Marketing Technology Trends for 2026

By David Ronald 

The marketing technology landscape is undergoing one of the most transformative periods in its history.

What was once the domain of isolated automation tools and basic analytics has evolved into fully adaptive, AI-driven systems that reshape how brands engage audiences, personalize experiences, and make strategic decisions.  

From hyper-personalization to autonomous AI agents, I’m expecting that 2026 will set the pace for the next era of marketing innovation. 

In this blog post I examine six martech trends that I predict will be big in 2026.  

  

1. AI Moves from Assistive to Strategic

Artificial intelligence continues to dominate Martech discussions, of course, but its role in 2026 will be fundamentally different than just two years earlier.

During 2024 and 2025, many teams adopted AI mainly for efficiency, drafting social posts, generating creative variations, or automating repetitive tasks.

By 2026, AI transitions into a core operational infrastructure, with brands using custom-trained models across strategy, personalization, and workflow orchestration.

This means AI won’t just help marketers; it will power marketing decision systems, turning real-time data into actionable, context-aware customer experiences. 

2. Hyper-Personalization at Scale

I’ve posted about this a few months ago, and my thinking expectations in area haven’t changed – hyper-personalization becomes more than a buzzword next year, it becomes essential.

Through machine learning and real-time behavior analysis, brands can tailor messaging, visuals, and offers for individual users across every touchpoint.

Dynamic content systems will adjust not just based on past behavior but predicted intent and context, such as time of day, device used, and inferred needs, creating nearly invisible personalization that feels intuitive and seamless. 

3. Autonomous AI Campaigns

Marketing systems that think rather than merely execute are no longer futuristic.

Autonomous AI agents, capable of planning, launching, optimizing, and even reallocating budgets, will shift campaign management into a new paradigm.

These AI agents analyze performance in real time, test creative variations, and adjust audience targeting without constant human intervention.

This evolution compresses creative and media workflows, allowing marketing teams to focus on strategy and storytelling. 

4. First-Party & Zero-Party Data as the Cornerstone

With privacy regulations tightening and third-party cookies largely deprecated, first-party and zero-party data will become critical assets.

Tools that help marketers collect, unify, and activate consented data open the door to better audience segmentation, deeper personalization, and compliance with emerging privacy standards.

Centralized Customer Data Platforms and preference centers help brands unite identity resolution and real-time activation, shifting marketing stacks toward privacy-first architectures. 

5. Immersive & Experiential Technologies

In 2026 immersive technologies will become practical everyday marketing tools. 

Augmented reality and virtual reality aren’t just for gaming or niche retail experiences anymore.

Browser-based AR, virtual try-ons, and 3D interactive ad formats enable richer storytelling and deeper emotional connections, helping brands bridge the gap between imagination and experience. 

6. No-Code & Low-Code Empowerment

Marketing teams increasingly wield no-code and low-code platforms to build landing pages, workflows, dashboards, and integrations without the need for heavy engineering support.

This democratization of technology accelerates execution, reduces bottlenecks, and shifts ownership of innovation closer to marketing practitioners. 

Conclusion

Martech will be defined not by individual tools in 2026, but by interconnected intelligent systems that anticipate needs, adapt in real time, and deliver relevance at scale.

For brands ready to invest in AI fluency, data sovereignty, and immersive experiences, the future isn’t just bright… 

It’s already here.

Thanks for reading.

Are you interested in discussing exploring which marketing technologies are best for your business. My email address is david@alphabetworks.com – I look forward to hearing from you.

Building a World-Class Partner Marketing Playbook

By David Ronald

Not so long ago I joined a fast-growing startup, with an energetic marketing team. 

And, in addition to my “day job”, I had been volunteered to lead partner marketing.  

But, in reality, partner marketing was little more than a wish list.

Every few weeks I tried something new – a webinar, a co-branded asset, and, if there was budget left over, a field event. 

But nothing connected, and this is how things went for weeks. 

Until, one day, our CRO said to me, “Partners are either a strategy or a distraction. But they can’t be both.” And this statement forced me to admit that we really didn’t have a partner program.

So, I began building one - and, over the six months, partners went from a side project to a core growth engine.

In this blog post I share how we did it, and how we developed a world-class playbook for partner marketing. 

1. It Started With Clarity

An epiphany came during a QBR when we were reviewing partner performance: 

• 29 partners listed.
• Five generating pipeline.
• Two producing real revenue.

Wow! I had been treating every partner like a priority, but the truth was that none of them were.

So, I gathered my key constituents together and asked the hard questions: 

• Which partners actually help us win?
• Which create real customer value when combined with our solution?
• Which partners do sellers actually care about?
• Which ones are aspirational, but not practical?

That meeting became the foundation of our partner segmentation model. For the first time, we had clarity on where to invest, and where to stop spreading ourselves thin.

This was the beginning of our partner marketing playbook. 

2. Recruiting the Right Partners

Before my reset, partner recruitment looked like this: “Great logo. Let’s sign them.” After my reset, recruitment looked like this: “Where is there undeniable customer value and mutual benefit?”

And one example stands out: I met with a consulting firm who had expertise in industries we struggled to break into. On paper, they weren’t the biggest partner but, when I dug deeper, I found something better: a perfect customer overlap and immediate value in co-delivering solutions.

Within three months, they sourced more opportunities than several large partners combined. And that’s when I realized that partner recruitment is about strategic fit and fast time-to-value, not quantity.  

My onboarding processes shifted too. Instead of dropping partners into a portal and wishing them luck, we built an experience: 

• A shared value proposition.
• Enablement paths.
• Playbooks they could use on Day 1.
• Quarterly success plans.

And, looking back, I believe that this was when the momentum began. 

3. Enablement Becomes the Multiplier

A turning point came while we were chasing a major opportunity.

One of our partners emailed us: “We pitched the solution ourselves. They want a demo now - can you join us for next steps?”

So, in other words, this partner had delivered the pitch, perfectly.

And that was the moment we truly understood the power of enablement.

We had provided them with: 

• Messaging frameworks.
• Industry-specific one-pagers
• Battlecards.
• Co-branded decks.
• Sales plays.

But, in my opinion, the best marketing teams don't just hand partners a bunch of content – they give partners them the confidence to sell their product. 

4. High-Impact Co-Marketing

Looking back, I’d have to say that for months we ran “partner webinars” that generated little more than vanity metrics.

But, once we rebuilt the program, we transformed co-marketing from random acts into predictable momentum.

Here’s one example: We hosted a joint webinar with a mid-market technology partner. Normally we’d just send a few emails, post on LinkedIn, and hope. This time was different: 

• We aligned on a single ICP.
• We co-developed the narrative.
• Both sales teams committed to follow-up.
• We built a shared nurture sequence.
• We held a pre-brief and post-brief with the partner’s SDR team.

What was our outcome: 

• 342 registrants.
• 11 qualified enterprise opportunities.
• 3 closed-won deals within the quarter.

We repeated that play several times, with content launches, events, marketplaces, roundtables, and partner ABM, and each time the story was the same: coordinated co-marketing creates pipeline, fast. 

