Most marketing teams can tell you exactly how many blog posts they published last quarter. Fewer can tell you what those posts actually produced. And almost none can trace a straight line from their daily work to business impact.
This is the core problem the logic model solves.
What is a logic model?
A logic model is a structured framework that maps how your work actually creates results. Originally developed for programme evaluation (the W.K. Kellogg Foundation and University of Wisconsin-Extension are the canonical sources), it breaks any initiative into five connected components:
Table of contents
Open Table of contents
Why marketing teams need this
Your team published 40 blog posts, launched 3 campaigns, redesigned the homepage, and sent 200,000 emails. The CMO asks: “What did all that produce?”
Silence.
The logic model forces you to think beyond deliverables. Publishing 40 blog posts is an output. Generating 500 qualified leads from those posts is an outcome. Growing pipeline by 30% is impact. These are different things, and conflating them is how marketing teams lose credibility.
As Jeff Bezos wrote in his 2009 letter to Amazon shareholders: “We take these financial outputs seriously, but we believe that focusing our energy on the controllable inputs to our business is the most effective way to maximize financial outputs over time.”
Bezos understood the logic model intuitively. Control the inputs. Do the right activities. The outputs, outcomes, and impact follow — but only if the chain is intact.
Breaking down each component
Inputs: what you invest
Inputs are the resources your marketing team brings to the table: people, budget, technology, data, partnerships, and time. These are the raw materials.
Most teams undercount their inputs. They think about budget and headcount but forget about data quality, existing content libraries, brand equity, and partner relationships. A complete picture of inputs helps you understand what you are actually working with — and where you are constrained.
This connects directly to finding your growth levers. The inputs available to you determine which levers you can pull.
Activities: what you do
Activities are the work itself. Running experiments, writing content, optimising landing pages, building conversion funnels, managing channels. This is where most marketing teams spend their attention — and where they get stuck.
The trap is treating activities as the goal. “We ran 15 experiments this quarter” tells you nothing about whether those experiments produced anything useful. Activities matter, but only as a means to an end.
A strong growth system turns activities into repeatable processes. But the system only works if those activities actually connect to measurable results downstream.
Outputs: what you produce
Outputs are the tangible, countable things your activities create. Blog posts published, emails sent, ads running, landing pages live, experiments completed. These are easy to measure, which is exactly why teams over-index on them.
Outputs are not results. They are evidence that work happened. The distinction matters because optimising for outputs instead of outcomes is the most common way marketing teams waste resources. You can ship a mountain of content and move no business needle whatsoever.
Outcomes: what changes
Outcomes are the measurable changes that result from your outputs reaching the right audience. More qualified leads. Higher conversion rates. Shorter sales cycles. Better retention. Outcomes answer the question: “Did our work actually change anything?”
This is where your driver metrics live. If your goal metric is revenue (impact), your driver metrics — landing page conversion rate, demo booking rate, trial-to-paid conversion — are outcomes. They are leading indicators that something is working.
Your North Star Metric sits at the outcome level too. It measures the value your product delivers to customers, not just the things you shipped.
Outcomes can be layered by timeframe:
- Short-term outcomes: awareness, engagement, leads generated
- Medium-term outcomes: behaviour changes, pipeline created, activation rates
- Long-term outcomes: customer retention, expansion revenue, market position
Impact: the ultimate result
Impact is the final link in the chain — the business-level change your marketing ultimately drives. Revenue growth. Market share. Profitability. These are the goal metrics your CEO cares about.
Impact is almost always a lagging indicator. It reflects the cumulative effect of everything upstream. You cannot directly optimise for impact any more than you can directly optimise for revenue. But you can build a logic model that connects your daily activities to impact through a clear, measurable chain.
Altitude matters: zooming in and out
The logic model works at different altitudes:
10,000 feet — the strategic view. What is the impact we are trying to create? What outcomes would signal we are on track? This is where your growth marketing strategy lives.
1,000 feet — the operational view. What activities and outputs are driving our outcomes? Are our driver metrics moving? Are we investing our inputs in the right places?
100 feet — the tactical view. What did we ship this week? What experiments are running? What is the team working on right now?
Most teams spend all their time at 100 feet. They know what they are doing but not why. The logic model gives you a framework to zoom out, verify the chain is intact, and zoom back in with confidence that today’s work connects to tomorrow’s results.
“The most basic logic model is a picture of how you believe your program will work. It uses words and/or pictures to describe the sequence of activities thought to bring about change and how these activities are linked to the results the program is expected to achieve.”
W.K. Kellogg Foundation, Logic Model Development Guide
Building your marketing logic model
Here is a practical example for a B2B SaaS marketing team:
| Component | Example |
|---|---|
| Inputs | 3 marketers, $50K monthly budget, HubSpot, content library |
| Activities | SEO content, paid search, email nurture, webinars |
| Outputs | 12 blog posts/month, 4 campaigns, 50K emails sent |
| Outcomes | 400 MQLs, 15% MQL-to-SQL rate, 8% demo conversion |
| Impact | $200K monthly pipeline, 25% revenue growth |
Now you can diagnose problems. If pipeline is flat, you work backwards:
- Are outcomes declining? Check your conversion rates.
- Are outputs reaching the right audience? Check targeting and channel fit.
- Are activities aligned to strategy? Check your prioritisation framework.
- Are inputs sufficient? Check budget, headcount, and tools.
This turns vague “marketing isn’t working” conversations into specific, answerable questions.
Where teams go wrong
Skipping from inputs to impact. This is the most common failure I see. Teams invest budget and expect revenue without mapping the chain in between. When results disappoint, they have no idea where it broke.
Measuring outputs and calling them outcomes. “We published 40 blog posts” is not a result. “Those posts generated 300 qualified leads” is. This confusion is so common it deserves its own article — and I wrote one.
Ignoring time lags. The logic model is not instantaneous. Content published today might generate leads for months. Experiments run this quarter might show outcome-level impact next quarter. Build time lags into your expectations, especially for long-term brand building.
Treating the model as linear. In reality, outcomes feed back into inputs. A successful webinar (activity) generates leads (outcome) and a recording you can repurpose (input for future activities). The best marketing teams build flywheel effects where outputs from one cycle become inputs for the next.
Making it practical
Start here:
- Write down your desired impact — the business result your marketing exists to drive.
- Identify 2-3 outcomes that would indicate you are making progress. These become your driver metrics.
- Map the outputs your team produces that should drive those outcomes.
- List the activities that produce those outputs.
- Audit your inputs — do you have the resources to sustain those activities?
Then ask the hard question at every link: “Is this connection real, or am I assuming it?”
If you cannot articulate why a specific activity leads to a specific outcome, you have found a broken link. Fix it or stop doing that activity.
The bottom line
The logic model is not new or flashy. It has been used in programme evaluation for decades. But it solves a problem that marketing teams face every day: the gap between effort and results.
The teams that get this right track the right metrics at every level of the chain and can explain exactly how today’s work connects to business impact.
Stop counting outputs. Start mapping the chain.