Fix Strategy Before Tactics: Why Better Growth Starts With ICP, Operating Model, and One AI Workflow
Many growth teams are not underperforming because they lack effort, channels, or tools. They are underperforming because they are trying to scale tactics that were never grounded in a coherent strategy.
That was the clearest message from a discussion with B2B growth leaders Kathy and Patrice of Invert: when campaigns stall, the root problem usually is not the ad platform, the email sequence, or the newest AI tool. It is a mismatch between who the company is targeting, how internal teams work together, and how the business is trying to operationalize growth.
For executives, PE operating partners, investors, and portfolio finance leaders, this distinction matters. It changes where you place bets. Instead of approving another tactical spend increase, the smarter move may be to tighten the ideal customer profile (ICP), redesign handoffs between teams, and apply AI to a single cross-functional workflow before rolling it out broadly.
This article distills the discussion into an operating perspective: what leaders should take from it, where the real leverage lies, and how to recognize whether your organization has a tactic problem or a strategy problem.
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Key Takeaways
- Start with ICP before optimizing campaigns. Better targeting often produces more value than more spend.
- Do not confuse channel metrics with campaign effectiveness. Clicks and sends matter, but pipeline progression matters more.
- Most marketing breakdowns are operating-model breakdowns. Teams often fail at handoffs, shared definitions, and coordinated execution.
- AI adoption without workflow redesign creates noise, not impact. Reimagine one end-to-end, cross-functional process first.
- Measure account engagement, not just tactic efficiency. More meaningful engagement across a buying group often correlates with higher win rates and larger deals.
- Sales, marketing, and BDRs should operate as one revenue motion. Fragmented ownership weakens execution and learning.
- Smaller firms need sharper focus, not broader reach. In competitive markets, a narrow ICP and clear differentiation beat "peanut butter spread" budgets.
- RevOps and marketing ops are strategic functions. System design and data flow speed shape buyer experience and revenue outcomes.
The Core Diagnosis: Companies Go to Tactics Too Fast
One of the strongest themes in the conversation was that many companies jump directly into execution. They buy an ABM platform, launch ads against target accounts, or roll out AI tools team by team. Then they wonder why outcomes do not scale.
That sequence is backward.
The speakers described a common pattern: organizations "go right to channels and tactics" before revisiting how work should get done. In other words, they are trying to improve output without first fixing the machine.
For leadership teams, this is an important lens. A stalled campaign is often treated as a marketing-performance issue when it may actually be one of:
- unclear target segments
- inconsistent campaign definitions across functions
- weak sales-marketing coordination
- fragmented data
- slow operational handoffs
- tool adoption without process redesign
This is why tactical interventions alone often disappoint. They optimize a layer of the business that sits downstream of the real constraints.
Why ICP Work Often Delivers the Highest Return
If there was one recommendation in the discussion that sounded almost universal, it was this: if you want better campaigns, do more work on your ICP.
That advice may sound basic, but it is frequently neglected because leadership teams assume they already know their market. In practice, many organizations operate with an ICP that is too broad, too old, too informal, or too disconnected from actual revenue outcomes.
Why ICP matters more than most teams admit
A strong ICP does several things at once:
- concentrates spend on the most promising accounts
- clarifies messaging and value propositions
- improves alignment between marketing, BDRs, and sales
- sharpens prioritization across content, channels, and offers
- reduces waste from broad, low-conversion campaigns
For smaller companies especially, this matters even more. If you cannot outspend larger competitors, you have to out-focus them. The conversation emphasized that in competitive markets, trying to match larger players across paid channels is often a losing strategy. Precision beats scale when resources are constrained.
A practical leadership interpretation
For operators and investors, ICP quality is not a "marketing detail." It is a strategic asset.
A weak ICP leads to:
- diluted pipeline generation
- lower sales productivity
- confused positioning
- poor conversion analytics
- internal conflict about where resources should go
A refined ICP, by contrast, gives the organization a common decision framework. It tells teams where to spend time, where not to spend time, and what "good demand" looks like.