5. Co-Selling Takes Off

Before we built our playbook, co-selling was sporadic at best. Sellers weren’t sure when to bring partners in, which partners made sense, or what partners could even offer.

Once we fixed that, everything changed.

We built: 

• Clear rules of engagement.
• Joint sales plays.
• Account mapping workflows.
• Deal registration guidelines.
• Co-branded sales materials.
• A repeatable co-sell process.

The breakthrough came when a partner AE called one of our reps: “I’ve already scoped the project. They’re ready to buy. Can you join the final call?” 

The partner had done 80% of the work – and that was the moment leadership shifted their view of partnerships from optional, to essential. 

6. Expanding Through Customer Success

It’s my belief that one of the best kept secrets in partner marketing is this: Your biggest wins often come after the customer signs. 

I learned this during a large-scale deployment where implementation was handled jointly by us and one of our partners. The customer experience was seamless, and when renewal time came, the customer expanded their contract through both of us.

 That’s when we built shared success programs: 

• Joint customer workshops.
• Shared QBR frameworks.
• Co-delivered implementation offerings.
• Partner-led training and onboarding.

Customers began seeing us and our partners as a unified solution, and not two separate companies. 

It was this perception alone created stronger renewals, faster expansions, and more advocacy stories than we had expected. 

7. Measuring What Matters

At first, the metrics we tracked were basic: 

• Number of partners.
• Number of meetings.
• Number of campaigns.
• None of that told us whether the program was working.

But, once we rebuilt our measurement model, I chose to focus on metrics that actually matter: 

• Partner activation rate.
• Time to first deal.
• Co-marketing sourced pipeline.
• Co-sell win rate.
• Partner attach rate.
• Retention and expansion influenced by partners.

The numbers showed that partners were no longer a side channel for the team, but a competitive advantage. 

Conclusion

By the end of that first year, our partner program didn’t look anything like the one I’d inherited.

Partners were closing deals on their own. Sellers were bringing partners into opportunities early. Co-marketing programs were producing pipeline consistently. Customer success teams were collaborating with partners by default. 

What changed everything wasn’t a new portal, new incentives, or new logos... 

It was a commitment to building a playbook that turned partnership chaos into partnership momentum.

The story we lived became the playbook companies everywhere can use: 

1. Get clear on which partners matter.
2. Recruit for strategic fit and fast value.
3. Enable partners so well they don’t need you on every call.
4. Build repeatable co-marketing plays.
5. Shift co-selling from reactive to strategic.
6. Extend partnerships into customer success.
7. Measure the metrics that truly reflect impact.

When done right, they open markets, increase credibility, deepen customer trust, and accelerate revenue in ways no single team can accomplish alone.

Thanks for reading – I hope you found this blog post useful.

Are you interested in discussing how to improve your partner marketing? If so, let’s have a conversation. My email address is david@alphabetworks.com – I look forward to hearing from you.

Are You Showing Up in ChatGPT Searches?

By David Ronald  

If you’re focused on discoverability, you’ve probably invested years sharpening your SEO strategy – optimizing keywords, building backlinks, and producing content that earns you a coveted spot on Google. 

But now ChatGPT and other large language models have upended tradition.  

The rise of AI assistants has fundamentally changed how people find information, evaluate products, and make decisions.  

Increasingly, users are asking ChatGPT, Claude, or Gemini for direct answers, instead of typing queries into a browser.  

So, in many cases, AI output is the new first impression.  

And the real question becomes: are you showing up in ChatGPT searches?  

In this blog post, I examine what you need to do to ensure the answer is an empathetic “Yes”.

Why ChatGPT Visibility Matters

AI assistants operate differently than search engines.  

They don’t simply point to links; they synthesize knowledge.  

That means if your brand is not referenced in the datasets, reviews, documentation, product comparisons, community discussions, or signals these models draw from, you’re effectively invisible in a fast-growing channel of discovery.  

This matters for three big reasons:

1. AI is becoming the first stop for research

Business buyers increasingly ask ChatGPT for vendor comparisons, market overviews, and product recommendations. If your competitors are being named and you aren’t, that’s a competitive disadvantage you may not even know about.

2. AI shapes buyer expectations

When models summarize your space, they define the narrative. If you’re missing, or inaccurately described, you lose control of your story.

3. AI visibility compounds

As more people ask AI about your category, the model’s understanding of “the top players” entrenches. Being excluded early can lock you out of future visibility.

How to Improve Your AI Visibility

Showing up in ChatGPT results is a content and reputation strategy. Here’s where to start:

1. Strengthen your public footprint

AI models pull from publicly available text across documentation, reviews, press, help articles, blogs, interviews, and reputable databases. The more clear, consistent, factual, and useful content you publish, the more likely you are to appear.

2. Clarify your category

Models respond best when companies articulate their category, target audience, and value proposition clearly. Ambiguous positioning leads to ambiguous AI output.

3. Invest in third-party validation

Analyst reports, customer reviews, independent comparisons, and reputable media coverage give AI models confident signals to learn from. These sources often matter more than what you publish yourself.

4. Answer the questions real users ask

If buyers frequently ask, “What are the best tools for X?”, you should create content that directly addresses those queries. AI learns from patterns of language and intent.

The New Frontier of Discoverability

ChatGPT search visibility has become as important as Google search visibility once was.  

And businesses that take this onboard will earn a durable advantage as AI-native discovery accelerates – while those that ignore it may find themselves missing from the conversations that matter most.  

So, ask yourself this question: when someone asks ChatGPT about your category, are you part of the answer?  

Thanks for reading.  

Are you interested in discussing how to improve your visibility with ChatGPT and other large language models? If so, let’s have a conversation. My email address is david@alphabetworks.com – I look forward to hearing from you.

Measuring the Impact of Product Marketing

By David Ronald

Here’s a thorny paradox.

Product marketing is one of the most influential functions in a company’s go-to-market motion, but it’s also one of the hardest to measure.

Product marketers shape the market perception, the competitive posture, the customer understanding, the go-to-market strategy, and the launch campaign. They often orchestrate how a product becomes something the market wants but, because they operate upstream, the results of their work typically show up downstream in metrics owned by other teams.

This is why many organizations fall into the trap of measuring product marketing by counting activities  such as the amount of content created, sales decks delivered, campaigns supported, and so on.

These are important operational signals, but they don’t reflect strategic contribution – they don’t show how product marketing changes customer perception, strengthens sales performance, accelerates adoption, or increases pipeline quality.

As economic conditions tighten and companies demand clearer attribution for every dollar spent, product marketing leaders must elevate how they communicate their value.  

Measuring the impact of product marketing is essential for shaping strategic decisions, securing budgets, and driving predictable revenue growth – but doing it well requires a shift in mindset.  

In this blog post I examine how product marketing can start demonstrating that it is indispensable. 

Why the Impact of Product Marketing Is Hard to Measure

Unlike sales, product marketing doesn’t close deals. Unlike demand generation, product marketing doesn’t run ads; unlike product, product marketing doesn’t ship features. And, unlike customer success, product marketing doesn’t own retention.

Instead, product marketing influences all of these things. 

