Salesforce unlocks marketing insights faster with Google
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Case Study
Salesforce unlocks marketing insights faster
with Google Analytics 360
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Analytics 360
The Goals
A single interface for reporting across all
Salesforce-owned sites
Measure the impact of paid digital ads
A seamless user journey with relevant
messaging for each customer segment
The Approach
Restructure previous analytics framework
Use BigQuery to analyze over 50 different
site metrics
Use BigQuery ML’s K-means clustering to
develop customer segments
Use Analytics 360 to measure campaign
performance and optimize investment across
channels
The Results
Faster availability of campaign and user
engagement insights
86% of multichannel performance reports
unified with native product integrations
San Francisco-based Salesforce is known for its
customer relationship management (CRM)
platform. The platform helps businesses around
the world connect their marketing, sales,
commerce, service, and IT teams – giving
businesses a shared view of their customers to
help drive business growth.
Recently, Salesforce saw an opportunity to
unify its own view of its customers. Salesforce
had been using an analytics tool that provided
reporting across all of its websites, but even
compiling basic reports was complex and took
too long. Plus, reports of user journeys across
the Salesforce websites were disjointed,
meaning that unified user engagement insights
across properties like the corporate blog and
product pages slipped through the gaps.
Understanding the impact of multiple visits, or
connected visits, was difficult for the team.
Multi-Channel Funnels wasn't
possible, either. With its legacy tool,
Salesforce wasn’t able to evaluate the impact
that various marketing channels – for example
paid digital ads, email campaigns, or paid
search – were having on conversions on its
website. Salesforce knew that they were leaving
insights on the table, and began searching for
a more integrated solution.
The move to Google Analytics 360
To prioritize what its teams needed in a new
solution, Salesforce ran an internal survey,
asking what expectations everyone had for an
analytics tool, the problems the teams wanted
to solve, and the type of support they needed
along the way.
Next, Salesforce worked alongside partner
Cardinal
Path to restructure how their organization
approached digital analytics. Their key
objective throughout the restructuring was
simplicity and data democratization, which is
one of the reasons they turned to
Analytics 360, part of Google Marketing
Platform, for their new analytics solution.
Another factor in Salesforce's decision to
implement Analytics 360 was its simple,
streamlined integration with Salesforce Marketing Cloud. With
this combination of solutions, the team could
trigger personalized customer email journeys,
and optimize the website experience and
journeys across different channels.
“Salesforce’s move to Analytics 360 is a
milestone in raising our digital maturity,”
says Michael Andrew, Vice President, Data, AI,
and Personalization. “The advanced marketing
analytics capabilities of Google combined with
the power of Salesforce’s CRM data will enable
Salesforce’s marketers to make better decisions
to drive ROI and customer success.”
To ramp up adoption of Analytics 360 across
teams, Salesforce held internal trainings, and
set up office hours so that anyone could come
in and ask questions or get some guidance for
troubleshooting.
Now fully integrated, Salesforce has a single
interface for reporting across all
Salesforce-owned sites. The teams can also
drill down into insights about their own work
on the website. Salesforce’s digital marketing
team can now access both campaign and user
engagement insights faster than before.
Audience Analysis Segmentation
One of the goals for the digital marketing
team’s new analytics tool was to really
understand which audiences were visiting their
website, and how to segment them for the most
effective messaging and a seamless user journey
ahead.
Using Google Cloud’s enterprise data warehouse,
BigQuery. Salesforce created and
trained machine learning models within BigQuery
to unearth behavioral patterns across more than
50 different metrics. Using BigQuery ML’s
K-means clustering model, they created unique
customer segments and categorized users into
five personas based on those insights. Each
persona, they discovered, had a unique
preference for the type of content they found
the most engaging. “Consideration Clare,” for
example, was drawn to videos.
Now, Salesforce is building on this insight.
They’re finding new ways to optimize content
recommendations to the relevant user personas,
in order to encourage site visitors to convert
to customers.
Integrated Campaign Analysis
The team also needed to understand the
performance of marketing campaigns and optimize
their investment across channels. They also
used Analytics 360 to meet these goals, as it
identified traffic sources, matching the right
channel to the incoming traffic from sources
such as auto-tagging enabled by product linking
and UTM tags.
Now, the team can understand which digital
media efforts produce the best results,
creating better targeted campaigns. Salesforce
can also access full-funnel reporting, and
measure visitors and engagement across all
their web properties.
For an even fuller integration, Salesforce
teams are building dashboards through their own
internal platforms to combine Analytics 360
campaign traffic data with Salesforce CRM
conversion data for one view. This way,
campaign managers can compare various
campaigns, and easily see the ROI of
advertising efforts.
Looking Ahead with Analytics 360
“Our Analytics 360 implementation has
modernized our digital marketing analytics
infrastructure, while supporting its
digital-first imperative.”
Michael
Andrew, Vice President for Data, AI, and
Personalization, Salesforce
As for next steps, Salesforce is working on
widely spreading the benefits of Analytics 360
across the company. The teams are preparing to
integrate the solution into even more of their
digital properties, including Trailhead and AppExchange.
“The end goal of all of this will be the
ability to pull in data across the board, so
the customer journey is visible and
personalized across every stage,” says Michael.
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