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If you’ve been in a growth review lately, you’ve probably felt the tension. Spending is up. Demand is still there. But every individual channel looks worse than it did two years ago. Meta CPMs keep climbing. Google feels less predictable by the quarter. SEO traffic flattens even when rankings hold. Leadership asks the same question in different ways: “Why doesn’t any single lever work like it used to?”
Here’s the thing. That question assumes performance still lives inside channels. It doesn’t.
Hawke Media’s 2026 Market Vision Report makes this painfully clear. After analyzing 17.9 billion impressions, 321 million clicks, and $313 million in ad spend, their conclusion isn’t that algorithms stopped working or that demand dried up. It’s that performance has shifted upstream. Creative velocity, funnel design, and cross-channel orchestration now drive growth. Brands that still operate channel by channel are falling behind. Brands that treat acquisition as a unified system are pulling away.
We’re seeing the same pattern across Relevance client accounts. Not because we read it in a report, but because we’ve lived through the consequences of ignoring it.
Channel-first thinking breaks under modern cost structures.
Channel-first marketing made sense when platforms rewarded specialization. If you cracked Facebook targeting in 2018, you could scale for months. If you ranked page one in Google, traffic compounded predictably. That era trained teams to think in silos: paid search team here, paid social team there, content over in another corner.
Fast forward to 2026, and those silos are liabilities.
Costs are structurally rising. Not temporarily. Structurally. More advertisers. Fewer signals. More competition for the same attention. When CPMs rise 20 to 40 percent year over year, you don’t optimize your way out with marginal bid tweaks. And when attribution keeps fragmenting, channel-level ROAS starts lying to you.
We’ve watched teams kill profitable growth engines because one channel’s dashboard “looked bad” in isolation. Meanwhile, total acquisition efficiency quietly improved when everything worked together. Channel-first optimization obscures that reality.
Unified performance systems explain what’s actually happening.
A unified performance system treats marketing like a coordinated acquisition engine, not a collection of tactics. Creative isn’t “for Meta” or “for TikTok.” Messaging isn’t owned by one channel. The funnel isn’t rebuilt five times by five teams. Everything ladders to a shared model of how demand is created, captured, and converted.
When Hawke talks about creative velocity, they’re not talking about pumping out more ads for the sake of it. They’re pointing to a system where creative insights move fast across channels. A hook that works in paid social informs landing page headlines. High-intent search queries shape video scripts. Email and retargeting reinforce the same narrative rather than introducing new friction.
Which means each channel makes the others more efficient.
We’ve seen this play out with B2B SaaS clients where paid social “lost” efficiency on paper. CAC looked worse month over month. But demo-to-close rates increased because prospects arrived more educated. SEO content aligned with paid messaging shortened sales cycles. Net CAC dropped even though no single channel looked heroic.
That only shows up when you stop judging channels independently.
AI didn’t kill performance. It exposed bad systems.
AI gets blamed for everything right now. Rising costs. Creative fatigue. Declining click-through rates. In reality, AI accelerated what was already breaking.
Automation flattened advantages. Targeting parity is real. Everyone has access to similar bidding strategies, lookalikes, and optimization tools. When inputs converge, differentiation moves elsewhere.
That “elsewhere” is system design.
Teams still trying to win with isolated channel hacks struggle because AI neutralizes those edges quickly. Teams investing in unified performance systems win because AI amplifies coordination. Faster creative testing feeds smarter insights. Better insights inform tighter funnels. Tighter funnels make rising costs survivable.
AI rewards teams that know what question they’re asking. Channel-first teams ask the wrong ones.
Creative velocity beats creative perfection.
One of the biggest shifts we’ve seen since late 2024 is how creative strategy operates. The best teams aren’t chasing perfect concepts. They’re building feedback loops.
Creative velocity means shipping, learning, and iterating across the entire system. Not just ads. Landing pages, email sequences, sales decks, and even how offers are framed in outbound. The same core message gets pressure-tested everywhere.
When one angle breaks through, it scales horizontally. Not vertically inside one channel.
That’s why Hawke’s data matters. When performance is driven by creative velocity and orchestration, the old question of “Which channel should we invest in?” becomes less useful. The better question is “How quickly can we turn insight into system-wide execution?”
GEO forces unification whether you like it or not.
Generative engine optimization is quietly forcing this shift. LLMs don’t care which channel “owns” the message. They synthesize across sources. Brands showing up consistently in AI answers tend to have unified narratives, not fragmented ones.
We’ve seen companies dominate ChatGPT and Perplexity results without ranking first in Google for every keyword. Why? Because their content, PR mentions, paid visibility, and brand language reinforce each other. That doesn’t happen accidentally. It happens when teams operate from a shared performance system.
Channel-first teams struggle here because their outputs don’t cohere. Unified teams compound visibility.
What actually changes in practice?
Moving away from channel-first doesn’t mean abandoning channels. It means reorganizing how decisions get made.
High-performing teams in 2026 tend to do a few things differently:

They plan creative strategies centrally, then deploy everywhere.
They evaluate performance at the funnel and cohort level, not just ROAS.
They prioritize speed of learning over channel-level optimization theater.
They align incentives so teams win together or lose together.

