more teams asking to be in Looker. The first business team we onboarded to Looker are still in love with the tool and the freedom they have to find their own information. Our team can plan better because everything is no longer a last-minute, urgent fix. Our data professionals have so much more time for deeper analysis. Team satisfaction has improved. And our business has massively grown.

We don’t use Looker very much for defining business logic and I believe dbt in conjunction with Looker is a better solution for that. But Looker has been a big success at our company and it has put me in a very good light for advocating for it."

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Sisense
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Conflicting metrics and/or data mistrust
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
    • Speed/limitations of showing data
  • Faced the following business challenges prior to implementing Looker:
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics
    • End-user frustrations – self-service, ease of use, and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Uses the following bi platforms along with Looker:
    • Sisense
    • PopSQL
  • Priorities as a data leader:
    • Using data to identify new revenue opportunities or grow the business
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Informing strategic opportunities
    • Proving return on high-cost investment in data

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Empowered users to self-serve
    • Freed up their data team to focus on more strategic initiatives
    • Broke down data silos -encourage cross-functional data-driven collaboration
    • Lowered end-user frustration
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Provided the users an actionable interface that allows more than just reporting
    • Offered better visualizations and dashboards
    • Infused relevant information into the tools and products people already use (ex. Slack, Email, Teams, text)
    • Delivered data to external users such as customers or partners
  • Saw a return on their investment in Looker within 1-6 months.
  • Increased their revenue after implementing Looker in the following ways:
    • New Customer acquisition
    • Improved customer satisfaction
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk:
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Prove return on high-cost investment in data

Looker Case Study

Small Business Healthcare Company

Introduction

This case study of a small business healthcare company is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service. The profiled company asked to have their name blinded to protect their confidentiality.

“Leveraging embedded analytics with Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class data products that keep our development teams focused on core competencies.”

“We built a population Heath solution using Looker. We probably could not have scaled as quickly and see data across multiple facilities as easily if not for Looker. Again, I am not happy with the amount of time to load many of our dashboards and Looks. We use PDTs and we still have issues around speed.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following embedded analytics platforms before switching to Looker:
    • No other embedded analytics
  • Purchased an embedded analytics solution for the following reasons:
    • Need to create new revenue streams and monetize analytics
  • Experienced the following challenges before using Looker:
    • Did not use a product as we built our company around using Looker.

Use Case

Trying to achieve the following when purchasing an embedded analytics solution:

  • Create new products faster
  • Lower engineering costs to build new products
  • Increase revenue
  • Make the data team a driver of revenue and not a cost center

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Increased agility and competitiveness of internal and/or external data products and workflows
    • Experienced revenue growth from offering differentiated and premium data product experiences to customers
  • Saw a return on their investment in Looker within 1-6 months.
  • Seen a return on their investment in Looker in the following ways:
    • Improved customer satisfaction
    • Reduced development and maintenance costs
    • Increased revenue (e.g. drove upgrades with premium tier customer-facing analytics offering)
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • New customer acquisition
  • Agreed that Looker allowed them to:
    • Accelerate development time and build efficiently with modern APIs, SDKs and git software development workflows: agree
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk: agree
    • Drive greater product market fit with rapid prototyping and iteration: agree
    • Focus engineering resources on core competencies to minimize data development and delivery costs: agree
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs: strongly agree
    • Incentivize upgrades by strategically tiering unique and high-value data product capabilities in premium plans of their subscription product offering: agree
    • Delight users with beautiful, dynamic, and easy-to-use data product experiences: agree

Looker Case Study

Small Business Professional Services Company

Introduction

This case study of a small business professional services company is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service. The profiled company asked to have their name blinded to protect their confidentiality.

“Leveraging embedded analytics with Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class data products that keep our development teams focused on core competencies.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following embedded analytics platforms before switching to Looker:
    • SAP Business Objects
  • Purchased an embedded analytics solution for the following reasons:
    • Need to deliver more competitive data product experiences
    • Need to create new revenue streams and monetize analytics
    • Need to increase efficiency by infusing data into business workflows
  • Experienced the following challenges before using Looker:
    • Slow reporting
    • A lack of integrations

Use Case

Trying to achieve the following when purchasing an embedded analytics solution:

  • Lower lifetime cost of maintaining a product
  • Increase revenue
  • Transform the business to become more data-driven
  • Increase product reliability

