The Most Overrated Marketing Metrics

 Marketers leaders say click-through rate (CTR) is the most overrated metric for measuring success, according to recent research from Keen.

The report was based on data from a survey of 120 senior brand and agency marketers.

A quarter of respondents say CTR is the most overrated metric and 23% say ROAS is the most overrated metric.

Some 37% of senior marketers say if they had to pick just one metric to report to their board, they'd choose total revenue.

Some 40% of senior marketers say their biggest current measurement blindspot is a lack of real-time insights for inflight optimization.

Senior marketers say the top barrier to advanced measurement is high cost/resource constraints.

About the research: The report was based on data from a survey of 120 senior brand and agency marketers.

https://tinyurl.com/295udw34

Why People Use Generative AI Tools in 2026

 Which types of tasks are Americans using generative AI tools for? How does AI use vary by age and income?

To find out, EMARKETER conducted a survey in May 2026 among 1,570 consumers in the United States aged 15-80 who use generative AI tools.

Among respondents who use generative AI tools at least weekly, some 51% say they use them for "asking" (to look for information), 34% for "doing" (for help with personal tasks), 30% for "playing" (for fun), and 26% for "working" (for work or school tasks).

Gen Z and millennial respondents are more likely to use AI at least weekly compared with older generations, and are also more likely to use AI to meet a wider range of different needs.

Higher income respondents (household income over $200,000) are twice as likely to use AI tools for working compared with lower income respondents (household income under $49,999).

About the research: The report was based on data from a survey conducted in May 2026 among 1,570 consumers in the United States aged 15-80.

https://tinyurl.com/yc628e34

Project planning basics

 

https://tinyurl.com/e2epkejd

How to develop your project plan

 

A project plan is more than a schedule. It is the roadmap that connects business objectives with execution and business value.

A strong Project Plan should cover 12 essential steps:

1️⃣ Understand the Business Need — Why does the project exist, and what value should it deliver?

2️⃣ Define Objectives & Success Criteria — Make success clear and measurable.

3️⃣ Define the Scope — Clarify what is included, excluded, and expected as deliverables.

4️⃣ Build the WBS — Break deliverables into manageable work packages.

5️⃣ Develop the Schedule — Activities, sequence, durations, milestones, resources, and critical path.

6️⃣ Estimate Resources & Cost — Integrate people, materials, equipment, subcontractors, time, and budget.

7️⃣ Plan Procurement — Determine what must be purchased or outsourced and when.

8️⃣ Identify Risks & Opportunities — Define probability, impact, response, and ownership.

9️⃣ Define Quality & HSE Requirements — Establish the standards for safe and compliant delivery.

🔟 Plan Stakeholder & Communication Management — Define who needs what information, when, and how.

1️⃣1️⃣ Establish Governance & Controls — KPIs, reporting, approvals, change control, escalation, and decision rights.

1️⃣2️⃣ Integrate & Baseline the Plan — Connect Scope + Schedule + Cost + Resources + Risk + Procurement + Quality + Governance into one integrated baseline.

The key point?

A Schedule is part of the Project Plan — not the Project Plan itself.

And a good plan should never become a document sitting on a shelf.

It should remain a Living Plan:

PLAN → EXECUTE → MONITOR → ADAPT → SUCCEED

Because good project planning is not about predicting the future.

It is about preparing the project to manage it.

https://tinyurl.com/mt4kt8s5

How to Write a Project Plan

 

A well-structured project plan is the foundation of project success. Without proper planning, teams often face scope creep, budget overruns, missed deadlines, and communication gaps. A strong project plan provides clarity, direction, and alignment for everyone involved.

Key Steps to Create an Effective Project Plan

✅ Define the Business Case & Objectives

Clearly identify the project purpose.

Establish measurable goals and success criteria.


✅ Identify Stakeholders

Determine who is impacted by the project.

Understand expectations and communication needs.


✅ Define Scope

Document what is included and excluded.

Prevent scope creep through clear boundaries.


✅ Develop the Schedule

Break work into tasks and milestones.

Create realistic timelines and dependencies.


✅ Plan Resources

Allocate people, tools, and budget.

Ensure resource availability throughout the project lifecycle.


✅ Assess Risks

Identify potential challenges.

Develop mitigation and contingency plans.


✅ Create a Communication Plan

Define reporting frequency and channels.

Keep stakeholders informed and engaged.


✅ Establish Quality Standards

Set performance and acceptance criteria.

Monitor deliverables to ensure compliance.


✅ Obtain Approval

Review the plan with key stakeholders.

Secure baseline approval before execution.