None of this requires a massive budget. It requires discipline. And, frankly, uncomfortable conversations about how success is measured.
Why this matters for resource-constrained teams
If you’re running lean, this shift is actually good news. Unified systems reduce waste. You stop duplicating creative work. You stop fighting over budget ownership. You stop killing experiments prematurely because one dashboard looks ugly.
We’ve helped small teams outperform better-funded competitors simply by tightening orchestration. Same spending. Fewer assets. Better coordination. The results show up in blended CAC, retention quality, and pipeline velocity, not vanity metrics.
That’s the uncomfortable truth channel-first thinking avoids.
The real takeaway for 2026
Marketing economics have changed. Not because consumers disappeared or platforms broke, but because growth now emerges from systems, not silos. Hawke’s data confirms what many practitioners already feel in their gut. Unified performance systems outperform channel-first approaches because they reflect how buyers actually move.
The brands winning in 2026 won’t ask which channel to scale next. They’ll ask whether their system can absorb higher costs without collapsing. That’s a harder question. It’s also the right one.
The post Marketing in 2026: Why Unified Performance Systems Outperform appeared first on ReadWrite.

As remote work continues to redefine how tech teams operate, distributed engineering teams face unique cybersecurity challenges. Protecting sensitive code, proprietary algorithms, and customer data requires more than standard password protection — it demands a comprehensive strategy that spans identity management, zero-trust frameworks, and encrypted communications. This article explores practical cybersecurity essentials for distributed tech teams and highlights how structured company formation can further support compliance and operational security.
The Rise of Distributed Tech Teams
The COVID-19 pandemic accelerated a trend that was already underway: technology teams working remotely across multiple geographies. Cloud-based collaboration platforms, virtual private networks (VPNs), and project management tools have made it easier than ever to coordinate work from anywhere. While these tools enable flexibility, they also expand the attack surface for cybercriminals.
Distributed teams face challenges such as inconsistent security policies across locations, varying levels of hardware security, and reliance on personal networks. In this environment, even minor lapses in security can lead to major breaches. That’s why implementing robust cybersecurity measures is no longer optional — it is essential.
Implementing a Zero-Trust Framework
At the core of modern cybersecurity for distributed teams is the zero-trust model. Unlike traditional security, which assumes devices inside a corporate network are trustworthy, zero-trust assumes no device or user should be automatically trusted. Verification must occur continuously.
Key practices include:

Micro-segmentation: Dividing the network into smaller zones to limit the lateral movement of attackers.
Least-privilege access: Giving team members only the permissions necessary to perform their roles.
Continuous authentication: Regularly validating user identity and device integrity using multi-factor authentication (MFA).

Zero-trust strategies not only protect sensitive codebases but also ensure that even if a single device is compromised, the attacker cannot access the entire system.
Identity and Access Management (IAM) for Remote Teams
Identity management is critical for distributed teams. With employees and contractors spread across multiple locations, ensuring the right people have access to the right resources becomes a logistical challenge. IAM systems streamline user provisioning, access control, and auditing. Key components include:

Single Sign-On (SSO): Reduces password fatigue and simplifies access to multiple services.
Role-based access control (RBAC): Defines access policies based on team member roles to maintain security without hindering productivity.
Audit trails: Tracks user activity for compliance and internal monitoring purposes.

By implementing robust IAM, distributed teams can prevent unauthorized access and maintain clear accountability.
Encrypted Communication
Even with zero-trust and IAM in place, unsecured communications can still leave teams vulnerable. Remote tech teams often rely on instant messaging, email, and video conferencing tools, which can be intercepted if not properly secured. Essential encryption practices include:

End-to-end encryption (E2EE) for messaging platforms.
TLS/SSL for data transmitted over web applications.
Encrypted cloud storage for project files and code repositories.

Encrypting communication ensures that sensitive technical information remains confidential, even if a network is compromised.
Compliance and the Role of Company Formation
Beyond technical measures, structured company formation plays a critical role in operational security. Properly registered companies have the legal framework to implement corporate cybersecurity policies effectively, define accountability, and meet regulatory requirements.
For distributed tech teams, taking guidance from company formation services like Your Company Formations ensures that the organization has:

Clearly defined legal responsibilities for data protection.
The ability to implement company-wide security policies and contractual compliance with clients.
Access to business banking, corporate accounts, and official documentation that supports secure operations.