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Being able to set-up data governance
  • Saw a return on their investment in Looker in 12+ months.
  • Seen a return on their investment in Looker in the following ways:
    • Improved customer satisfaction
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • Offering a premium analytics upsell
    • New customer acquisition
  • Looker allowed them to:
    • Accelerate development time and build efficiently with modern APIs, SDKs and git software development workflows
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make better data-driven decisions with built-in data product instrumentation and usage analytics
    • Drive greater product market fit with rapid prototyping and iteration
    • Focus engineering resources on core competencies to minimize data development and delivery costs
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs
    • Incentivize upgrades by strategically tiering unique and high-value data product capabilities in premium plans of their subscription product offering
    • Delight users with beautiful, dynamic, and easy-to-use data product experiences

Looker Case Study

Cadmium

Introduction

This case study of Cadmium is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Looker allowed us to leapfrog our competitors’ reporting solutions. It increased customer satisfaction and was a delight to implement.”

Challenges

Trying to achieve the following when purchasing an embedded analytics solution:

  • Need to deliver more competitive data product experiences

Experienced the following challenges before using Looker:

  • Slow data product development
  • High development costs
  • Missed competitive / revenue opportunities
  • Poor user experience
  • Siloed data sources

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Trying to achieve the following when purchasing an embedded analytics solution:
    • Create new products faster
    • Lower engineering costs to build new products
    • Iterate on products faster to achieve product market fit
    • Increase revenue
    • Increase product reliability

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Increased agility and competitiveness of internal and/or external data products and workflows
    • Reduced costs of software development, account management and/or operations
    • Experienced revenue growth from offering differentiated and premium data product experiences to customers
  • Saw a return on their investment in Looker within 1-6 months.
  • Seen a return on their investment in Looker in the following ways:
    • Improved customer satisfaction
    • Increased revenue (e.g. drove upgrades with premium tier customer-facing analytics offering)
    • Reduced customer churn
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • Offering a premium analytics upsell
    • New customer acquisition
    • Decreasing customer churn
  • Looker allowed them to:
    • Accelerate development time and build efficiently with modern APIs, SDKs and git software development workflows
    • Make better data-driven decisions with built-in data product instrumentation and usage analytics
    • Drive greater product market fit with rapid prototyping and iteration
    • Focus engineering resources on core competencies to minimize data development and delivery costs: strongly agree
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs
    • Incentivize upgrades by strategically tiering unique and high-value data product capabilities in premium plans of their subscription product offering
    • Delight users with beautiful, dynamic and easy-to-use data product experiences

Looker Case Study

Feedforce Inc.

Introduction

This case study of Feedforce Inc. is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Data aggregation into Looker and employee’s Explore skill are important to leverage the value to use Looker.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following embedded analytics platforms before switching to Looker:
    • No other embedded analytics
  • Purchased an embedded analytics solution for the following reasons:
    • Need to deliver more competitive data product experiences
    • Need to increase efficiency by infusing data into business workflows
  • Experienced the following challenges before using Looker:
    • Missed competitive / revenue opportunities
    • Inconsistent metrics
    • Poor user experience
    • An inability to realize the value of data

Use Case

Trying to achieve the following when purchasing an embedded analytics solution:

  • Lower lifetime cost of maintaining a product
  • Increase revenue
  • Transform the business to become more data-driven
  • Increase product reliability

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Increased agility and competitiveness of internal and/or external data products and workflows
  • Saw a return on their investment in Looker in 12+ months.
  • Seen a return on their investment in Looker in the following ways:
    • Increased revenue (e.g. drove upgrades with premium tier customer-facing analytics offering)
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • Offering a premium analytics upsell
  • Looker allowed them to:
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs
    • Delight users with beautiful, dynamic, and easy-to-use data product experiences

Looker Case Study

Crio Inc.