That has implications beyond marketing. It affects pricing, sales capacity planning, territory design, hiring, and M&A integration priorities.
The Hidden Reason Campaigns Fail: The Implementation Layer
A useful point from the discussion was that marketing often fails at the implementation layer.
That is worth underscoring because many executive conversations stay too abstract. Leadership approves a strategy, signs off on budgets, and expects execution to follow. But once organizations grow, the work becomes fragmented. Informal coordination stops working.
What used to happen around one table now depends on:
- role clarity
- documented workflows
- service-level expectations
- clean data movement
- shared definitions
- escalation paths
- system interoperability
Without those, campaigns can exist "in market" while still being structurally weak.
Signs your implementation layer is broken
The video pointed to several symptoms, which can be translated into leadership diagnostics:
1. Teams use the same words differently
If product marketing, field marketing, social, and Salesforce admin teams all define "campaign" differently, reporting and orchestration will break down.
2. Functions barely know each other
In some organizations, cross-functional teams are so siloed they have little practical connection. That is not just a cultural problem; it is an execution risk.
3. Budget incentives create infighting
When each specialist function is measured primarily by its own activity or budget protection, collaboration suffers. Teams optimize for proving value within their silo instead of moving accounts through pipeline.
4. Handoffs are too slow
A lead or engagement signal may technically move through the stack, but if action takes 24 hours instead of 30 minutes, buyer experience suffers.
5. AI usage is widespread but incoherent
If individual contributors are using AI in isolated ways, but leaders cannot point to business impact, the organization has experimentation but not transformation.
AI: Don’t Automate Random Tasks. Redesign One Workflow
The AI guidance in the conversation was notably disciplined. Instead of urging companies to deploy AI everywhere, Kathy recommended a narrower move: reimagine one workflow from start to finish, especially one that crosses functions.
That is excellent advice because most AI programs fail from overbreadth, not under-ambition. Companies spread pilots across too many teams, celebrate usage, and struggle to quantify impact.
Why one workflow is the right unit of change
A workflow is where strategy, process, people, systems, and accountability meet. If AI improves only one isolated task, the broader process may remain just as slow or broken as before.
For example, AI may help create:
- better account research
- faster email drafts
- quicker content summaries
- richer signal aggregation
But unless the surrounding workflow changes, those improvements may not alter response times, buyer engagement, or conversion rates.
A cross-functional workflow redesign forces harder questions:
- Where should human judgment sit?
- What information should move automatically?
- Which approvals add value versus delay?
- What should marketing own versus sales or BDRs?
- Where are signals being lost?
- Which metrics indicate workflow success?
A portfolio-company lens
For PE-backed businesses, this matters because AI investments are often pursued under pressure to deliver fast efficiency gains. The temptation is to automate labor before stabilizing process. But the discussion suggests a better sequence:
- Identify a workflow that materially affects growth.
- Map the current-state process across functions.
- Redesign decisions, handoffs, and data flow.
- Apply AI where it improves speed, consistency, or insight.
- Measure business impact, not just usage.
That is a much more investable approach than broad AI experimentation with fuzzy ownership.
Stop Mistaking Activity Metrics for Business Outcomes
Another strong point in the discussion was the distinction between tactical metrics and campaign effectiveness.
Marketing technology generates enormous volumes of data. Teams can report on clicks, sends, opens, keyword rankings, attendance, and conversion events. But those metrics do not necessarily answer the executive question: Is this campaign helping accounts move toward revenue?
The hierarchy leaders should use
A useful way to interpret the conversation is as a measurement hierarchy:
Level 1: Channel efficiency
Examples:
- cost per click
- email open rate
- event attendance
- media reach
These matter, but they are local metrics.
Level 2: Campaign effectiveness
Examples:
- whether target accounts are progressing
- whether buying groups are expanding
- whether engagement is sustained
- whether priority messages are landing
This is more strategic.
Level 3: Revenue contribution
Examples:
- pipeline creation
- deal velocity
- win rate
- average deal value
- bookings
This is where executives should focus.
