How to apply April Dunford’s positioning framework to deep tech and complex B2B technology.

By Gabe Green on 10th August 2026

Deep B2B tech companies don’t struggle with innovation.

They struggle with clarity and articulation.

When your product involves AI, hardware acceleration, inference optimisation, advanced architectures or new technology altogether, it’s easy to default to explaining how it works – not why it matters.

It’s easy for your messaging to become:

overly technical
inward‑looking
or impressive… but unclear

April Dunford’s B2B positioning framework is especially powerful for deep tech and smart technology companies, because it forces simplification without dumbing things down.

Positioning at this level isn’t about dumbing things down.

It’s about making deliberate choices so the right buyers immediately understand:

what your technology actually does
who it’s for
why it exists (its inevitable role)
and why it’s a better option than what they’re doing today

This article walks through the 5-step positioning process, applied to a complex B2B technology like AI and machine learning products, in a way buyers can actually understand.

The 5-step framework (quick refresher)

Competitive alternatives (what else buyers would do)
Unique attributes (your distinctive capabilities)
Value (what those capabilities enable)
Ideal customer profile (perfect-fit buyers)
Market category (the context buyers use to understand you)

For complex B2B technology, the order matters even more than usual. Skipping steps is how you end up with messaging that engineers love and buyers don’t.

Step 1: Identify your real competitive alternatives

Deep tech companies often get this wrong by assuming:

“Our competitors are other advanced technology platforms.”

In reality, buyers usually default to simpler or brute‑force alternatives, not more sophisticated ones.

The common deep tech mistakes at this stage are:

Listing only companies with similar technology
Ignoring “do nothing” or scale-through-spend options
Underestimating how long buyers will tolerate inefficiency
Over-predicting the trend of an adoption curve

A complex B2B tech example

Let’s imagine a complex AI product that optimises performance, cost or efficiency in production environments.

Real competitive alternatives might include:

Scaling infrastructure (more compute, more hardware, more cloud spend)
Accepting inefficiencies as the cost of growth
Internal tooling or manual optimisation attempts
Generic platforms not built for this specific problem
Delaying change because current systems “work well enough”

Why this matters:

Positioning only works when framed against what buyers are actually replacing, not what you wish they were comparing you to.

Step 2: Identify your unique attributes that customers actually care about

This is not a place for:

algorithms
architectures
internal terminology
or how clever the technology is

Positioning attributes are capabilities as experienced by the buyer, not explanations of how the system works.

A practical filter for deep tech teams

If the attribute:

requires a technical deep dive to understand
doesn’t change the buyer’s day‑to‑day reality

…it’s probably not a positioning attribute.

A complex B2B tech example (continued)

Instead of:

“Proprietary optimisation engine”
“Advanced model orchestration”
“Next‑gen AI architecture”

You might land on:

Improves performance without requiring major system changes
Works with existing models and infrastructure
Reduces operational cost at scale
Deploys without disrupting production environments

These are capability‑level attributes, not technical descriptions.

Step 3: Translate attributes into value (this is non‑negotiable for complex technology)

Attributes alone don’t persuade buyers – especially in deep tech.

Value must be explicit, commercial and often emotional, particularly when risk and cost are involved.

A simple translation still applies:

Attribute → Functional value → Business value → Emotive value

This is the complex B2B tech example continued

Attribute	Functional value	Business value	Emotive value
Works with existing systems	No re-platforming required	Faster time to value	Relief and reduced risk
Performance optimisation	Lower latency or higher throughput	Improved customer experience	Confidence in delivery
Cost efficiency at scale	Reduced compute usage	Lower operating costs	Control over spend

This is the step where complex technology becomes commercially legible and emotive.

Step 4: Define who this is actually for (and be brave about exclusion)

“Anyone using AI” is not an ICP.

It’s a refusal to choose.

Deep tech products are rarely valuable to everyone. They’re valuable to people with:

specific scale problems
specific technical maturity
specific constraints

Deep tech ICP prompts

Is AI already in production or still experimental?
Does performance or cost materially impact the business?
Are infrastructure constraints a strategic issue?
Do teams have the capability to adopt advanced tools?

Deep tech example ICP

Companies running AI models in production environments
Performance, latency or cost issues are becoming business‑critical
Existing solutions involve over‑provisioning or inefficiency
Technical teams are sophisticated but resource‑constrained

Being specific here increases relevance and you’ll have more chance of resonating with your buyers faster.

Step 5: Choose the right market category to sit in

Market category isn’t branding.

It’s the mental shortcut buyers use to make sense of what you are.

Deep tech companies often try to invent categories to reflect novelty. Buyers usually prefer familiar anchors.

Two key rules for complex technology categorisation

If the category isn’t recognised, expect longer sales cycles and understand that you must generate demand
Anchor first, then differentiate and delight

An example of this in action

Instead of:

“Next-generation AI optimisation platform”

You might anchor to:

“AI performance optimisation software”

“Infrastructure optimisation for AI in production”

Clear first. Clever later.

Once buyers understand what kind of thing you are, you can then explain why you’re different.

If you start with ‘different’, you get ignored by buyers because it doesn’t feel relevant or applicable to them now.

Pulling it all together (what changes in the real world)

When complex technology is positioned correctly:

Conversations move away from technical explanations and towards outcomes
Non‑technical stakeholders stay engaged
Sales cycles shorten because value is easier to articulate internally
Your product sounds premium for the right reasons

Positioning doesn’t make your technology simpler.

It makes the decision to buy it simpler.

Positioning for deep tech isn’t about showcasing how advanced your technology is – it’s about making its value immediately obvious to the people who decide whether to invest in it. When complex AI and smart technology products are positioned around clear outcomes, realistic alternatives and familiar context, they become easier to understand, easier to justify internally and far more compelling commercially. Get the positioning right, and your technology stops being admired from a distance and starts being purchased and adopted with confidence.