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3 Marketing Pipeline Management Problems (And How to Fix Them)

4 min

With 83% of CEOs expecting their CMOs to drive revenue growth, generating pipeline sits at the top of the modern marketing leader’s to-do list.

An enormous martech ecosystem has flourished to help marketers plan and execute strategies that generate revenue. But most marketing leaders have been missing a single system to plan, forecast, and track the very mechanism that drives revenue: pipeline.

This means marketing pipeline management has remained a dark art, completed in spreadsheets or homegrown tools and often based on gut feelings, not data. So, it’s no surprise that Forrester found 85% of B2B organizations regularly miss their monthly forecast by more than 5%.

We’ve looked at why marketers are still relying on guesswork for pipeline management, the problems it causes, and how marketers can fix these issues using AI.

Pipeline Management: Three Key Questions

To confidently manage your pipeline, and build credibility with the C-suite, marketing leaders need to be able to consistently answer three questions:

  • What’s our revenue goal and how will we reach it? (Plan)
  • How are we tracking against that plan? (Forecast)
  • Which targets, programs, and activities will get us there? (Insight)

The answers to these key questions should be readily available (and not require hours of spreadsheet math). But, for the majority of marketers, pipeline management is based on time-consuming trial and error, ballpark figures, and static benchmarked figures, making it impossible to predict with any conviction.

Disconnected Data Creates Confusion

Frustratingly, the data needed to put together the pieces of the pipeline management puzzle is available — but it’s shackled by disconnected systems and processes that keep customer insights and knowledge locked up in silos across the organization.

Without a unified view of customers or prospects, or a clear understanding of what’s working to engage and attract buyers, marketers face problems across every stage of pipeline management.

Problem 1: Pipeline Planning

The principles behind planning pipeline and answering “What’s our revenue goal and how will we reach it?” are straightforward enough:

  • Know the revenue number you need to hit
  • Work out what you need to achieve at each stage of the buying journey to get there

But predicting each stage involves calculating sales cycles, conversion rates, and average deal sizes. And that’s before you consider differences across geographies, regions, and solutions.

All these variables mean even small mistakes at the planning stage lead to big discrepancies down the line. And because of manual processes and incomplete data sets, errors are common.

Problem 2: Pipeline Forecasting

Just as pilots use the 1 in 60 rule to regularly check and correct their heading, marketers need a way to continuously check that pipeline is trending in the right direction. Smart CMOs proactively forecast pipeline to avoid surprises and adapt their plans and spend based on how they’re tracking against target.

But the ability to predict marketing pipeline starts with understanding historical performance across:

  • Market segments
  • Territories
  • Channels
  • Sources
  • Stages
  • Average conversion times

Many companies’ data isn’t complete enough to analyze historic opportunities in this much detail. And even if data quality isn’t an issue, the skills needed to dissect, understand, and action this data are rarely found in internal marketing teams.

This often leads to a DIY approach, waiting around for answers from analysts, or the most dangerous pipeline forecasting tactic of all — crossing your fingers and hoping.

Problem 3: Pipeline Insights

Most marketers create a linear pipeline plan based on generating a certain number of leads per quarter. In reality, new pipeline ebbs and flows. Whether you’re facing seasonal downturns or poor performance on specific channels, you need to be able to react rapidly to shortfalls in your pipeline.

To do this effectively you need the right insights at your fingertips. This means clear visibility of KPIs like:

  • Qualified pipeline
  • Average deal cycles
  • Which programs and activities are performing
  • Which accounts are most likely to close

Knowing at a glance what is and isn’t working means you can pause activities that aren’t driving pipeline, double down on the ones that are, and dive deeper into unexpected trends.

But the same barriers apply. Data housed across multiple systems, combined with pain-staking spreadsheet analysis, means marketing leaders don’t have a quick and easy way to see the pipeline insights that matter.

How Applying AI Fixes Pipeline Management Problems

We’ve seen that inaccurate or inaccessible data is often the source of marketers’ pipeline management woes. It leads to guesswork and error.

AI helps take the problems out of pipeline management by pulling data across silos to provide a unified view of your customer or prospect. It crunches past data, snapshots, trends, seasonality, and threats to give you a clear picture of past, present, and future pipeline performance.


AI uncovers historical data to project actual conversion rates, opportunity sizes, and sales cycles for each go-to-market segment so you can:

  • Plan with confidence
  • Plot across market segments, e.g., enterprise vs. mid-market, or EMEA vs. APAC
  • Run scenarios around how increasing or decreasing budget within channels or business units will impact your plan


AI-powered analysis of past and present forecasting allows you to take a pulse check and:

  • See if you’re on course for the quarter and year
  • Understand how individual segments, channels, or industries are trending in real-time
  • Check if deals are moving quickly enough through the buying journey


Get real-time visibility into current performance and the KPIs you need for decision making. If you’re not tracking on target, AI provides smart recommendations to plug pipeline gaps, including:

  • Taking targeted action to find the shortest path to revenue
  • Seeing which accounts to prioritize to hit revenue goals
  • Knowing which activities are generating pipeline to prioritize marketing spend

See how 6sense Revenue AI™ Can Help You Hit Goals

6sense Revenue AI provides marketers and sales teams the insights they need to close more deals, more quickly, with higher deal values. We combine intent signals, an embedded CDP, and AI and machine learning to generate actionable insights.

We also share data seamlessly with the tools you already use, like Salesforce, HubSpot, Microsoft Dynamics 365, Marketo, Drift, Mutiny, Salesloft, and many more.

Book a demo to see the platform in action and discover how it can add power and simplicity to your tech stack.

The 6sense Team

6sense helps B2B organizations achieve predictable revenue growth by putting the power of AI, big data, and machine learning behind every member of the revenue team.

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