C A S E S T U D Y : L A B E L I N S I G H T

Building the

Perfect Data Stack.

Results

• 200% ROI through freeing up 140 hours of manual reporting weekly

• Brings together data from multiple sources into a single source of truth

• Enables faster and more detailed analysis plus additional insights for clients

• Used by 70% of the company’s team

Label Insight

Label Insight provides comprehensive data about what’s in the products we buy, delivering

transparency to consumers by powering analytics, marketing, merchandising, and

ecommerce solutions for retailers and manufacturers. It covers more than 80% of top-selling

food, pet, and personal care items in the United States and creates more than 22,000

high-order attributes per product.

Customer

S I N G L E S O U R C E O F T R U T H S A V E T I M E A N D M O N E YD E E P E R L E V E L O F I N S I G H T S D A T A D R I V E N C U L T U R E 2 0 0 % R O I

This case study was originally produced and published by Google.

To view electronically, please visit: cloud.google.com/customers/label-insight/

3 C A S E S T U D Y : Label Insight fivetran.com

S U M M A R Y :

Fivetran data connectors enables Label Insight to

bring all its data into a single BigQuery database

and create a single source of truth for its CPG

information. Now 70% of the Label Insight team

uses Looker each week to run analytics on that

data – driving value for corporate customers and

end consumers.

• 200% Return on investment through freeing up 140 hours of manual reporting weekly

• 17 data sources incorporated into a single source of truth

FivetranConnectorsFully-managed

Standardized schemas

5-minute setup

The modern data stack

BigQueryData WarehouseFully-managed

Fast and cost-effective

Highly scalable

Looker BusinessData analytics for all

Single source of truth

Ask any question with SQL

While using data more effectively is important for every business, at Label Insight using data more effectively is the business.

The company is quickly becoming the go-to provider for product data; if

consumers, retailers or regulators want to know what’s in a packaged food,

drink, or personal care product, Label Insight is often the source. It captures

information from product labeling, then creates more than 22,000 unique

attributes per product, from micro and macronutrient content, allergens,

and sustainability practices, to specialty diet eligibility.

Label Insight then works with retailers and Consumer Packaged Goods (CPG)

manufacturers to help them gain deeper insights about their product set

and inventory and meet the increasing consumer demand for transparency.

Label Insight helps CPG brands participate in the SmartLabel transparency

initiative, which provides detailed product information to consumers online.

“We can derive around 22,000 attributes from product

data,” explains Jim Shedlick, Director of Architecture at

Label Insight, “from whether something is paleo-diet

approved to whether ethical claims can be justified.” With

the company now holding data on over 400,000 consumer

products, that’s a huge volume of information.

Lots of data, no warehouse

Although Label Insight had a lot of processes to collect, transform, digitize,

and QA data, the company didn’t have a data warehouse. “We had a bunch

of databases and people had to work directly in them to access product

information,” Jim says. That could require looking in several different tools

to gather the relevant information to respond to queries—a time-consuming

process, which meant the company’s ability to scale depended on

increasing its headcount of operational staff to answer questions.

The lack of integration also limited the company’s ability to analyze data

across categories. Along with product information, Label Insight also

captures a substantial volume of event data relating to how consumers

access information—using apps, scanning QR codes, or simply searching

online—and what kind of searches are most popular. That kind of data has

the potential to provide valuable insight for retailers and manufacturers to

improve on-package information or support targeted marketing.

4 C A S E S T U D Y : Label Insight fivetran.com

The commercial choice

Jim and his colleagues were increasingly aware of these limitations—and

particularly the missed commercial opportunities. Having identified more

than 40 use cases for improved business intelligence and analytics, they

decided to trial three cloud-based data warehouses, all of which appeared

to offer the scalable, single platform that Label Insight needed. However,

one stood out in several areas: BigQuery.

With BigQuery, Label Insight wouldn’t have to pay for data ingestion—which

one of the rival offerings required. Another important differentiator was that

BigQuery separates compute from storage—both technically, using different

hard disk space within the cluster, and commercially.

“You pay for both storage and compute separately as you use them,” Jim

confirms. “Storage is relatively low cost, and when we started, we didn’t

really need the compute element; we were building up our use cases, our

models, and dashboards. Once we had built up enough data in BigQuery

to run useful models, we could start paying for compute.” As a result, the

upfront costs were lower, reducing the barrier to entry.

Another key advantage for Jim was that BigQuery is a completely

managed service, so there was no need to acquire additional servers

or factor in IT management.

Seventeen sources collated in minutes

Another crucial factor in the decision to deploy BigQuery was the

availability of Google Cloud partners Fivetran and Looker. Fivetran simplified

the implementation, while Looker offered Label Insight the essential

analytical capabilities.

Like BigQuery, Fivetran is also a fully-managed service, which focuses on

enabling data to be centralized into cloud data warehouses. It has developed

over 100 connectors that gather data from different applications, file stores,

databases, and event streams into a single central data warehouse—such

as BigQuery - with minimal set-up. Invaluably, no transformation is required;

Fivetran cleans and normalizes the data itself. The result: data can be

collated from multiple sources in minutes.

For the complex landscape of Label Insight’s data, which was spread across

17 sources including Salesforce, HubSpot, and Zendesk, this ability was

priceless. “Fivetran is really simple in a good way,” says Jim. “They extract

the data and load it into the warehouse in the format you want. We just trust

them to do that.”

Sources Connected

• Asana

• DynamoDB

• Google Analytics

• Jira

• Kinesis Firehose

• MySQL

• RDS

• Postgres RDS

• Amazon S3

• Salesforce

• Zendesk

“Fivetran is really simple

in a good way. They extract

the data and load it into the

warehouse in the format you

want. We just trust them to

do that.”

