Marketing Operations

The Engine Room

In today’s data-driven go-to-market models, board members and executives have an insatiable appetite for data.  Everyone wants to understand how the pipeline is growing, how campaigns are performing, and how new technology investments are paying off.  While the demand generation team may be the one executing the campaigns and bringing in the leads, it is the operations team that is quantifying marketing’s contribution to the business in terms of pipeline, bookings, and ARR.  Ops often operates behind the scenes, but they have a massive influence on how decisions are being made.

No marketing deliverable gets higher levels of visibility with the board than analytics produced by the ops team.

SaaS Marketing Operations – Key Functions

SaaS and cloud providers are investing big bucks in technology to collect data and even more in the analysts trained to interpret it. That is why many of the “cool kids” in marketing want to be on the ops team. Compensation packages for highly-skilled martech engineers are beginning to rival those of developers. But pursuing a career path in operations is no easy feat. It requires mastering complex skills ranging from integrating dozens of different Martech systems to performing analytics on billions of data points each month.

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Tech Stack

  • Marketing automation
  • Generative AI
  • Account-based marketing

  • Identity resolution
  • Technographic/firmographic
  • Buyer intent data
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Process Design

  • Lead qualification
  • Attribution and scoring
  • Lead nurturing

  • Leads, deals, wins
  • Pipeline, bookings, revenue
  • Campaign effectiveness & ROI

  • Annual planning
  • Spend analysis
  • Variance-to-plan
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  • GDPR


Marketing Ops has responsibility for growing the marketing database that supports email, direct mail, advertising, and other lead gen programs. Most teams adopt a dual strategy for growing the database. First party data is collected from direct interactions with prospects then supplemented with data licensed by third parties sales intelligence tools. Examples of data sets marketing collects include:

  • Contacts & Accounts – Details about each of the accounts in the target market including the company name, location, and address. The names, titles, and contact details for each decision maker.
  • Techno & Firmographic – Marketing and SDR teams need details about each account’s revenue, products, and industry as well as their ERP, CRM, and cloud platforms.
  • Intent Data – Intelligence about who is researching your products, your category, or your competitors from online review sites, media properties, and other sources.
  • Identity & Behavior – Tracking web page views, content downloads, and webinar registrations for each prospect. Behavioral data is enhanced when prospects self-identify through form submissions.

MarTech Stack

There are 10,000 different marketing applications available for SaaS and cloud providers to choose from. In recent years, dozens of new categories have emerged to automate everything from gathering competitive intelligence to generating new content ideas. The explosion in AI technologies will likely result in another wave. CMOs and CROs habitually want to chase every new shiny object with the hope that tech will provide the answer. Ops teams will face a significant challenge managing the burgeoning tech stack and all the associated bespoke integrations.

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Arming the demand generation team with a tech stack that maximizes the odds of reaching potential buyers and converting them into leads. Marketing Ops performs the day-to-day administration of the tech stack as well as acting as the architect for data flows and integration between systems. Examples of key MarTech applications include:

  • Marketing Automation Platform – The central hub of the MarTech ecosystems, which houses the marketing database and campaign workflows. Used to distribute emails, capture website leads, and track subscription preferences.
  • Account-Based Marketing – Enables targeted and personalized campaigns to highest potential customers based upon firmographic criteria. Examples include running targeted ad campaigns on Facebook, LinkedIn, and Google.
  • Website Analytics – Tracking a wide variety of metrics about website activity including number of visitors, navigation paths, referral sources, ad conversions, and user demographics.

Data Privacy

CPRA for B2B Marketing

The California Privacy Rights Act (CPRA) is bringing GDPR-level privacy rights to the 40M residents of California. CPRA builds upon the original CCPA legislation that went into effect in 2020.  Although much of the language in CPRA targets B2C marketing programs, the regulations apply to B2B marketing programs as well.

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Metrics & Analytics

Today’s marketing organizations are assigned quantifiable goals and quotas such as the number of leads booked or the dollar value of pipeline created. Marketing Ops tracks all the KPIs and provides regular reporting. In addition, the Ops team analyzes the performance of different campaigns and channels to help demonstrate the ROI of spend. Examples of the types of metrics tracked include:

  • Leads, Deals, Wins – Reporting on the quantity of marketing sourced leads (MQLs and SQLs) into the top of the funnel. Equally important is the number of leads that convert into sales opportunities and closed business.
  • Pipeline, Bookings, ARR – Quantifying the dollar value of marketing-sourced leads. Depending upon the company, the value might expressed in terms of ARR, ACV, or TCV as they convert from pipeline to bookings to revenue.
  • Ad Impressions, Clicks, Conversions – Analyzing the return on advertising spend from paid search and display campaigns. Understanding the conversions to content downloads, demo requests, and free trials.

Popular SaaS Marketing Metrics

CEOs have finally gotten religion around the importance of lead generation to growth. As a result, all eyes are on the pipeline and top of funnel metrics. Marketing operations teams are responsible for the “high visibility” metrics on MALs, MQLs, and SQLs to board members, investors, and executives. As marketing decisions continue to be more data-driven the role of marketing operations is likely to evolve from a support function enabling the team to more of a strategic function that is driving decision making.

Marketing Qualified Leads
Lead to Win Conversion
Customer Acquisition Cost
Sales Qualified Lead (SQL)
Last Touch Attribution
Marketing Sourced Bookings
Email Clickthrough Rate
Pipeline Velocity
Return on Advertising Spend
Total Pipeline Generated

Process Design

SaaS marketing organizations have millions, if not billions, of interactions with potential buyers each year. The data points need to be analyzed and scored to determine which qualify as a lead, where the lead should be routed, and how the lead should be attributed. Marketing Ops teams need to work closely with BDRs, sales, and partner organizations to design process flows for:

  • Qualification & Scoring – Defining criteria for leads to advance to MAL, MQL, SQL. Scoring leads based upon firmographic, technographic, and behavioral intelligence data.
  • Lead Routing – Automating the distribution of new leads to BDRs, sales reps, and customer success managers based upon territory assignments and existing relationship scope.
  • Lead Attribution – Assigning credit for the lead to the first known engagement, last touchpoint before conversion, or the weighted average of multiple different steps.
  • Nurturing – Maintaining a regular cadence of communications with future potential leads until the prospects meet the qualification criteria for sales engagement.

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