Introduction

This case study of CRIO Inc. is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Leveraging embedded analytics with Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class data products that keep our development teams focused on core competencies.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following embedded analytics platforms before switching to Looker:
    • No other embedded analytics
  • Purchased an embedded analytics solution for the following reasons:
    • Need to deliver more competitive data product experiences
    • Need to create new revenue streams and monetize analytics
    • Need to increase efficiency by infusing data into business workflows
  • Experienced the following challenges before using Looker:
    • Missed competitive / revenue opportunities
    • Poor user experience
    • An inability to realize the value of data

Use Case

Trying to achieve the following when purchasing an embedded analytics solution:

  • Lower engineering costs to build new products
  • Transform the business to become more data-driven

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Increased agility and competitiveness of internal and/or external data products and workflows
    • Reduced costs of software development, account management and/or operations
    • Experienced revenue growth from offering differentiated and premium data product experiences to customers
  • Saw a return on their investment in Looker within 7-12 months.
  • Seen a return on their investment in Looker in the following ways:
    • Improved customer satisfaction
    • Reduced development and maintenance costs
    • Increased revenue (e.g. drove upgrades with premium tier customer-facing analytics offering)
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • Offering a premium analytics upsell
    • New customer acquisition
  • Looker allowed them to:
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make better data-driven decisions with built-in data product instrumentation and usage analytics
    • Focus engineering resources on core competencies to minimize data development and delivery costs
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs
    • Incentivize upgrades by strategically tiering unique and high-value data product capabilities in premium plans of their subscription product offering
    • Delight users with beautiful, dynamic, and easy-to-use data product experiences

Looker Case Study

Headset

Introduction

This case study of Headset is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“I think for me the biggest benefit was the decrease in data architecture time. This allowed us to develop more products faster.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following embedded analytics platforms before switching to Looker:
    • Tableau
    • Sisense
    • Microstrategy
    • Power BI
  • Purchased an embedded analytics solution for the following reasons:
    • Need to deliver more competitive data product experiences
    • Need to increase efficiency by infusing data into business workflows
  • Experienced the following challenges before using Looker:
    • Slow data product development
    • An inability to realize the value of data

Use Case

Trying to achieve the following when purchasing an embedded analytics solution:

  • Create new products faster
  • Lower engineering costs to build new products
  • Iterate on products faster to achieve product market fit

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Increased agility and competitiveness of internal and/or external data products and workflows
    • Reduced costs of software development, account management and/or operations
    • Experienced revenue growth from offering differentiated and premium data product experiences to customers
  • Saw a return on their investment in Looker within 1-6 months.
  • Seen a return on their investment in Looker in the following ways:
    • Reduced development and maintenance costs
    • Increased revenue (e.g. drove upgrades with premium tier customer-facing analytics offering)
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • Offering a premium analytics upsell
    • New customer acquisition
    • Decreasing customer churn
    • Reducing development costs
  • Looker allowed them to:
    • Accelerate development time and build efficiently with modern APIs, SDKs and git software development workflows
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Drive greater product market fit with rapid prototyping and iteration
    • Focus engineering resources on core competencies to minimize data development and delivery costs
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs
    • Incentivize upgrades by strategically tiering unique and high-value data product capabilities in premium plans of their subscription product offering

Looker Case Study

Medium Enterprise Retail Company

Introduction

This case study of a medium enterprise retail company is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service. The profiled company asked to have their name blinded to protect their confidentiality.

“Conecting our new database – BigQuery – with the analytic tool”

“Leveraging embedded analytics with Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class data products that keep our development teams focused on core competencies.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following embedded analytics platforms before switching to Looker:
    • Qlickview
  • Purchased an embedded analytics solution for the following reasons:
    • User-specific filters on reports (access filters) and easy connection to BigQuery
  • Experienced the following challenges before using Looker:
    • High development costs
    • Slow reporting

Use Case

Trying to achieve the following when purchasing an embedded analytics solution:

  • Create new products faster
  • Transform the business to become more data-driven
  • Increase product reliability

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Increased agility and competitiveness of internal and/or external data products and workflows
  • Seen a return on their investment in Looker in the following ways:
    • Improved customer satisfaction
    • Reduced development and maintenance costs
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • Reducing development costs
  • Agreed that Looker allowed them to:
    • Accelerate development time and build efficiently with modern APIs, SDKs and git software development workflows
    • Focus engineering resources on core competencies to minimize data development and delivery costs
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs
    • Delight users with beautiful, dynamic, and easy-to-use data product experiences

Looker Case Study

Affinity

Introduction

This case study of Affinity is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Breadth of visualizations to support. Time to model data and support the level of filtering/pivoting that an end user needs. Range of export options to support (e.g. PDF).”

