What’s Working In Modern Analytics? Unifying Data Insights To Align Teams Around Metrics & Goals

Published: April 20, 2022

Gartner research revealed that by 2024, organizations that lack a sustainable data and analytics operationalization framework will have their initiatives set back by up to two years. On the other hand, McKinsey research found that companies effectively using analytics in service of marketing and sales performance are 1.5X more likely to achieve above-average growth rates than their peers.

In other words, “marketers are only as good as the data and analytics processes they have in place,” explained Cindy Chao, Sr. Manager of Product Marketing at Salesforce, in her B2BMX presentation. “We all know that more data doesn’t necessarily mean better insights; it can actually cause more friction across the customer journey for your sales, service and marketing teams — in addition to the customer itself.”

What separates the leaders from the laggards comes down to focus. B2B organizations generate an overwhelming amount of data and insights to fuel campaigns, so when they can sift through insights with the goal of identifying the strategies that work and those that need improvement, that’s where they’ll see the positive ROI.

“When your analytics and data efforts are focused on a particular set of KPIs and cleansed data, there’s magic there,” said John Fernandez, Sr. Vice President of Marketing for digital customer service platform Glia, in an interview. “When you figure out what to prioritize, you can get beyond data to gain meaningful insights and business decisions without drowning. Modern data analytics really comes down to determining what actions are driving revenue.”

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According to Salesforce research cited by Chao, less than 50% of marketers indicated they were happy and satisfied with aspects of their data hygiene, accessibility and completeness. Throughout this report, B2B experts will walk readers through the best ways to analyze metrics and identify trends or patterns in their data that optimizes sales and marketing strategies. Specific topics of discussion include:

  • The strategies marketing teams are implementing to streaming data collection and accessibility across their organization;
  • The importance of making analytics accessible to key stakeholders in real time;
  • The top metrics B2B organizations are looking to track as part of their analytics initiatives; and
  • Real-world case studies of organizations successfully refining their data analytics processes.

Streamlining Data Collection & Accessibility

Let’s first reframe the data narrative — words such as “overabundance,” “drowning” and “overwhelming” have negative connotations when really, a plethora of data isn’t a bad thing; it’s just messy. With marketers indicating they’re collecting data from from up to 15 sources, it’s important organizations can distill the insights into manageable chunks.

“I wish we only had four sources of data coming into our platforms, but in reality, there are dozens,” explained Brant Schmitz, Sr. Director of Digital Marketing at NBC Sports, in his B2BMX presentation with Chao. “For us, democratizing data is about finding that source of truth and leveling the playing field. It must be available to everyone in the organization, so if marketing, sales and revenue finance are all looking for customer data, they’re all starting from the same place and ensuring they have the fullest breadth of data available.”

To that end, the most popular strategy cited by the practitioners was collecting and housing all data in an easily accessible place for all departments: The CRM. And when it comes to inputting and collecting that data, Fernandez suggested that less is more.

“We’re past the old world of marketing only working with marketing automation and sales only working in the CRM,” Fernandez continued. “Putting everything in your CRM is very important, so at Glia, we tend to export everything. We also run lean on the technology side so that we can make sure our data is consistent across our systems.”

The other benefit of centrally storing data and ensuring key stakeholders have access to it? It breeds accountability. Fernandez explained “there’s a real integrity problem in data,” specifically in the exporting process, as the amount of data that’s post-produced in Excel and PowerPoint leaves the door open for “bad behavior” — i.e., cleaning up numbers to make them more attractive.

Proof Point: USAA Enabled Analysts To Pull Reports In Seconds

Since 1922, USAA has provided insurance and financial services to military and civilian members. The company’s risk analysts use data from multiple systems, including customer relationship management and business intelligence services — to help ensure that USAA is meeting its key performance metrics.

But having data in multiple places was a risk in itself, and the process USAA used for sorting data and building reports varied from person to person and team to team.

USAA turned to analytics platform Tableau, a Salesforce company, to connect all of its data sources and create dashboards and visualizations based on this newly centralized data hub. Tableau enabled USAA data workers to quickly build reports for internal and external stakeholders. Drawing the data from a unified, “single source of truth” helps USAA maintain consistency and accuracy across all reports.

As a result, speed and agility of information sharing have also improved dramatically. By unifying data and streamlining reporting with Tableau, analysts can now prepare reports in seconds, where previous processes could take up to one month and not be as consistent or accurate. Workers at all levels of the organization can now make faster, better decisions and feel more confident that the data they’re using is the right data.

Cutting Down On Measurement Metrics

Once all departments can easily access all the data insights, they must then be aligned on the metrics that matter. But with different teams prioritizing different metrics and success standards, it can be difficult to unite internally around an internal goal. Instead of operating on a granular measurement level where teams dive into the nitty gritty of click-through rates and email opens, the experts suggested applying a bigger picture approach to metrics that infuses both sales’ and marketing’s measurement methods for more accurate reporting.