That influence is where its power lies, and also where measurement becomes difficult. 

• When product marketing strengthens competitive positioning, it improves win rates – but sales gets the “credit".
• When product marketing improves messaging, it changes how prospects understand value – yet this shows up as higher conversion rates on the website or in sales calls.
• And when product marketing clarifies the ideal customer profile, pipeline quality improves – but demand generation sees the lift. 

The key to measuring the impact of product marketing is to recognize that it is a causal function rather than an ownership function. 

Which means that you are not trying to prove that product marketing owns a metric; you are demonstrating how product marketing contributed to its improvement.  

It’s this mindset shift that unlocks a world of meaningful measurement. 

Five Areas Where Product Marketing Creates Impact

Although product marketing’s responsibilities vary by company, its influence tends to fall into five interconnected areas: 

1. Customer and market insights.
2. Positioning and messaging.
3. Cross-functional alignment.
4. Sales enablement. 
5. Product launches and go-to-market execution.

1. Customer and Market Insights

Product marketing sits at the intersection of market intelligence and product decisions.

Customer insights from interviews, alpha programs, advisory boards, and win/loss analysis shape the roadmap just as much as they shape go-to-market messaging. Competitive insights influence positioning just as strongly as they influence sales tactics.

Measuring this impact means tracking the decisions that flowed from product marketing insights. 

• How many roadmap priorities were informed by user research?
• Which product changes came from product marketing-identified friction points
• How did pricing evolve based on segmentation work? And what improvements followed?

Although these are sometimes qualitative, organizations that build a culture of documentation often find that product marketing plays an outsized role in the decisions that matter most.

2. Positioning and Messaging

Positioning is one of the most powerful levers in go-to-market performance, because it shapes every downstream motion. 

When product marketing improves, it affects website engagement, sales conversations, product adoption, analyst perception, and even investor narratives.

The impact becomes visible through the clarity customers express during calls, how well prospects articulate the product’s value back to you, or the degree to which sales teams naturally adopt the new narrative.

More formal signals, such as improvements in win/loss themes or increased engagement on core pages, provide quantitative support.

Not just that, the most effective product marketing teams track the before-and-after moments: what did customers believe, understand, or misunderstand before the messaging changed, and what shifted after? 

The narrative itself becomes a measurable asset. 

 

3. Cross-Functional Alignment

Product marketing is the glue. 

It is the connective tissue that ensures product, sales, and marketing share the same story, target the same segments, and prioritize the same opportunities.

When this alignment improves, everything else improves – campaigns perform better, sales cycles shorten, launch quality increases, and internal friction decreases. 

When alignment appears, product marketing is almost always the reason.

Measuring alignment can be as simple as tracking cross-functional readiness or conducting periodic internal surveys to capture clarity, confidence, and alignment across teams.  

4. Sales Enablement

Sales enablement is one of the most underrated sources of measurable product marketing value. 

When product marketing equips sales teams with a compelling narrative, strong tools, and great training, revenue performance shifts quickly and tangibly.

The strongest indicators of enablement impact appear in win rates.

Plus, improvements in time-to-first-deal for new reps also reveal whether product marketing has improved sales readiness.

Sales leaders often express the impact qualitatively first, such as “the team finally understands how to sell this”, but the quantitative metrics eventually reflect the shift. 

What distinguishes high-performing product marketing teams is that they measure enablement by how results improve, and not by how many assets they create. 

5. Product Launches

Launches are one of the most concrete places where product marketing influence is both broad and deep.

Product marketing sets the launch strategy, narrative, target audience, enablement plan, and success criteria. A well-run launch accelerates adoption, drives pipeline, and shapes market perception – while a poorly run launch can bury even the strongest product.  

To measure launch impact, product marketing teams focus on the outcomes that tie directly to launch intent. 

• If the goal is adoption, look at 30/60/90-day usage trends.
• If the goal is revenue, examine pipeline influenced or opportunities created in the launch window.
• If the goal is awareness, track media coverage, analyst response, and engagement.

Launch impact is clearest when product marketing establishes a baseline from previous launches and shows how the new playbook lifted results. 

Over time, this becomes a compelling proof-point that product marketing is a multiplier on product investment.   

 

Shifting the Measurement Conversation

The most successful product marketing organizations use a simple mental model to anchor measurement: inputs, outputs, and outcomes. 

1. Inputs are the strategic foundations product marketing provides – research, segmentation, competitive insights, and messaging.
2. Outputs are the assets, programs, and launches that translate those insights into motion.
3. Outcomes are the business results that reflect product marketing’s influence – better win rates, stronger pipeline quality, higher adoption, and clearer market differentiation.

Product marketing teams should track all three, but communicate primarily about outcomes, and the causal story that links them back to product marketing’s work. 

Executives don’t want to know how many assets product marketing created – they want to know how product marketing helped the company win more deals, launch better products, and improve customer understanding. 

Conclusion

High-impact product marketing teams embrace a simple principle: measurement must be designed into the work, not bolted on afterward.

Before launching new messaging, they benchmark current performance. Before launching a product, they define what success looks like. Before rolling out new competitive content, they capture current win rates.

This allows them to tell a clean, credible narrative: 

• Here’s where we were.
• Here’s what we changed.
• Here’s what improved.

Although product marketing may once have been an “invisible function”, it is quickly becoming one of the clearest drivers of differentiation and growth.

And the organizations that measure product marketing well are the ones that unlock its full potential.

Thanks for reading.

Are you interested in discussing how to measure the impact of your product marketing? If so, let’s have a conversation. My email address is david@alphabetworks.com – I look forward to hearing from you.

15 Powerful Tools to Unlock Buyer Intent Data and Drive Growth

By David Ronald  

Understanding buyer intent has become one of the most powerful levers for accelerating growth.  

By uncovering who is in-market, what they’re researching, and when they’re ready to buy, marketers can focus their efforts where it matters most.  

Buyer intent data helps align marketing and sales teams, shorten sales cycles, and personalize outreach at scale.  

In this blog post I take a look at a variety of tools can help you capture and act on these insights. 

(Just a heads-up: this reads a bit like a laundry list – my apologies for that – some people express themselves through poetry but I, apparently, prefer bullets.) 

1. Third-Party Intent Data Platforms

Third-party intent tools collect and analyze behavioral signals from across the web, such as content consumption, searches, and engagement, to identify companies showing buying interest.

• Bombora – one of the best-known providers, aggregating intent signals across a massive B2B data co-op.
• ZoomInfo Intent – combines intent topics with firmographic and contact data, giving sales teams a clear picture of who to target.
• 6sense – uses AI to predict buying stages and prioritize accounts for outreach.
• Demandbase – integrates intent insights with account-based advertising and personalization campaigns.
• Dealfront (formerly Leadfeeder) – identifies the companies visiting your website, even when visitors don’t fill out a form.

When used together, these intent sources give marketing and sales teams a multidimensional view of in-market buyers, allowing for more precise targeting and higher-converting outreach.

2. First-Party Intent Tools

Your own data can be just as powerful.  

First-party intent tools leverage website activity, email engagement, and content downloads to uncover high-potential leads.