The discussion argued that organizations often get trapped at Level 1 because specialist teams are built around tactics. That encourages optimization within silos rather than accountability for revenue movement.
A more useful executive dashboard
One particularly practical idea from the conversation was to examine opportunities or bookings alongside total marketing engagement from the account over time. Not as a perfect proof of causation, but as a directional indicator.
The logic is simple: more meaningful engagement across an account often correlates with:
- higher win rates
- larger deal sizes
- better velocity
That is not a final attribution model, but it is highly actionable. It can serve as an early-warning system.
If an account has too little engagement, the next move becomes clearer:
- increase relevant touches
- engage more stakeholders
- vary message themes
- align sales and marketing outreach
For leaders, this is far more useful than reviewing disconnected tactic reports.
The Buying Group Matters More Than the Lead
One subtle but important shift in the discussion was away from single-contact thinking and toward buying-group engagement.
This is especially relevant in B2B, where one champion rarely closes a deal alone. If there is only one engaged contact in the database, the opportunity is structurally weaker than one with multiple active stakeholders.
What this means operationally
A mature growth motion should ask:
- How many contacts are engaged in target accounts?
- Which personas are represented?
- Which message themes are resonating?
- Are we seeing breadth of engagement or just depth with one person?
This matters because pipeline quality is not just about account count. It is also about stakeholder penetration.
For CFOs and CROs, that has forecasting implications. Opportunities with broader engagement may deserve different confidence weighting than those dependent on a lone contact.
Why Smaller Companies Need Focus More Than Brand Spend
The discussion also touched on an issue many lower-middle-market firms face: how much to invest in brand visibility versus direct demand generation.
The answer offered was pragmatic. For smaller companies, especially those in competitive spaces, broad brand spending may be less efficient than investing in organic discoverability and a tightly defined ICP.
The speakers referenced SEO and AEO as current focus areas, reflecting the need to win where larger media budgets are less dominant. While the video did not go deep into execution specifics, the larger point stands: smaller firms need to prioritize channels where differentiation and relevance matter more than brute-force spend.
The strategic implication
When resources are limited, brand building cannot be detached from target selection. Focused reputation compounds. Generic awareness burns cash.
The better question is not, "How do we build more visibility?" It is, "How do we become highly visible to the right accounts, in the right contexts, with the right message?"
That framing links brand, demand, and sales more effectively.
The BDR Role Is Being Redefined, Not Eliminated
One of the more interesting parts of the conversation involved BDR teams and AI. The speakers noted that some executives are aggressively questioning the role, sometimes reducing headcount sharply, only to hire back later.
That pattern should not surprise operators. New technology often prompts overcorrection.
What AI changes in BDR work
AI can certainly assist with:
- account research
- summarizing firmographic and behavioral signals
- drafting outreach
- prioritizing next actions
- surfacing buyer context
But that does not settle the question of where judgment belongs.
The discussion suggested companies are split:
- some want BDRs to own more intelligence-supported judgment
- others want subject matter experts or centralized teams to prepare intelligence for BDRs
What seems clear is that the old model of high-volume, low-context outreach is under pressure. The future role is likely more integrated with marketing and more informed by account-level intelligence.
Leadership takeaway
The question is not "Should we replace BDRs with AI?"
The better question is: What parts of the BDR workflow should be automated, and what parts require human interpretation, coordination, and learning?
That distinction matters because BDRs are often a rich source of market feedback. They can reveal:
- whether messaging is landing
- how buyers describe their pain points
- which objections are emerging
- how prospects discovered the company
If that loop disappears, the organization may save labor while losing insight.
Enterprise Complexity Is Not Just Bigger Scale. It’s Different Complexity
The speakers drew a clear contrast between smaller businesses and large enterprises. In large organizations, growth problems are rarely tidy. They span geographies, product lines, systems, departments, and stakeholder agendas.
That is useful framing for executives who move between company sizes. Enterprise growth issues are not merely "more of the same." They require different problem-solving methods.