“Oftentimes, measurement forces a leader to have a hard conversation where they’re comparing apples to oranges,” explained Bob Peterson, Principal Analyst at Forrester, in his B2BMX session. “But if you can think about applying multiple lenses to those metrics, you’re in a much better position to have an informed conversation with your leaders about what this looks like from a performance benchmark across all your routes to market.”

Across the funnel, Fernandez explained that he’s cut down “enormously” on what he measures across the early and middle stages. Instead of wondering what content is working or not, he takes a bigger picture approach to identify what actions are driving the most revenue and how he can maximize that strategy across his organizations.

“That lens has taken me largely away from a lot of the obsession that I used to have over looking at web analytics very heavily throughout the funnel — and given how much data we have, you can’t focus too highly there,” he said, continuing that his “revenue-focused” company primarily focuses on tracking:

  • What’s generating pipeline;
  • How pipeline is performing; and
  • The insights the company receives from analyzing its performance.

“Predicting future revenue growth or potential challenges is always the No. 1 business analytics project in any organization,” said Fernandez. “You want to have marketing in that conversation; you don’t want to have, ‘hey, we’re going to talk about a sales performance and then we’re going to look at some blog posts!’ That relegates marketing into the kiddie table. You need marketing involved in the conversation.”

Proof Point: InvoiceCloud Reduced Sync Errors Between Tech Stacks By 95% To Improve Pipeline

InvoiceCloud, an online payments solution, needed to implement new processes for optimizing its marketing and sales technology stacks and integrations to streamline its measurement and metrics.

Brooke Bartos, the company’s Director of Marketing Operations & Analytics at InvoiceCloud, developed a roadmap to take advantage of new opportunities for internal and external customer experiences, created checklists and resources to ensure the tech stacks were measuring campaigns accurately and efficiently and implemented new spreadsheets for urchin tracking modules (UTM) parameters and account data for more comprehensive attribution. To manage all this customer data, Bartos integrated Drift Email and ZoomInfo to help InvoiceCloud manage its contact information and helps its teams segment account data at the granular level.  

With these additions, InvoiceCloud was able to reduce its sync errors between tech stacks by 95%, improve pipeline and revenue generation and maximize marketing spend by vertical and persona.

Leveraging Analytics To Inform ABM Campaigns

Though 61% of marketers reported using an ABM strategy, only 5% have fully optimized their measurement, with nearly two-thirds remaining in the fledgling stages. To that end, Fernandez explained that his team operates with an “ABM lite” approach, which means the company vary narrowly focuses its efforts solely on its target audience.

“Our target market is in the 1000s, and there are two things that happen once you get to that level,” explained Fernandez. “On one hand, you can create a reasonably curated experience for each account, but on the other hand, you can’t do that with all accounts simultaneously. So you have to get intelligent with choosing your accounts and deciding who’s going to get the targeted outreach today.”

He continued that Glia is “reasonably intelligent” in determining which accounts are put into a cadence or ad campaign. Fernandez explained that his team looks for two things: Accounts who have just engaged with the company and those who haven’t received any recent outreach. To determine those accounts, Glia’s sales and marketing teams work together in their centralized CRM to analyze the account insights that inform those actions.  

Proof Point: How Bazaarvoice Increased Enterprise Pipeline 6X

Bazaarvoice, a user-generated reviews platform, wanted to better align its sales and marketing teams around its ABM initiatives. The company’s Sr. Global ABM Manager, Jennifer Leaver, helped create a unified ABM playbook that enabled marketing and sales to unify their go-to-market strategy and deliver targeted messaging and content to their key accounts. 

The playbook used insights gathered from select customer success and sales groups to inform the company’s ABM strategy, providing guidance on 1:many stage-based campaigns, 1:few campaigns for SMBs and 1:1 interactions for its top five enterprise accounts. Leaver also helped build out a new reporting network that would allow teams to measure the impact their ABM programs have on pipeline, win rates and deal velocity with target accounts. This allows the company to bridge the siloes between marketing and sales, while building improving their ability to gather and leverage engagement data for future ABM campaigns.

As a result of the playbook, Bazaarvoice saw a 6X increase in enterprise pipeline and 4X increase in revenue, along with an additional 58% growth in the number of SMB opportunities. 


Marketers are able to collect more data than ever before, but the ability to organize and utilize it is key to success. It’s no longer about manual processes and disjointed teams; the modern analytics landscape requires centrally stored databases that are accessible to all stakeholders. As internal teams work together to identify key metrics and work together in the measurement process, it creates more streamlined processes across the company and breeds a better customer experience.

“The folks that are succeeding are learning how to unite their data and tell stories with it,” said Fernandez. “You would think that is a core skill for us marketers, but it’s not always applied well to data, and that’s where frustration is starting to grow. Data is all about the insights you can generate from analyzing them.”

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