Total Product Marketing

Total Product Marketing Marketing & Design for Hosting, Cloud and Technology Companies You are a founder-led start up with absolutely no marketing personnel. Desktop-as-a-Service?

You’ve enjoyed early growth but it’s time to get serious and differentiate – AWS isn’t going away anytime soon. You are an established player in your industry going through a transition or are in need of veteran presence to provide some high-quality volume to your marketing and lead generation efforts. All good reasons for needing Total Product Marketing services. We live, eat and breathe the Clou

d, the Hosting sector and technology. We spend time learning about PCI and HIPAA. We understand application optimization. Yes, we believe it’s coming on strong. Whatever your situation, there will be times when you have an urgent need for a “burst” of senior-level product marketing hands-on-help. We’re ready for you.

08/21/2026

🤖 The best AI prompt might not be a prompt at all.

A lot of the early conversation around AI focused on finding the “perfect prompt” that would suddenly unlock better results. But in practice, the real advantage comes from giving AI enough context, clear guardrails, and a repeatable way of working.

That means defining things like the role AI should play, the context behind the task, the style you want, and the rules it should consistently follow.

It also means treating AI less like a vending machine and more like a collaborator.

For more complex work, one of the most useful instructions can simply be to have the AI ask questions until it understands the task well enough to proceed. That often produces a better result than trying to cram every possible detail into one giant prompt.

The same applies to recurring workflows. If you find yourself giving AI the same instructions every week, that is probably a sign the process should be saved, standardized, or turned into a reusable workflow.

And once AI can access the actual tools, documents, and data involved in the work, the value increases even further.

The shift is subtle but important:

Prompting is becoming less about “How do I phrase this perfectly?”

And more about:

“How do I create an environment where AI consistently understands how I work?” 🧠

That is when AI starts becoming part of the workflow rather than something you occasionally ask for help.

https://contentmarketinginstitute.com/ai-content-creation-tools/write-ai-prompts

Too many AI prompts fail to deliver. See how top marketers structure theirs — from role-context frameworks to hallucination guardrails.

08/19/2026

🌐 Your website can be doing everything right and still not be enough to reach today's B2B buyer.

That is because the buying journey no longer happens in one place.

A prospect might first encounter your company on LinkedIn, research you through an industry publication, compare reviews, watch a video, receive an email, and only then visit your website.

If your marketing strategy depends primarily on getting everyone to discover you through search and return to your site repeatedly, you may be missing large parts of that journey.

A multi-channel approach creates more opportunities to meet buyers where they are already spending time, while also making your marketing less dependent on any single source of traffic.

It can also give you a better picture of your audience. Different channels reveal different signals about what people engage with, what questions they are asking, and what ultimately moves them closer to a decision.

But multi-channel marketing does **not** mean being everywhere.

The real challenge is choosing the right combination of channels, keeping your positioning consistent across them, and adapting the experience to how people actually use each platform.

So how do you decide which channels deserve your time and budget, and how do you manage them without spreading your marketing team too thin?

👉 We break down the benefits of multi-channel marketing and how to build the right mix here: https://totalproductmarketing.com/blog/benefits-of-multi-channel-marketing/

The benefits of multi-channel marketing are often overlooked in the B2B world. But skipping this strategy could be costing you — here’s what you need to know.

08/17/2026

🔗 AI visibility is becoming less about how much content you publish and more about how much credibility exists around what you publish.

Traditional SEO taught us to create useful content, optimize it, earn links and improve rankings. But generative search changes the equation because AI systems are not simply deciding which page should rank first. They are synthesizing information from multiple sources and deciding which brands, people and ideas appear credible enough to include.

That makes thought leadership and earned media increasingly important parts of GEO.

If an executive is consistently quoted on the same subject, company research is referenced by respected publications, or an original framework begins appearing across multiple credible sources, those signals reinforce the association between the brand and that area of expertise.

It is not necessarily about generating more mentions either. Quality and consistency matter.

One authoritative industry placement can carry more weight than dozens of low-value mentions, particularly when it reinforces a topic the company genuinely wants to be known for.

It also changes how we should think about content itself. Instead of only asking whether something is optimized or readable, marketers may increasingly need to ask:

Would a journalist quote this?
Would another expert reference it?
Would an AI system have a clear reason to cite it?

The goal is no longer just to publish expertise.

It is to build enough evidence around that expertise that others validate it too. 🎯

https://www.marketingprofs.com/articles/2026/55296/ai-visibility-thought-leadership-credibility

Discover how brands can earn more AI citations by creating quotable content, building third-party credibility, and strengthening entity recognition across trusted sources.