• HubSpot – provides lead scoring and behavioral tracking across all your owned channels.
• Marketo (acquired by Adobe) – uses predictive scoring to identify accounts most likely to convert.
• Drift (now part of Salesloft) and Qualified – surface real-time engagement signals from live chat and conversation flows.
• Clearbit Reveal (acquired by HubSpot) – identifies anonymous website visitors and enriches them with firmographic data.
• Mutiny – personalizes website experiences for high-intent visitors to increase conversions.

When combined, these first-party insights give you a clear, real-time picture of which accounts are leaning in, so you can engage them proactively and accelerate pipeline.

3. Review and Content Engagement Platforms

When buyers are comparing vendors, their research activity becomes a goldmine of intent data.

• G2 Buyer Intent – alerts you when companies are viewing your product or category pages.
• TrustRadius Intent Data – highlights which businesses are reading reviews or running side-by-side comparisons.
• Capterra and Gartner Digital Markets – offer similar insights for software buyers across various verticals.

These signals give you near-real-time visibility into active evaluation cycles, helping you prioritize accounts that are closest to making a purchase decision.

4. Data Enrichment and Signal Integration Tools

Intent data becomes most powerful when connected across systems.

• Apollo – merges verified contact data with intent signals for targeted outreach.
• RollWorks – integrates intent into your account-based marketing campaigns.
• Slintel (now part of 6sense) – combines technographic and intent data for precise segmentation.
• Triblio – automates follow-up by syncing multi-source intent scores with your CRM.

By unifying these sources, you create a single, actionable view of account readiness – enabling smarter orchestration, tighter alignment, and more effective engagement across the entire GTM motion.

5. Social and Search Intent Tools

Social and search activity reveal valuable signals about buyer interests.

• LinkedIn Sales Navigator – surfaces engagement data within your target accounts.
• SparkToro – identifies where your audience spends time and which topics influence them.
• Google Ads and Search Console – provide keyword-level insights into what prospects are actively searching for.

These signals help you understand what topics are resonating in the moment, allowing you to tailor content and outreach to match active buyer interests.

Conclusion

Buyer intent data doesn’t just help you see who’s interested, it also helps you act faster and smarter.  

The strongest buyer intent strategies combine third-party, first-party, and contextual data sources. By leveraging this combination you will observe better alignment, higher conversion rates...

And a marketing engine that’s driven by insight.  

Thanks for reading – I hope you found this blog post useful.  

Are you interested in discussing the tools that you can leverage to uncover buyer intent? If so, let’s have a conversation. My email address is david@alphabetworks.com – I look forward to hearing from you.

A Brief Guide to Content Marketing

By David Ronald 

Brands win when they create content that feels purposeful, trustworthy, and unmistakably human.

Yet, truly effective content is the outcome of a thoughtful, ongoing relationship between a brand and its audience.

Over the years, I’ve watched teams transform their marketing simply by stepping back and asking, “Why are we creating this?” 

Everything else flows from that clarity.  

In this blog post I examine the best practices that separate truly resonant content from digital noise.

(You may also be interested in reading this post Mapping Content to Your Buyer’s Journey.)

Start With Strategy, Not Output

Too many marketing teams jump straight into production without understanding how any of it connects into business goals.

The best content marketers, by comparison, begin with something more foundational. Strategy. 

Before a word is written, you should know which business objective the content supports: 

• Is it meant to generate leads?
• Establish authority?
• Nurture customer loyalty?
• Or something else? 

And who exactly are you trying to reach at that moment in their journey?

Once these anchors are clear, choosing formats becomes intuitive: early-stage buyers might need educational explainers, while those closer to purchase benefit from case studies, webinars, or ROI tools.

When strategy drives creation, content stops being clutter and starts becoming a force multiplier. 

Let Your Brand Voice Do the Heavy Lifting

A distinctive tone builds familiarity, and over time, trust – the key is consistency, whether your brand sounds authoritative, warm, witty, or visionary.

For example, a cybersecurity startup may use calm, data-driven language signals credibility – a wellness brand may adopting a softer, more empathetic tone that conveys approachability. 

What matters is that every piece of content, feels like it comes from the same personality – documenting your voice ensures that anyone who creates content reinforces the same identity. 

Lead With Storytelling, Grounded in Substance

We are wired for stories.

But storytelling isn’t about being dramatic – it’s about making meaning tangible. The most resonant content casts the customer as the hero and the brand as the guide – it highlights tension (ie, what challenge the customer faces) and resolution (ie, how insight, not hype, helps them overcome it).

The story may bring people in, but it’s the substance that keeps them there.

Pairing narrative with expertise is the combination that turns readers into believers. 

Create for Humans First, Algorithms Second

Search still matters, but modern algorithms reward what humans reward: clarity, relevance, and value. The days of stuffing pages with keywords are long gone.

A user-first mindset changes how you write. You focus on topics instead of keywords, structure articles for readability, and incorporate visuals or data to elevate the experience.

Ironically, the more human your content feels, the better it performs in search. 

Reach Audiences Where They Already Are

Because people consume information differently, format diversity matters. Some audiences gravitate toward long-form articles; others prefer short videos, podcasts, or interactive tools.

Effective marketers don’t try to be everywhere - instead, they selectively show up where their audience already spends time.

A deep-dive blog can be converted into a video summary. 

A customer interview can become a podcast; a webinar can produce social clips and infographics.

So, distribution becomes a strategic act, not an afterthought. 

Let Data Be Your Compass

Content is creative, but it’s also analytical.

Every interaction leaves a trail of insights – what people click, how long they stay, what they share, where they drop off. These patterns tell you what resonates and what falls flat.

High-performing content should be repurposed and expanded – and underperformers should be refreshed or retired.

When teams treat analytics as feedback rather than judgment, they evolve faster and produce content that feels increasingly indispensable. 

Quality Over Quantity

The digital world is overflowing with content.

What’s scarce is clarity, originality, and meaningful insight – producing more doesn’t increase impact; publishing better does.

High-quality content reflects real research, thoughtful structure, and a point of view – it adds something new, an opinion, a framework, a dataset, that audiences can’t find in ten other tabs.

In the end, a handful of exceptional pieces will always outperform a flood of forgettable ones. 

Build a Culture of Collaboration

Great content is rarely created in isolation.

It comes from cross-functional collaboration: product teams who understand features and roadmaps, sales teams who hear objections firsthand, customer success managers who know what frustrates and delights users.

When these voices inform the editorial process, content becomes more relevant, accurate, and aligned with go-to-market priorities.

Monthly content councils, shared dashboards, and regular feedback loops turn content into a company-wide asset, not a marketing department project. 

Repurpose and Refresh to Maximize Impact

You don’t need to reinvent the wheel every time you launch a new campaign. Often the most powerful content already exists, it just needs to be reshaped or modernized.

A popular article can become a LinkedIn carousel; a podcast interview can become a case study; a series of related blogs can evolve into an eBook or a nurture sequence.

This approach not only saves time but reinforces your brand’s key messages across channels and formats. 