Integrating company formation into the cybersecurity strategy reinforces accountability and operational discipline across all team members, no matter their location.
Cloud Security and Collaboration Tools
Distributed tech teams heavily rely on cloud platforms for development, testing, and deployment. Securing cloud infrastructure involves:

Configuring access permissions carefully.
Enforcing MFA for all cloud accounts.
Regularly auditing cloud activity logs.
Encrypting stored data at rest and in transit.

Collaboration platforms should also have integrated security features. Tools like GitHub, Jira, and Slack offer enterprise-level security controls that teams should configure correctly to prevent breaches.
Incident Response Planning
No security strategy is complete without a well-defined incident response plan. Distributed teams must know how to react if a breach occurs:

Identify the compromised systems and isolate them.
Notify stakeholders promptly.
Perform forensic analysis to determine the breach’s scope.
Remediate vulnerabilities and update security protocols to prevent recurrence.

Regularly testing incident response plans ensures that all team members can act quickly and efficiently under pressure.
The Future of Cybersecurity for Distributed Teams
As technology evolves, so too will the threats facing distributed teams. Emerging trends include AI-driven attacks, sophisticated phishing schemes, and attacks targeting cloud infrastructure. Continuous investment in cybersecurity tools, staff training, and organizational governance will remain crucial.
Structured company formation continues to support this by enabling organizations to implement company-wide policies, meet regulatory obligations, and provide clear lines of accountability. By combining advanced technical measures with solid business foundations, distributed teams can operate securely and efficiently in a global environment.
Conclusion
Distributed tech teams face unique cybersecurity challenges, but these can be effectively managed with a combination of zero-trust frameworks, identity management, encryption, and endpoint security. Security culture, incident response planning, and cloud infrastructure management further strengthen resilience.
Alongside technical measures, formal company formation is an often-overlooked part of cybersecurity. Ensuring that your business is properly structured provides the framework to enforce security policies, comply with regulations, and protect assets across distributed teams. For remote engineering teams, integrating operational discipline through structured company formation is as critical as deploying the latest cybersecurity tools.
Photo by Rohan; Unsplash
The post Cybersecurity Essentials for Distributed Tech Teams: Zero-Trust, Identity Management, and Beyond appeared first on ReadWrite.

The story that’s often told about AI in business is how it’s a big boss decision, or part of a massive tech rollout. But a comprehensive study by Recon Analytics, with support from analysts Roger Entner and Joe Salesky, suggests otherwise. Their study, drawing from over 100,000 respondents, shows the truth is much simpler: The AI adoption shift is being driven by the people who actually use it every day.
An Employee-Led Surge
This dynamic shift shows that about 61 percent of workers say their peers, not a company mandate, influenced them to adopt AI. This represents the largest bottom-up technology shift since the advent of mobile. And this finding is important because it shifts the conversation: AI isn’t just a mandatory corporate tool. It’s helping individuals work smarter, not harder.
Recon Analytics found that 40.8 percent of knowledge workers now use AI tools at work, routinely rating their productivity gains between 7 and 8 out of 10 for tasks like writing, brainstorming, and analysis. When you look at the entire workforce, this translates to $420 billion in new value annually, with the data showing that AI is an economic advantage, not just a promise.
Tackling the Downsides
But despite these gains, the AI market is still split. Seventy-nine percent of users tend to stick with free versions, while only 21 percent pay for subscriptions. This gap matters because paying users see a 13 percent jump in productivity and can automate more complex tasks, but some have trouble justifying the upgrade, with the feeling that the free tool is “good enough.”
Add to that that the world of AI tools continues to be unstable. Unlike older software, it’s easy to switch AI platforms, which can lead to high turnover, including a surprising 28.8 percent among people who pay for the service. Market share shifts weekly as platforms gain and lose users at high rates. For many workers, the choice comes down to more practical things, such as speed, simplicity, and privacy. That can make it tough for any one platform to rule the space for long.
The Future is Now
But one feature consistently predicts a tool’s success: speed. Workers say fast performance is the most valuable trait, and this preference can deeply drive adoption. Speed, it’s understood, is the best indicator of why users switch, why they decide to pay for an upgrade, and which platform they choose.
So, in the greater scheme of things, the highest productivity scores are linked to tools that don’t stand alone. When AI is woven into a company’s internal data systems, productivity jumps to 9+, far exceeding the 8.1 seen with basic, separate tools. This points to the future: AI needs to be integrated directly into existing company data systems to gain greater relevance.
The New Standard for AI Intelligence
Tracking these behavior patterns, from how people use the tools to why they switch and what is really helping them, Recon Analytics’ AI Pulse service provides companies with real-time intelligence that traditional research can’t match. Where conventional studies take months, Recon delivers actionable insights in one week, helping businesses anticipate market shifts rather than react to them. With data from over 6,000 respondents per week, they’ve become the source of truth for understanding how workers actually use AI and where the market is headed next.
Photo by Steve Johnson; Unsplash
The post AI Adoption Isn’t Driven by Executives, But by Workers: What 100K Users Reveal appeared first on ReadWrite.