08/14/2026

🔍 One of the more interesting uses of AI in marketing may have nothing to do with creating more content.

It may be helping us understand what customers are already saying.

Marketers have access to an enormous amount of customer feedback through surveys, reviews, sales calls, CRM notes, search queries, Reddit discussions and other sources. The challenge is that the most valuable insight is not always explicitly stated.

A customer might tell you they want “quality” or “better service.”

But what they tell a friend could be very different: they are worried about making the wrong choice, getting hit with unexpected costs, looking bad internally, or regretting the purchase six months later.

Those underlying motivations are often where the better marketing message comes from.

This is where AI can be particularly useful. Instead of immediately asking it to write an ad or email, we can use it to analyze large amounts of customer language and look for recurring anxieties, motivations and patterns that might otherwise be easy to miss.

The creative comes afterward.

As ad platforms automate more of the targeting, bidding and delivery process, our understanding of the customer becomes an increasingly important differentiator.

So perhaps one of the better questions marketers can ask AI isn't:

“What should we say?”

It's:

“What are our customers already telling us that we're not hearing?” 👂

https://martech.org/what-customers-tell-friends-that-marketers-miss/

The strongest marketing messages address the frustrations and motivations customers rarely share directly. Here's how AI can help uncover them.

08/12/2026

🤖 AI can make marketing faster, cheaper, and easier to scale.

But none of those things automatically mean better.

As AI becomes embedded in more marketing workflows, it is easy to start making assumptions about what the technology actually brings to the table.

For example, AI-generated content might be completely free of plagiarism while still lacking genuinely original thinking. An AI system can sound remarkably knowledgeable while still producing inaccurate information. And the ability to generate five times more content does not mean your audience suddenly wants five times more content from you.

The same thinking applies to automation and personalization.

There are plenty of areas where AI can make marketers dramatically more effective, but problems tend to arise when the technology itself becomes the goal rather than the outcome it is supposed to improve.

Customers ultimately do not care whether your campaign was created with AI.

They care whether it was useful, relevant, trustworthy, and worth their attention.

That is why we think the better approach is not “Where can we use AI?”

It is “Where can AI genuinely make the marketing better?”

We broke down seven common assumptions about AI marketing that are worth questioning before they become part of your strategy, including a few that are much less obvious than they first appear.

👉 Read all seven and how to avoid them: https://totalproductmarketing.com/blog/ai-marketing-problems-to-avoid/

The cracks are starting to show. AI marketing problems are very real, and making the wrong assumptions about AI can spell serious trouble for your team.

08/11/2026

🤖 What if your organic traffic drops, but your search marketing is actually becoming more effective?

That sounds contradictory until you look at how AI is changing the way people search.

Tools like ChatGPT and Perplexity can now answer detailed questions, compare options, and help buyers narrow down their choices without requiring them to visit a website every step of the way.

That means the traditional search model of “rank → click → website visit” is starting to change.

For marketers, the goal increasingly becomes bigger than earning the click. You also want your brand, expertise, and content to influence the answer itself.

This is where Answer Engine Optimization (AEO) comes in.

Rather than focusing exclusively on short keyword phrases, AEO looks at the real questions buyers are asking and whether your content gives AI systems a clear, authoritative answer they can understand and reference.

It also changes how we should think about declining traffic.

A visitor who finally reaches your website after researching through AI may already understand their problem, know the available solutions, and be much closer to making a decision.

So the better question may no longer be:

“How much organic traffic are we generating?”

It may be:

“When buyers ask AI about the problems we solve, are we part of the answer?”

There are several practical ways marketers can improve those odds, from the types of content you create to how you structure and maintain it.

👉 We break down five key areas to focus on in our guide to Answer Engine Optimization: https://totalproductmarketing.com/blog/answer-engine-optimization/

Your audience isn’t just getting answers from Google — they’re talking to AI. Learn how Answer Engine Optimization can give your brand a competitive edge.

08/10/2026

🤖 Most companies are not building AI into their marketing stack.

They are adding AI buttons to it.

AI copy in the CMS.
AI summaries in the CRM.
AI recommendations in analytics.
AI assistants inside individual SaaS tools.

Useful? Absolutely.

Transformational? Not necessarily.

The bigger opportunity comes when AI can actually connect the systems, data, and workflows behind the scenes.

That means moving beyond isolated tools toward an environment where AI can:

• Access real-time enterprise data
• Share context across systems
• Work across multiple applications
• Make decisions based on business rules
• Coordinate with other AI agents
• Operate within built-in governance and security controls

But there is a catch.

