case study: label insight building the perfect data stack. · case study: label insight building...
TRANSCRIPT
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.
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C O N T A C T:
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