Challenges

Trying to achieve the following when purchasing an embedded analytics solution:

  • Purchased an embedded analytics solution for the following reasons:
    • Need to deliver more competitive data product experiences
    • Need to create new revenue streams and monetize analytics
    • Need to increase efficiency by infusing data into business workflows
  • Experienced the following challenges before using Looker:
    • Slow data product development
    • High development costs
    • Missed competitive / revenue opportunities
    • Slow reporting
    • Poor user experience
    • An inability to realize the value of data
    • Poor product performance

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Trying to achieve the following when purchasing an embedded analytics solution:
    • Create new products faster
    • Lower engineering costs to build new products
    • Lower lifetime cost of maintaining a product
    • Iterate on products faster to achieve product market fit
    • Increase revenue
    • Transform the business to become more data-driven

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Reduced costs of software development, account management and/or operations
    • Experienced revenue growth from offering differentiated and premium data product experiences to customers
  • Saw a return on their investment in Looker within 7-12 months.
  • Seen a return on their investment in Looker in the following ways:
    • Improved customer satisfaction
    • Increased revenue (e.g. drove upgrades with premium tier customer-facing analytics offering)
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • Offering a premium analytics upsell
    • New customer acquisition
  • Looker allowed them to:
    • Accelerate development time and build efficiently with modern APIs, SDKs and git software development workflows
    • Focus engineering resources on core competencies to minimize data development and delivery costs
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs
    • Incentivize upgrades by strategically tiering unique and high-value data product capabilities in premium plans of their subscription product offering
    • Delight users with beautiful, dynamic, and easy-to-use data product experiences

Looker Case Study

Aira

Introduction

This case study of Aira is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Leveraging embedded analytics with Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class data products that keep our development teams focused on core competencies.”

Challenges

Experienced the following challenges before using Looker:

  • Slow data product development
  • High development costs
  • Inconsistent metrics
  • Slow reporting
  • Poor user experience
  • Unreliability at scale
  • A lack of integrations

Use Case

Used the following embedded analytics platforms before switching to Looker:

  • Grow

Purchased an embedded analytics solution for the following reasons:

  • Need to deliver more competitive data product experiences
  • Need to increase efficiency by infusing data into business workflows

Trying to achieve the following when purchasing an embedded analytics solution:

  • Create new products faster
  • Lower engineering costs to build new products
  • Iterate on products faster to achieve product-market fit
  • Increase revenue
  • Transform the business to become more data-driven
  • Increase product reliability

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Increased agility and competitiveness of internal and/or external data products and workflows
  • Saw a return on their investment in Looker within 1-6 months.
  • Seen a return on their investment in Looker in the following ways:
    • Reduced development and maintenance costs
    • Reduced customer churn
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • Decreasing customer churn
    • Reducing development costs
  • Looker allowed them to:
    • Accelerate development time and build efficiently with modern APIs, SDKs and git software development workflows
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk: strongly agree
    • Make better data-driven decisions with built-in data product instrumentation and usage analytics
    • Drive greater product-market fit with rapid prototyping and iteration
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs
    • Delight users with beautiful, dynamic, and easy-to-use data product experiences

Looker Case Study

Fetch Robotics

Introduction

This case study of Fetch Robotics is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“We reduced our development and maintenance burden for our analytics package by at least 10x, and it is more reliable. We’ve also been able to move towards upsell packages which will eventually increase our revenue. There are some architectural issues with our multi-instance production integration, but overall things have been great.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following embedded analytics platforms before switching to Looker:
    • A homegrown embedded analytics platform
  • Purchased an embedded analytics solution for the following reasons:
    • Need to deliver more competitive data product experiences
  • Experienced the following challenges before using Looker:
    • Slow data product development
    • High development costs
    • Inconsistent metrics
    • Poor user experience
    • A lack of integrations

Use Case

Trying to achieve the following when purchasing an embedded analytics solution:

  • Create new products faster
  • Lower engineering costs to build new products
  • Lower lifetime cost of maintaining a product
  • Iterate on products faster to achieve product-market fit
  • Transform the business to become more data-driven
  • Increase product reliability

Results

The surveyed company achieved the following results with Looker:

  • Experienced the following benefits since implementing embedded analytics with Looker:
    • Increased agility and competitiveness of internal and/or external data products and workflows
    • Reduced costs of software development, account management and/or operations
  • Seen a return on their investment in Looker in the following ways:
    • Improved customer satisfaction
    • Reduced development and maintenance costs
  • Increased their revenue in the following ways after implementing embedded analytics with Looker:
    • Offering a premium analytics upsell
    • Reducing development costs
  • Looker allowed them to:
    • Accelerate development time and build efficiently with modern APIs, SDKs and git software development workflows
    • Drive greater product-market fit with rapid prototyping and iteration: strongly agree
    • Focus engineering resources on core competencies to minimize data development and delivery costs
    • Grow and improve their product easily overtime to minimize ongoing maintenance costs
    • Incentivize upgrades by strategically tiering unique and high-value data product capabilities in premium plans of their subscription product offering

Looker Case Study

State & Local Government

Introduction

This case study of a state & local government is based on a July 2021 survey of Looker customers by TechValidate, a 3rd-party research service. The profiled organization asked to have their name blinded to protect their confidentiality.