Earn Trust Through Transparency

In an era where AI-generated content floods every feed, trust is the most valuable currency. Audiences can sense the difference between content created to manipulate and content created to help.

Attribution to real authors, transparent sourcing, honest reflections, and open engagement are powerful trust-builders.

When a brand demonstrates humility, expertise, and empathy, people do more than simply consume the content – they rely on it. 

Use AI Thoughtfully, Without Losing the Human Spark

AI has become a powerful creative partner.

It can cluster keywords, draft outlines, analyze user behavior, and automate repetitive tasks.

But it cannot replace human insight, intuition, or imagination.

The best content teams use AI to accelerate workflows, not dictate them. AI handles the grunt work; humans shape the story.

That partnership (I think of it as “speed with soul”) is what sets modern content marketing apart. 

Measure the Metrics That Matter

Executives want results, and the strongest content teams speak the language of impact.

Instead of celebrating vanity metrics like impressions, they connect content to outcomes: pipeline creation, lead quality, customer expansion, share of voice, loyalty.

Clear dashboards, regular reporting, and narrative insight about why content worked help stakeholders see the strategic value. 

Once they do, support, and investment, increase.

Commit to Continuous Learning

Content marketing is a moving target.

New channels appear, old ones fade, and audience expectations shift constantly.

The teams that thrive are the ones that stay curious – reading industry reports, watching emerging formats, experimenting with new ideas, and analyzing their wins and failures.

Curiosity is a competitive advantage.

Each iteration makes your content sharper, more relevant, and more aligned with what audiences truly need. 

Conclusion

The best content has the potential to transform minds.

It turns passive readers into active advocates and fleeting attention into lasting loyalty.

When strategy meets storytelling, when clarity pairs with creativity, content becomes more than a tactic. It becomes the heartbeat of a brand.

When you commit to creating content that is strategic, human, and consistently excellent, you’re building trust at scale.

Thanks for reading – I hope you found this blog post useful.

Are you interested in discussing how to improve your content marketing? If so, let’s have a conversation. My email address is david@alphabetworks.com – I look forward to hearing from you.

The Marketing Report That I Trust Above All Others

By David Ronald

Every marketer has a report that they rely on.

A report that cuts through bias, noise, and opinion to reveal the truth of what’s really happening.

For me, it’s the weekly pipeline influence report.

It’s the one snapshot that keeps our feet planted firmly on solid ground – especially when everything else in the business feels full of shifting narratives and competing priorities. 

In this blog post I explain why this report matters to me so much. 

What is a Pipeline Influence Report?

A weekly pipeline influence report is a recurring analysis that shows how marketing activities are contributing to the creation and progression of the revenue pipeline. 

At its core, it highlights what pipeline was created or progressed, which touchpoints shaped that movement, and where early opportunities or bottlenecks are emerging. 

It brings together data from a variety of sources including our CRM platform, marketing automation platforms, and website analytics to reveal which campaigns are influencing opportunities at each stage of the buyer’s journey. 

And, because it’s built on consistent definitions and clean data sources, it provides a stable, trusted view of how marketing affects real revenue outcomes, and not just vanity metrics.

What The Report Shows

The pipeline influence report tells the story of real customer movement, not surface-level performance data, and it does so without clutter.  

At its core, the report answers three things: 

1. What pipeline was created or progressed this week? This surfaces new opportunities, deals that moved forward, and any shifts in deal velocity or value.
2. Which marketing touchpoints influenced that movement? It connects engagements such as content downloads, events, ads, emails, or website activity to opportunities, showing where marketing is helping spark or accelerate buyer interest.
3. Where are the emerging opportunities or bottlenecks? By normalizing data week over week, it highlights patterns, friction points, or early signals that might impact future revenue.

Because it’s built on consistent definitions (eg, what counts as an “influence,” “qualified engagement,” or “pipeline”), it provides a stable and trusted view of how marketing affects revenue outcomes.  

When done well, it connects the dots across channels, campaigns, and sales activities without exaggerating marketing’s role or underplaying the contributions of the broader go-to-market engine. 

Building Your Own Pipeline Influence Report

Although there isn’t a “one-size-fits-all” example of a “weekly pipeline influence report,” especially since much of the information on would be proprietary, there are some excellent templates available: 

1. Pedowitz Group

The Pedowitz Group provides a practical breakdown of how to define, track, and report influenced pipeline. Their guide outlines the core elements: defining qualifying touchpoints, mapping contacts to opportunities, choosing an attribution model, and building dashboards that show pipeline / revenue by channel and program. 

2. Salesforce

If you use Salesforce, there’s a built-in Campaign Influence feature, and you can run reports like “Campaigns with Influenced Opportunities (Customizable Campaign Influence)”. 

3. Qualified

Qualified offers a Weekly Pipeline Council framework that’s designed for cross-functional team alignment. While not exactly a “pipeline influence report” in the pure marketing attribution sense, this kind of structured weekly council model ensures the data (influenced pipeline, velocity, risk) is being consumed by stakeholders and acted upon. 

4. Microsoft

Microsoft’s Dynamics 365 Marketing (Customer Insights / Journeys) has a built-in Marketing Program Effectiveness report. It includes a “Lead Pipeline” report and an ROI / attribution section. You can export or snapshot this weekly to serve as your influence report if you define “programs” or “journeys” as your influencing touch points. 

5. ClickUp

ClickUp provides a weekly sales report template that tracks key pipeline metrics: velocity, number of new opportunities, deal values, conversion rates, and so on. While it’s more of a sales pipeline report than a “marketing influence” report, you could combine this with a custom influenced-pipeline dashboard to approximate your weekly pipeline influence report. 

Conclusion

When a report consistently helps you make better decisions, you start to rely on it – not out of habit, but out of earned confidence.

And over time, it becomes more than a dashboard. It becomes the compass you trust in both calm and chaotic seasons, the one source that points you back to what buyers are actually doing, not what anyone wishes they were doing.

Thanks for reading – I hope you found this blog post useful.

Are you interested in discussing how to improve your ability to track marketing’s influence on pipeline? If so, let’s have a conversation. My email address is david@alphabetworks.com – I look forward to hearing from you.

How to Make Your Product Launch a Success

By David Ronald  

Nearly 95% of new products fail to create profitable impact, according to research from Harvard Business School. 

Not surprisingly, the cumulative cost in wasted development budgets, marketing spend, opportunity cost, and brand damage of these failures is enormous.  

What’s more, many of these failures don’t stem from bad ideas or technology, but from overlooking the go‑to‑market and launch disciplines that separate a promising concept from a commercially successful offering.  

In this blog post I provide guidance on how to embed launch rigor, align cross‑functional stakeholders, and transform your next product release into a growth engine instead of a write‑off.  

(You may also be interested in reading this blog post Too Many Product Launches Are Unsuccessful.)

1. Launch Discipline

One of the major reasons why products flop is due to companies becoming “too engrossed in product development” and neglecting market readiness.  

But building a product doesn’t guarantee market traction – what matters is how you bring it into the world, how you communicate value, how you reach the right buyers, and how you support them once they adopt. 