Jim Shedlick, Director of Architecture

Label Insight

5 C A S E S T U D Y : Label Insight fivetran.com

200% return on investment

With the data combined to form a single source of truth, Label Insight can

then use Looker to analyze it—from running ad hoc queries to creating

dashboards for different users. Looker has proved to be highly intuitive for

the Label Insight team, who use it to quickly find product and manufacturer

information from multiple sources.

Jim estimates that his colleagues have now set up over 100 Looker dash-

boards, providing regular updates on different aspects of Label Insight’s

data and operation—from how many new products are waiting

to be analyzed to how many views a particular manufacturer’s products

have received on SmartLabel. Some are for internal monitoring, others

designed to share with corporate customers. It’s also easy to drill down

from the dashboards to access more detailed information about individual

products or specific topics.

“With Looker, we’ve been able to achieve far greater

responsiveness to customer information requests. Instead

of having to search separate tools, the team can now find

answers in the data far more quickly,” explains Jim.

To measure the business value of introducing the new solution, Jim asked

staff to report how much time they were saving by using the new solution.

On average, two hours per customer per week were saved on completing

internal process reports for customers and a further hour per customer per

month on SmartLabel analytics reporting.

“In total, we’re saving 140 hours of manual reporting time each week. We

multiplied that by how much an hour costs the business and compared that

cost to the total price of using BigQuery, Fivetran, and Looker. The return on

investment was double what we’d spent.” Instead of spending time on data

management and administrative tasks, the team can now focus more on

generating valuable insights for customers.

The strong return reflects the popularity of the solution within Label Insight.

“Over 70% of our team/employees are using the data stack, running queries

and viewing Looker dashboards, each week,” says Jim. Together, the

combination of BigQuery, Fivetran, and Looker is helping Label Insight move

to a culture where the whole company is able to perform, review, and benefit

from rich data.

“In total, we’re saving

140 hours of manual

reporting time each week.

We multiplied that by how

much an hour ‘costs’ the

business and compared that

cost to the total price of

using BigQuery, Fivetran and

Looker. The return on invest-

ment was double what we’d

spent.”

Jim Shedlick, Director of Architecture

Label Insight

6 C A S E S T U D Y : Label Insight fivetran.com

New possibilities from consolidated data

The initial returns don’t even include additional opportunities provided by

the new solution, particularly in terms of incorporating event data. “With

the help of Fivetran, we’ve created an event pipeline into BigQuery that

allows us to compare and analyze events alongside other data. Fivetran has

a connector that allows us to take all the event data directly from our web

services into BigQuery as immutable event logs. We can then analyze those

events in Looker like any other data.”

Data relating to over 400 million events is now stored in BigQuery—a

figure that increases at a rate of a couple hundred events per minute. It is

therefore a real benefit that Fivetran automatically adapts to changes in

the source data. With this wealth of additional information at its fingertips,

Label Insight is able to provide its customers with richer insights about the

way consumers interact with the product information, opening up new use

cases. “We can derive deeper insights, identify trends more quickly, and

provide customers with talking points that help drive product

development,” Jim says.

Working well together

The sheer volume of data is now prompting further exploration as to how

to best manage and manipulate it, including taking a closer look at Google

Google Cloud Dataflow. This is one of a handful of Google Cloud Services that

Label Insight is considering, along with Cloud Vision API with its high-quality

optical character recognition (OCR), which could accelerate the initial

input of packaging data with accurate scanning and recognition of words

on packages. “One of the advantages of consolidating data in BigQuery is

that it’s easy to adopt other Google Cloud solutions as our business needs

evolve,” Jim says.

“They’re all great companies to work with. They take our

feedback, and they’re quick to respond. We have close

relationships with Fivetran, Looker, and Google, and all

three have spent time on site providing training and

support. Best of all, they really work together.”

Whatever direction Label Insight decides to take, Jim is confident that the

support and service he will receive from Google and its partners will be a real

asset. “They’re all great companies to work with,” he says. “They take our

feedback, and they’re quick to respond. We have close relationships with

Fivetran, Looker, and Google, and all three have spent time on site providing

training and support. Best of all, they really work together.”

“We can derive deeper

insights, identify trends

more quickly and provide

customers with talking

points that help drive

product development”

Jim Shedlick, Director of Architecture

Label Insight

Fivetran

Fivetran is the easiest way to replicate data into your warehouse. Its zero-configuration

connectors bring data from applications, databases, events and file storage into one

central location. The standardized cloud pipelines take just a few minutes to setup, are

zero-maintenance, and fully-managed by Fivetran.

Looker

Google Cloud Technology Partner Looker provides a uniquely powerful data analytics platform

that helps companies get real value from their data. Connecting directly to core databases,

such as BigQuery, Looker allows anyone to ask sophisticated questions of the data using familiar

business terms – helping build a data culture.

Label Insight

Label Insight provides comprehensive data about what’s in the products we buy – delivering

transparency to consumers by powering analytics, marketing, merchandising and ecommerce

solutions for retailers and manufacturers. It covers more than 80% of top-selling food, pet, and

personal care items in the U.S and creates more than 22,000 high-order attributes per product.

BigQuery

BigQuery is Google’s serverless, highly scalable, cost-effective and fully-managed enterprise

data warehouse for analytics at any scale. It is fast, easy to use on data of any size, and

designed to make all your data analysts productive. BigQuery allows organizations to capture and

analyze data in real-time to find meaningful insights and securely share them within the

organization and beyond.

Customer

Data Stack

See how we can help you by setting

up a demo with a product specialist

or starting your free trial.

W E B S I T E :

C O N T A C T:

fivetran.com

sales@fivetran.com