Common features of enterprise growth complexity
According to the discussion, enterprise challenges often involve:
- multinational operating environments
- multiple business units
- many product lines
- fragmented data
- layered stakeholder management
- change management across functions
- unclear problem definition at the outset
In those cases, the first task is often not to solve the problem directly, but to break the problem down into manageable pieces and define an approach.
That is why large-scale go-to-market transformation typically combines:
- strategy
- business process redesign
- change management
- systems thinking
- data architecture
- operational governance
For operators and investors, this reinforces a key point: transformation work often looks slower at the front end because real complexity must be clarified before tools can help.
Why RevOps and Marketing Ops Are Strategic, Not Administrative
One of the strongest subtexts in the conversation was the importance of operations leadership. The discussion highlighted that two companies can have the same tech stack and perform very differently.
That is because software does not create capability on its own. The operating design around the software determines speed, reliability, and user trust.
What operations quality shapes
Operations teams influence:
- signal capture
- routing speed
- campaign consistency
- reporting integrity
- handoff quality
- SLA adherence
- buyer response times
- account visibility across teams
This is why experienced RevOps and marketing ops leaders are often competitive differentiators. They convert tools into functioning systems.
For executives, that means ops roles should not be treated as back-office support. They are part of the revenue engine.
The Pace Problem: Why This Matters More Now
A brief but meaningful note in the discussion was about pace. The market is moving faster, and teams are feeling it. Inventory shifts faster. Buyer behavior changes faster. AI capabilities evolve faster. Expectations move faster.
That acceleration makes weak operating models more costly.
In slower environments, teams can compensate for poor process through heroic effort. In faster environments, they cannot. Delays, misalignment, and unclear ownership compound quickly.
This is why the conversation’s advice feels timely:
- get sharper on ICP
- improve cross-functional coordination
- rethink one workflow with AI
- focus on account progression, not just activity
These are not just marketing recommendations. They are responses to compressed decision cycles and rising organizational complexity.
A Practical Framework for Leaders
If you want to turn the discussion into action, here is a simple way to apply it.
1. Audit your ICP
Ask:
- Is our ICP explicitly defined?
- Has it been updated based on actual conversion and retention data?
- Do sales, marketing, and BDRs use the same definition?
- Are we spreading budget too broadly?
2. Map one revenue workflow
Choose one cross-functional process, such as:
- target account activation
- inbound lead qualification
- opportunity acceleration
- post-event follow-up
Then map:
- current steps
- owners
- delays
- missing data
- duplicate effort
- points where AI could help
3. Separate efficiency metrics from outcome metrics
Review dashboards and ask:
- Which metrics measure team activity?
- Which metrics show account progression?
- Which metrics correlate with win rate, deal size, or velocity?
4. Evaluate buying-group coverage
For open opportunities, assess:
- how many contacts are engaged
- which personas are active
- where stakeholder gaps exist
- whether engagement is broad enough to support deal confidence
5. Test one AI-enabled operating change
Do not launch a broad AI transformation. Start with one workflow and define success in business terms:
- faster response times
- better account prioritization
- more stakeholder engagement
- improved conversion or velocity
Conclusion
The most valuable idea in this conversation is also the simplest: better growth usually comes from fixing the foundations before adding more tactics.
If campaigns are underperforming, the first question should not be which platform to buy or which channel to tweak. It should be whether the organization has clarity on its ICP, alignment across teams, and a workable operating model for turning market signals into coordinated action.
That is especially relevant now, when AI is making it easier to generate more activity without necessarily improving outcomes.
The companies that benefit most will be the ones that resist the temptation to optimize fragments. They will sharpen who they serve, unify how teams execute, and apply AI where it transforms a workflow rather than merely speeding up isolated tasks.
In a market defined by speed and complexity, strategy is no longer the slow part. It is the only way tactics scale.
Source: "Fix Strategy Before Tactics and Scale B2B Growth with Kathy Macchi and Patrice Greene" - Code Conspirators, YouTube, Jul 14, 2026 - https://www.youtube.com/watch?v=W9LavSjDPQM