In many ways launching a product is like sending a rocket into space  – building the rocket is essential, but if you don’t coordinate launch timing, trajectory, mission control, communications, and landing procedures, you might build a beautiful spacecraft that never reaches orbit.  

And the very high failure rate of new product launches shows that many organizations miss one or more of those mission‑critical pieces.  

By building discipline into a launch you make visible the hand‑offs, dependencies, timelines and metrics across product, marketing, and sales.

2. Performance Metrics

Tracking a launch shouldn’t be about checking boxes. It needs to be about measuring signals that the product is resonating and scaling. And, in this regard, there are five metric categories that we need to consider: 

2.1 Awareness

How many target prospects know about the offering and have seen targeted messaging?

• Measure – website traffic to launch pages, downloads of pre‑launch assets, invitations accepted, ad click‑throughs, earned media mentions.  

A key question at this stage is this – are we getting sufficient exposure among the right segment of buyers, not just broad traffic?

Ultimately, this stage is about ensuring awareness translates into meaningful engagement with the audiences that matter most.

2.2 Engagement

Are prospects actively interacting with the product narrative and experiencing value?

• Measure – free trial or demo sign‑ups, webinar attendance, product preview invitations, event participation.

The key question to address now is this – is the engagement meaningful (ie, deep enough) to suggest interest, not just curiosity?

The goal here is to confirm that prospects are moving beyond initial interest and beginning to connect with the product’s real value.

2.3 Acquisition

Are we converting engaged prospects into paying customers at an acceptable rate and cost?

• Measure – conversion rate from demo to customer, customer acquisition cost, time‑to‑close. 

The all important question here is this – is our cost to acquire acceptable relative to the expected lifetime value of the customer?

This phase is about validating that our acquisition efforts are both efficient and sustainable in driving profitable growth.

2.4 Retention

Are customers staying, using, deriving value and avoiding churn?

• Measure – monthly/weekly active users, churn rate, usage metrics, customer health scores.

A key question to answer at this stage is this – does the product deliver value such that customers want to stay and expand?

This stage focuses on ensuring customers realize lasting value that deepens their loyalty and drives long-term retention.

2.5 Referrals

Are customers so delighted that they refer others, amplifying growth?

• Measure – net promoter score, referral count, viral coefficient, word‑of‑mouth indicators.

The most valuable question to answer now is this – do customers act as advocates (not just users)?

Additionally, collect qualitative feedback from customers, prospects, sales, marketing, and product teams to surface issues, insights and opportunities for improvement.

3. Cross‑Functional Alignment

One of the major launch risks is functional silos. 

Product builds something, marketing tries to push it, sales tries to sell it, but alignment is weak. It's crucial to build a coordinated launch plan with owners, deadlines, KPIs and an end date.  

But how do you make this work?

• Define a launch command center – designate a launch lead (often from product marketing) who owns end‑to‑end readiness. Bring together stakeholders from product, engineering, marketing, sales, enablement, support, operations, finance, and channel/partners.
• Build your launch plan as a living document – include launch goals, target segments, positioning, key message pillars, pricing/packaging decisions, distribution strategy, marketing campaign timeline, sales enablement materials, support readiness checklist, risk mitigation items, and metrics.
• Set an end date – launch may schedule a date, but the real work lies in the “post‑launch review” phase (such as measuring outcomes, comparing to KPIs, capturing learnings, deciding next steps). Without an end date, the launch drifts into “we shipped, now we move on” mode and you lose evaluation, feedback and refinement.
• Communicate continually – keep internal teams and external stakeholders updated via weekly or bi‑weekly status reviews, dashboards, risk logs, and decision points. Transparency reduces surprises and aligns everyone to the same objectives.

By establishing clear ownership, living plans, defined timelines, and ongoing communication, you turn a potential siloed effort into a coordinated launch that delivers measurable impact. 

4. Pre‑Launch Demand Building

If you think launch day is the moment when demand begins, you’re probably already be behind.  

Effective launches often start weeks or months in advance with demand‑building activities that include thought‑leadership, awareness campaigns, community engagement, pre‑registrations, beta access, influencer outreach, and partner outreach.  

By building a pre‑launch funnel you do three things:

• You warm up the audience so that launch day already has traction.
• You validate messaging and offer (by tracking sign‑ups, engagement, conversion intent) and iterate early.
• You build operational muscle (marketing campaign flow, sales outreach, onboarding processes) before full scale.

This aligns with the concept of a customer journey that begins well before the product is sold.  

As the original article iterates, the buyer journey moves from “Unknown” to “Known” to “Engaged” and, finally, to “Converted”.

Extend that idea to the product launch journey: build awareness and engagement ahead of time, convert early adopters, iterate, then scale.

5. Scaling After Launch

Many product marketing teams celebrate on launch day and assume the job is done.  

But the reality is, the hardest work often begins after launch.  

 So, you should:

• Plan for scale – if the product starts gaining traction, do you have the processes to expand marketing spend effectively, onboard new customers efficiently, support them professionally, and capture referrals? If not, you risk peak and decline.
• Monitor metrics continuously – use the five metric categories (awareness through referrals) to track early indicators of trouble: stagnating conversion, accelerating churn, weak engagement, siloed acquisition. Use dashboards, regular reviews, and trigger thresholds (eg, conversion falls below X% for two weeks → initiate corrective action).
• Iterate and optimize – no product launch is perfect. Use early feedback to refine messaging, pricing, packaging, onboarding flows, and even product features. Treat the launch as a 90‑day sprint, not a one‑and‑done event.
• Leverage success for momentum – when you hit milestones (eg, first 100 customers, first customer success story, first referral loop), use them as marketing assets. Social proof and case studies accelerate adoption and credibility.

Growth is never automatic. Conversion curves, customer onboarding, usage adoption, churn, upsell, channel activation all need nurturing.

6. Leadership Imperatives

Beyond process and metrics, the kind of culture you bring to product launches makes a big difference. Some leadership and cultural behaviors that correlate with successful launches include:

• Customer obsession – building a product you think customers want is not enough — focus on what customers demonstrate they want, will pay for, and will use.
• Cross‑functional collaboration – product development, marketing, sales, support, operations all need to work in tight feedback loops rather than hand‑offs.
• Launch mindset not just “shipping” mindset – many organizations celebrate the development milestone (“It’s out!”) but fail to celebrate the business milestone (“It’s used, valued, scaling!”).
• Fail fast, learn faster – instead of burying failures, investigate them quickly, share learnings, adjust next launches.
• Accountability for outcomes – everyone involved in the launch should own the metrics and be involved in post‑launch reviews.

Cultivating these behaviors creates an environment where launches are not just completed, but truly drive impact, growth, and lasting customer value.

7. Launch Checklist

Here’s a practical checklist you can consider using when planning your next product launch:

• Define the business goals such as target revenue, market share, margin, time‑to‑break‑even.
• Map buyer segments and buyer journey for this product specifically.
• Conduct pre‑launch validation using messaging tests, pre‑registrations, pilot customers, willingness to pay.
• Build a launch plan with owners, milestones, KPIs, risk mitigation, end date and post‑launch review.
• Ensure pricing and packaging are aligned with value and segment.
• Create demand‑gen pipeline ahead of launch (awareness, engagement).
• Coordinate with sales/enablement regarding things such as training, collateral, pricing tools, objection handling.
• Ensure operational readiness across customer success staffing, support workflows, supply/distribution, onboarding flows.
• Establish launch metrics dashboard across awareness, engagement, acquisition, retention, referrals.
• After your launch, review performance, capture learnings, and iterate as needed.