Common Project Planning Mistakes

❌ Unclear project scope
❌ Poor stakeholder engagement
❌ Unrealistic schedules
❌ Inadequate risk management
❌ Lack of resource planning
❌ Weak communication processes

Why Project Planning Matters

Organizations that invest time in planning achieve better cost control, improved schedule performance, reduced risks, and higher-quality outcomes. Effective planning transforms ideas into actionable roadmaps and increases the likelihood of project success.

Remember: A project plan is not just a document—it's a strategic guide that helps teams execute with confidence, stay aligned with objectives, and deliver value successfully.


Writing a Strong Project Plan Changes Everything Great results rarely happen by accident. 

Studies show nearly 70% of initiatives struggle due to weak planning, not execution. When direction is clear, teams move faster, costs stay controlled, and confidence grows across stakeholders. The difference between chaos and control usually starts with how well the plan is written. 

🎯 Start With Outcome Thinking Before writing tasks, define the final picture. Research shows teams with outcome-defined planning achieve 2.5x higher success rates. Write what success looks like in measurable terms. Not “improve performance,” but “reduce processing time by 20%.” Precision removes confusion and builds trust instantly. 

🧠 Write For Humans, Not Documents Most plans fail because they are written like legal files. People follow simple, visual, and structured thinking. Use short sections, clear flows, and logical sequencing. Organizations using simplified planning structures report 35% faster decision cycles. 

📊 Turn Assumptions Into Visible Risks Hidden risks destroy timelines. High-performing teams document assumptions openly. Data shows projects with assumption tracking reduce rework by up to 30%. Write assumptions beside each major deliverable. If something changes, impact becomes visible immediately. ⏱ Plan Backward From Deadlines Instead of building forward, start from the final delivery date and move backward. This method improves schedule reliability by nearly 28% in large transformation initiatives. Reverse planning exposes hidden dependencies early. 

🔗 Connect Tasks To Business Value Every task must answer one question: Why does this exist? Plans aligned with business outcomes show 40% higher stakeholder approval rates. When value is clear, funding, support, and momentum increase automatically. 

📁 Document Decisions, Not Just Activities Execution teams struggle when decisions are not captured. Writing decision logic improves transition from planning to execution by 50%. Always capture why choices were made, not only what was chosen. 

🤖 Blend Data, Experience, And Pattern Recognition Modern planning mixes historical data, predictive insights, and human judgment. Organizations using data-supported planning improve forecast accuracy by 35% and reduce budget overruns significantly. 

🚀 The Real Secret Strong planning is not about documents. It is about thinking discipline. Clear thinking creates clear execution. Clear execution creates predictable results.

https://lnkd.in/p/dQCJtGDy

https://tinyurl.com/nja7t4sj

Value creation mechanisms of business models. Proposition, targeting, appropriation, and delivery.

 

How to Actually Build an AI Agent

 

Most AI agents fail before the first API call.

Because most teams start with prompts.
Production agents do not start there.
They start with a system.
A small one, but still a system.

The first decision is the goal.
What should the agent actually improve?
What does success look like?
What latency, cost, safety, and compliance limits matter?
No clear goal usually means a demo that cannot survive real work.

Then choose the model for the job.
Large reasoning models are useful for planning and complex decisions.
Large language models are strong general-purpose workers.
Small language models can be faster and cheaper for routing,
classification, extraction, and edge execution.
The model choice affects cost, speed, reliability, and user trust.

The framework comes after the job is understood.
Simple workflows may only need n8n, Gumloop, LangFlow,
or a lightweight agent setup.
More serious products may need LangChain, CrewAI,
LlamaIndex, Google ADK, or the OpenAI Agent SDK.
Start simple.
Scale only when complexity proves it deserves more structure.

The agent becomes real when tools are connected.
APIs.
MCP.
REST and GraphQL.
Function calling.
Structured outputs.
File systems and vector databases.
Without tools, the agent can talk.
With tools, it can act.

Memory is the next layer.
Short-term memory keeps the current task coherent.
Episodic memory tracks session history and events.
Long-term memory connects the agent to documents,
preferences, knowledge bases, and RAG systems.
This is where agents stop feeling stateless.

Then comes testing.
Accuracy matters.
Latency matters.
Cost matters.
Coverage matters.
Edge cases matter more than the happy path.
Red-team the weak points before users find them for you.

Deployment is not the finish line.
Monitor usage, errors, latency, and cost.
Add guardrails, rate limits, and fallbacks.
Improve the system from real feedback.

The best agents are not just smarter models.
They are better engineered workflows.
Clear goal.
Right model.
Useful tools.
Managed memory.
Continuous evaluation.

That is the difference between an impressive demo
and an agent people can trust in production.

https://lnkd.in/p/d5mf_3Fn