“Leveraging Looker, we have been able to increase our competitiveness and drive growth by rapidly building scalable, best-in-class solutions that keep our development teams lean and focused on core competencies.”

“Looker empowers our company to focus on strategic initiatives and less time on manual ad-hoc tasks.”

Challenges

The business challenges that led the profiled organization to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Barriers to entry – previous solution was difficult for people to extract the value they needed
  • Faced the following business challenges prior to implementing Looker:
    • Prioritizing and consolidating data processes
    • The complexity of managing multiple platforms (cloud providers, applications, on-prem)
    • Consolidating digital assets
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key priorities and goals as a data leader of the surveyed customer:

  • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
  • Improving operational visibility and inform strategic decision-making
  • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
  • Informing strategic opportunities

Results

The surveyed organization achieved the following results with Looker:

  • Experienced the following benefits since implementing Looker:
    • Created data governance at scale
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Provided the users an actionable interface that allows more than just reporting
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands: strongly agree
    • Make their company more data-driven by giving their team secure access to the data they need: agree
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems: agree

Looker Case Study

HP (Hewlett-Packard)

Introduction

This case study of HP, Inc. is based on a June 2021 survey of Looker customers by TechValidate, a 3rd-party research service.

“Stakeholders have been running their reports without cranking up sheets of data taking numerous hours. Now the data stories are not being presented through PowerPoint slides, but through almost real-time dashboards.”

Challenges

The business challenges that led the profiled company to evaluate and ultimately select Looker:

  • Used the following bi platforms before Looker:
    • Google Data Studio
    • Microsoft PowerBI
    • SAP BusinessObjects
    • Spreadsheets (e.g. Google Sheets, Excel)
    • Tableau
  • Pain points that led them to begin looking for a new analytics platform:
    • Providing access to insights/self-service
    • Conflicting metrics and/or data mistrust
  • Faced the following business challenges prior to implementing Looker:
    • Accessing a real-time view of the business
    • Prioritizing and consolidating data processes
    • Consolidating digital assets
    • Agility to build & transform to meet customer demands
  • Experienced the following challenges with data before using Looker:
    • A lack of governance – mistrust due to conflicting definitions and metrics
    • End-user frustrations – self-service, ease of use, and action
    • A lack of agility – flexibility to help them adapt as their needs change

Use Case

The key features and functionalities of Looker that the surveyed company uses:

  • Uses the following bi platforms along with Looker:
    • SAP BusinessObjects
    • Tableau
  • Priorities as a data leader:
    • Making the company more data-driven by enabling them to securely access the data they need in a manner appropriate for their role
    • Improving operational visibility and inform strategic decision-making
    • Freeing up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Reducing costs
    • Informing strategic opportunities

Results

The surveyed company achieved the following results with Looker:

  • Saw a return on their investment in Looker immediately.
  • Experienced the following benefits since implementing Looker:
    • Created data governance at scale
    • Empowered users to self-serve
    • Freed up their data team to focus on more strategic initiatives
    • Brokedown data silos -encourage cross-functional data-driven collaboration
    • Lowered end-user frustration
    • Provided leadership with improved access to accurate metrics they can use to guide strategy
    • Provided the users an actionable interface that allows more than just reporting
    • Offered better visualizations and dashboards
  • Increased their revenue after implementing Looker in the following ways:
    • Offering a premium analytics upsell
  • Looker allowed them to:
    • Help their data teams be agile, efficient, and keep data governed and controlled so they can better react to changing business demands
    • Make better business decisions, leading to more revenue, greater profitability, or reduced risk
    • Make the company more data-driven by giving their team secure access to the data they need
    • Free up high-value individuals (data analysts, data scientists) to work on high-impact problems
    • Productize and eventually monetize data by serving it back to customers and partners
    • Prove return on high-cost investment in data



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