Following this checklist helps ensure your product launch is strategic, coordinated, and positioned for measurable success from day one and beyond. 

Conclusion

It’s simply not enough to build an innovative product.

You must also launch smart.  

A robust launch process, disciplined cross‑functional alignment, validated market readiness, tracked metrics and a culture tuned to outcome, not just output, aren’t optional . They’re the difference between writing off your investment and unlocking growth, momentum and distinction.  

If you commit to linking product launch activities with business outcomes, treat launch as a strategic discipline and embed a learning‑and‑iteration mindset, your next product release is far more likely to be one of the 5 % that succeeds.  

And, what happens when it does?  

The rewards for growth, brand credibility, customer loyalty, and economic return are well worth the investment. 

Thanks for reading – I hope you found this blog post useful.  

Are you interested in discussing how to improve your next product launch? If so, let’s have a conversation. My email address is david@alphabetworks.com – I look forward to hearing from you.

The Product Marketer’s Guide to Market Research

By David Ronald

Market research isn’t a “one and done” project.  

Market research is a continuous feedback loop that keeps product marketers aligned with their customers, competitors, and the market’s direction of travel.  

Yet, in practice, many teams treat it as a box to check before a launch.  

This is a mistake that will create problems downstream.  

Truly effective product marketing teams know that smarter market research is what fuels everything: messaging that resonates, positioning that differentiates, and strategies that drive growth.  

In this blog post I explore some of the best practices that product marketers can apply in their market research.

1. Start with a Clear Objective

Before collecting any data, define why you’re doing the research.  

Are you trying to size a market opportunity? Validate messaging? Understand buyer pain points? Or something else.  

Clarity here prevents wasted effort and ensures every question and interview serves a specific purpose.  

Write down the decision you need to make and frame your research around that. 

For example: “We need to know whether our target audience values speed or reliability more – so we can adjust our product messaging accordingly.” 

2. Blend Quantitative and Qualitative Insights

Smarter market research doesn’t rely on one type of data.

• Quantitative methods, such as surveys, usage analytics, or secondary market data, show you what’s happening.
• Qualitative methods, including interviews, focus groups, social listening, explain why it’s happening.

The best product marketers triangulate both to get a full picture.  

For instance, survey data might reveal that 60% of buyers switch vendors within a year, but one-on-one interviews uncover the real reason: frustration with onboarding complexity.

3. Don’t Skip Competitive Intelligence

Competitive research is more than just tracking product features or pricing.  

It’s about understanding positioning. How are your competitors framing their value? Which segments are they targeting? What emotional levers are they pulling?  

Set up a simple framework to track competitor messaging, campaigns, and reviews monthly.  

This living document can be a goldmine for refining your own differentiation story.

4. Bring Sales and Customer Success Into the Process

Frontline teams often hear customer pain points long before they show up in survey data.  

Regularly interview sales and customer success reps to capture those insights early.  

Ask them questions such as, “What objections come up most often?” or “Which customer stories make deals close faster?” 

Integrating this voice-of-customer intelligence into your research makes your findings more grounded – and your go-to-market strategy more effective.

5. Turn Findings Into Action

Even the smartest research is useless if it stays trapped in a slide deck.  

Summarize insights in a concise, narrative format – highlight what’s new, what it means, and what action it requires. 

Create simple one-page briefs for stakeholders or use internal workshops to turn insights into positioning updates, campaign ideas, or roadmap inputs.

6. Make It Continuous

Markets move fast, and insights age quickly.  

Build lightweight, ongoing mechanisms to keep a pulse on change – automated sentiment tracking, regular win-loss interviews, or quarterly buyer persona refreshes. 

When research becomes a habit, not a project, product marketers stay closer to their customers than the competition ever will.  

Smarter market research is about better questions and faster learning.

When done right, it becomes your most powerful strategic asset – not just informing your marketing, but shaping the very direction of your business.  

Thanks for reading – I hope you found this blog post useful.  

Are you interested in discussing how to improve your market research? If so, let’s have a conversation. My email address is david@alphabetworks.com – I look forward to hearing from you.

How We’re Using Artificial Intelligence to Drive Innovation and Growth

By David Ronald

Artificial intelligence has moved swiftly from the realm of curiosity, to a core driver of marketing performance.

In my opinion artificial intelligence needs to be woven into every aspect of how marketing is planned, executed, and measured.

AI has the potential to amplify human creativity, intuition, and judgment, and creativity.

The magic lies in understanding where human expertise and machine intelligence intersect – and I’ve found that the most powerful outcomes happen when AI enhances how our team thinks, decides, and collaborates. 

In this blog post I examine some of the ways that Alphabet Works is using AI to accelerate strategy formulation, unlock creativity, and transforming operations. 

 (You may also be interested in reading this post AI is Changing the Role of the CMO, and this one 5 Ways Artificial Intelligence will Improve Marketing ROI too.) 

1. Turning Data Into Decisions

Yes, modern marketing runs on data, but it’s insights that provides us with an edge.

In this context, AI has become indispensable in moving us from raw data to meaningful action.

For example, we’ve evaluated AI-powered analytics tools such as Google Cloud Vertex AI and Tableau Pulse to surface patterns that could otherwise go unnoticed.

AI also helps us forecast performance.

By feeding historical data into machine learning models and using tools like Azure Machine Learning, HubSpot’s AI Forecasting, and Salesforce Einstein we’ve been able to anticipate which campaigns will deliver the strongest ROI and which markets are trending upward.

This predictive capability has transformed our quarterly planning process.  

So, instead of debating opinions, we align around data-backed probabilities – a shift that has made our decision-making faster and more confident. 

2. Enhancing Creativity, Not Replacing It

One of the most misunderstood aspects of AI is its role in creative work – I see AI as a catalyst for human imaginations, not as a replacement for it.

When developing positioning, messaging, or campaign ideas, I frequently use ChatGPT as a creative partner.

For example, I might prompt an AI system with a simple concept like “how to convey trust in a privacy-focused SaaS brand,” and receive dozens of angles I hadn’t considered.

Most won’t be perfect, but a few might spark a breakthrough.

We've also used AI to rapidly test variations of creative content. 

Instead of guessing which copy or visual will resonate most, AI tools like Copy, Jasper, and Midjourney can generate and analyze hundreds of A/B test variations within hours – which lets our creative team focus on crafting excellence, rather than just iterating endlessly. 

So, what results have we seen?  

Well, faster idea generation, richer brainstorming sessions, and higher-performing campaigns that are still distinctly human in tone and feel, are some of the most significant ones. 

3. Automating Repetition to Unlock Strategic Focus

We can all agree that AI excels at handling what I call the “busywork of marketing”, those repetitive, process-heavy tasks that are necessary but not strategic.