AI is only as useful as the infrastructure underneath it.

Fragmented data, outdated systems, poor taxonomy, and inconsistent information do not disappear when you add Gen AI.

If anything, AI can amplify those problems.

So the real enterprise AI question is not:

“Where can we add AI?”

It is:

“Do our systems, data, and workflows allow AI to actually work across the business?”

The future of AI-powered marketing may be less about having more AI tools and more about making AI the connective tissue between the tools you already have. 🔗

https://www.cmswire.com/digital-experience/what-it-actually-takes-to-build-gen-ai-into-your-enterprise-marketing-stack/

Gen AI bolted onto an enterprise marketing stack delivers pilot results. Built into it, it delivers transformation.

08/07/2026

📩 Most B2B cold emails fail because they sound like cold emails.

Not because the offer is bad.
Not because the targeting is wrong.
But because the message feels templated before the reader even gets to the point.

A useful test: read the email out loud.

If you would never actually say it that way in a conversation, rewrite it.

Strong cold outreach usually does a few things well:

• Keeps the message short, ideally under 100 words
• Leads with one highly specific, relevant detail
• Avoids long company intros and feature dumps
• Makes one clear ask
• Keeps that ask low-friction

One concept I especially liked was the idea of finding the “undeniable thing.”

That is the specific detail that makes the recipient immediately understand why the email is relevant to them.

It could be a funding amount, location, recent company change, mutual connection, or another concrete fact that proves the outreach was not completely generic.

The same applies to follow-ups.

“Just following up…” immediately feels like a sequence.

A natural, short check-in often feels much more human.

The goal of a cold email is not always to sell the meeting.

Sometimes, it is simply to earn the reply. 👌

https://www.marketingprofs.com/articles/2026/55155/b2b-cold-email-fixes

Learn how to improve B2B cold email reply rates with the read-aloud test, the 100-word rule, stronger personalization, and more effective follow-up emails.

08/03/2026

GEO keeps getting framed as the next marketing problem.

But marketing cannot solve it alone.

AI platforms do not form their understanding of a company from one optimized webpage. They pull signals from across the entire digital ecosystem, including product pages, executive commentary, news coverage, customer reviews, analyst reports and third-party discussions.

That means inconsistent messaging across departments is no longer just an internal brand issue. It can directly influence how AI describes your company to potential buyers.

A business might want to be known for one capability, while its website, sales materials and media coverage each tell a slightly different story. AI then has to decide which version is most credible.

This changes the question from:

“Can people find us?”

To:

“When AI finds us, does it understand us correctly?”

Strong GEO therefore requires more than content optimization. It requires alignment between marketing, communications, product, sales and leadership around a clear, credible and consistent company narrative.

GEO may sit closest to marketing, but the underlying challenge is organizational.

And that is exactly why it matters.

https://www.thedrum.com/opinion/geo-isn-t-a-marketing-problem-and-that-s-exactly-the-problem

Generative engine optimization looks like a marketing job. Fiona McKenzie of Marketbridge argues it is really a test of whether a business tells one consistent story, or several conflicting ones, across its silos.

07/27/2026

AI search has a trust problem. ⚠️

People are using AI tools because they're fast, convenient, and increasingly built into the way we search for information. But usage does not automatically mean trust.

That is the challenge marketers need to pay attention to.

A brand can show up in an AI-generated answer and still fail to earn confidence if the information is vague, outdated, inconsistent, or hard to verify. Visibility alone is not enough anymore.

This changes the way we need to think about search. 🤖

In traditional SEO, the goal was often to rank, earn the click, and bring the visitor back to your owned experience. With AI search, that journey can look very different. A buyer may form an impression of your brand through an AI summary before they ever visit your website.

That means the source material matters more.

Your website content, third-party mentions, reviews, structured data, product information, thought leadership, and brand messaging all contribute to how clearly AI systems can understand and represent you.

If those signals are inconsistent, AI search can expose that weakness quickly.

For marketers, the opportunity is not just to optimize for being found. It is to optimize for being believed. 🎯

That means creating content that is clear, credible, specific, and easy to verify. It means keeping owned content up to date, strengthening external proof points, and making sure the brand story is consistent across the places buyers and AI systems look for answers.

AI search may change where discovery happens.

But trust still has to be earned.

The brands that win will not just be the ones that appear in more AI answers. They will be the ones buyers can confidently validate after the answer appears.

https://martech.org/can-marketers-navigate-ai-searchs-trust-cliff/

New research reveals a growing gap between how often people use AI search and how much they trust it.

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