For instance, we’ve automated routine campaign reporting.

Instead of analysts spending hours pulling numbers from multiple platforms, AI tools like Google Looker Studio, HubSpot’s Marketing Analytics, and Tableau Pulse now consolidate data into visual dashboards that update in real time.

We also leverage AI for content summarization.

When hundreds of customer survey responses come in, tools such as MonkeyLearn, GPT-4, or Synthesio can group feedback into themes within minutes.

The insights that used to take weeks are now available in hours – and that speed translates into faster customer-driven action.

These automations free up valuable team bandwidth.  

Instead of grinding through reports or transcriptions, we focus on market insight, creative strategy, and long-term planning, which is the work that moves the needle. 

4. Reinventing Customer Understanding

AI has positively affected how we listen to and understand customers.

We’re looking at sentiment analysis tools such as Brandwatch, MonkeyLearn, and Sprinklr AI to monitor customer conversations across social channels, review sites, and support tickets.

But instead of just tracking sentiment, we look for emotional driver, which is the “why” behind the feedback.

In one very interesting example we use AI-based clustering to analyze product reviews with tools such as AWS Comprehend and Google Cloud Natural Language AI – we uncovered that “speed” and “ease of setup” were far more influential on satisfaction than “price” or “features”.

And that was an insight which directly shaped our messaging hierarchy.

We also use conversational AI to simulate customer interviews. 

By training AI models on actual feedback with platforms like ChatGPT and Forethought we can ask, “What would this customer persona think about a new feature?” and get remarkably human-like responses.

This shouldn’t replace real customer conversations, of course, but it can help test ideas early, cost effectively.  

The result is a richer, more dynamic understanding of our audience, one that keeps us responsive to shifts in sentiment, behavior, and expectation. 

5. Personalization at Scale

Every marketer talks about personalization, but AI makes it truly scalable.

We’ve evaluated AI-driven recommendation engines like Dynamic Yield and Salesforce Einstein to tailor content, offers, and messaging based on user behavior and preferences.

We feel that it’s about creating experiences that feel one-to-one – and no longer about creating “segments” of thousands.  

HubSpot, for example, uses machine learning to predict the best send time and content for each recipient based on prior engagement patterns.

Open rates and conversions have improved significantly because of smarter delivery powered by AI, not because of a smarter campaign concept.

We’re also exploring AI-assisted customer journeys with platforms like Braze that adjust dynamically – if a prospect spends extra time on a particular product page, AI can automatically trigger a follow-up with content specific to that interest. 

It’s about contextualization, and not just personalization.  

Every interaction becomes a learning moment, and every touch point gets smarter over time. 

6. Powering Content Strategy and SEO

When planning long-form thought leadership pieces, we’ve started with AI-assisted content mapping tools like Clearscope and MarketMuse.

These tools have helped us identify gaps in our coverage, and opportunities to establish authority in emerging areas.

AI also streamlines content production.

Tools such as Notion AI for summarization, Otter for transcription, and Writer for topic modeling, allow us to transform webinars, podcasts, and events into high-performing articles and social posts in a fraction of the time. 

Our SEO expert has used HubSpot’s Content Assistant and Surfer SEO to predict how search algorithms might evolve, helping us stay ahead of shifts in ranking factors.  

The combination of predictive analytics and creative storytelling has the potential to make our content strategy both agile and authoritative. 

7. Measuring Impact Beyond Vanity Metrics

In marketing, what gets measured drives behavior, as everyone knows.

And, within this context, AI continues to help us evolve our measurement framework beyond surface-level metrics.

We evaluated a variety of machine learning models, powered by platforms like Google Cloud Vertex AI and Tableau with Salesforce Einstein Discovery, to correlate engagement data with long-term business outcomes such as pipeline velocity, renewal likelihood, and customer lifetime value.

This will enable us to attribute results to specific campaigns with far greater accuracy.

AI also helps identify latent value through tools like Amplitude and Heap, which surface touch points that don’t immediately convert but strongly influence purchase decisions later.

Understanding this “assist value” has reshaped how we invest across channels.

These deeper insights have transformed our reporting from backward-looking to forward-guiding.

 So, instead of asking, “What happened?” we’re asking, “What’s likely to happen next, and how can we shape it?” 

8. Elevating Partner and Ecosystem Marketing

Partnerships are a huge growth lever, and AI is helping us maximize their impact.

We looked into using account intelligence tools like Crossbeam (with Reveal) to map ecosystem overlap, identifying where our partners’ customers align with our ideal customer profile.

This has helped us prioritize co-marketing efforts with the highest joint potential.

AI also enables real-time performance tracking for partner campaigns through platforms such as Allbound and Impartner - we can see which assets are driving engagement across partner channels, then double down on what works, without weeks of manual reporting. 

In group planning meetings, AI models built with Clari and HubSpot’s predictive analytics can even simulate revenue outcomes based on different budget allocations. 

This data-driven approach has elevated our partner relationships from transactional to truly strategic collaborations. 

9. Strengthening Internal Collaboration and Knowledge Sharing

AI has improved not just what we deliver externally, but how we operate internally.

We’ve tested knowledge bases like Guru and Notion AI that automatically summarize campaign learnings, customer insights, and competitive intelligence. 

Anyone on the team can query these systems to find what’s working, and what didn’t, in mere seconds.

This can remove silos and accelerate decision-making.

Our company is more connected, more informed, and, ultimately, more creative as a consequence.

Even simple AI features, such as automated meeting summaries in Fireflies or Otter have improved alignment.

Instead of rehashing discussions, we feel like we can move straight to action. 

10. Building a Culture of Experimentation

Perhaps the most transformative impact of AI is cultural, and not technological.

By automating the routine and surfacing insights faster, AI has made experimentation part of our everyday rhythm.

Using tools such as ChatGPT for ideation and content refinement and Airtable for workflow automation, we’ve tested more ideas, learned faster, and scaled what works without worrying about wasted effort.

Our mantra is, “Let AI do the heavy lifting, so humans can do the heavy thinking.” (I’d like to claim credit for this one but, sadly, I’m unable to.) 

Every marketing team faces the common constraints of bandwidth and budget.

AI doesn’t erase these concerns, but platforms such as Asana Intelligence and ClickUp Brain can help allocate energy where it matters most. 

Conclusion

The future of marketing belongs to those who treat AI not as a toolset, but as a mindset – it’s about curiosity, adaptability, and a willingness to evolve how we work.

For us, AI is a multiplier of ideas, efficiency, and insight, and it helps our team make faster and better decisions.

But the ultimate goal is to make marketing more human, not more automated. 

By letting AI handle the complexity beneath the surface, we free ourselves to focus on empathy, storytelling, and strategy which are, of course, the timeless foundations of great marketing.

We’re just beginning to see what’s possible when human creativity and machine intelligence truly collaborate.

And that’s what makes this moment in our industry so exciting.

Thanks for reading – I hope you found this blog post useful.

Are you interested in discussing how you can leverage AI to make your marketing better? If so, let’s have a conversation. My email address is david@alphabetworks.com – I look forward to hearing from you.