Technology and software

Brand design for artificial intelligence and data companies

The deeper the technology, the more simply buyers need it explained.

Buyers don't need to understand the model. They need to know what it does for them and how far to trust it. Sinh Vũ helps your technology be told through concrete work, not through jargon and the industry's familiar imagery.

A set of sample materials for an artificial intelligence and data company: a product landing page, a demo, technical documentation and an investor deck
Quick answer01

What brand does an artificial intelligence company need to be trusted?

Three things: one sentence on what the technology does for whom, a demo that shows results and states its limits, and a set of technical documents that are easy to read for the people who evaluate you. In an industry full of overstatement, being accurate and clear about limits is what earns trust.

  1. One sentence on what the technology does

    State what the customer does by hand today and how the product changes it, without model names or jargon.

  2. An honest demo

    Show real results on an example close to the customer, including where the product can't yet do the job.

  3. Readable technical documents

    How it works, what data it needs and how results are measured, written for both engineers and decision makers.

Business types02

Three kinds of products, three problems

All of them talk about data and artificial intelligence, but the buyers differ, so the brand has to tell a different story.

Artificial intelligence products

Their customersBusinesses that want a ready-made product for one specific job, such as customer care or reading documents.

Brand challengeShow that the product does that one job better than the current way, and state clearly where a person still needs to check.

Data analytics platforms

Their customersExecutives who need to see numbers to decide, and engineering teams who need to work on the same platform.

Brand challengeTurn the abstract into something easy to grasp: dashboards, real decision examples and an interface that doesn't overwhelm.

Machine learning solutions

Their customersBusinesses that need a solution built around their own data and processes.

Brand challengeShow clients the team can build what fits them, through a clear way of working and a trial on their real data.

Pain points03

Four pain points specific to artificial intelligence companies

These are the places where artificial intelligence companies tend to lose clients, even when the technology is genuinely good.

02

A landing page full of jargon

Accuracy, models, performance: buyers finish reading and still don't know whether it fits their work.

Open with what the customer does every day and how the product changes it; keep the jargon for the page meant for engineers.

Start from this problem
Customer journey04

At which stage do artificial intelligence companies lose the most clients?

At the Trial stage, the pilot run on the client's data. The client is interested but wary of risk, so how the trial results are presented decides whether they go on.

Where customers are most often lostTrial
Do this now
  1. Agree with the client from the start on what counts as a successful trial and how it will be measured.
  2. Present the trial results in one short document: what was done, what came out, where it fell short.
  3. State clearly which parts a person still needs to check, so clients are reassured the technology isn't oversold.
Touchpoints05

Five touchpoints to do first

Touchpoints are the places where clients and investors look at, read or try the product. You don't need to do everything at once. These five decide whether the technology gets understood.

  1. Landing page

    The place where buyers decide to read on or close the page, so it has to say what the product does in a few sentences.

  2. Demo

    The moment buyers see the product run and decide whether to believe it.

  3. Technical documentation

    Evaluators read it closely to check the promises, so it has to be clear and match the landing page.

  4. Investor materials

    Investors need to understand the technology just enough, and see that the team knows what it is selling.

  5. Product dashboard

    Where users meet the technology's results every day, so how the numbers are laid out decides whether they trust or doubt.

Roadmap06

Where Sinh Vũ suggests starting

Listed in the order to do them. A new company stops at step two or three; a company that already has clients and is raising funds goes further.

  1. Brand strategy and positioning consulting

    Settle what the technology does for whom, and what sets the company apart from others in the field.

  2. Building brand voice

    A way of telling the technology through concrete work, consistent across the website, demo and documents.

  3. Brand website design

    A landing page and solution pages by customer industry.

  4. Corporate capability profile design

    Readable technical documents and investor materials, told from one core story.

  5. Sales and marketing collateral design

    A template for presenting trial results and case studies for the sales team.

Projects07

Projects closest to artificial intelligence companies

Sinh Vũ has not published an artificial intelligence or data analytics project. The three below are closest because they share one problem: hard-to-grasp technology that needs to be trusted.

Further reading08

More on artificial intelligence and data

Free toolTouchpoint map for this business modelSee the five stages customers pass through, where they drop off most, then rate the five touchpoints to fix first.Open the tool Free toolFull logo file setFrom one logo, export the whole set: website icon, Zalo and Facebook avatars, white version, black version, email signature logo, share image.Open the tool
FAQ09

Frequently asked questions

Speak in concrete work instead of big promises. Show real results on one example, state the limits, and don't use the imagery that everyone in the field uses.

What the product does and for whom, a demo or a results excerpt, how it works at an understandable level, a page for engineers and a way to get in touch to try it. Keep the jargon for later.

Investors need to understand the technology just enough to see what is different and hard to copy. Include one page that explains the technology through an example, and keep the other pages on customers and the market.

Only if you state what data they were measured on and under what conditions. A number without context makes buyers doubt more than it makes them believe.

Start from the decision the user has to make, then choose the numbers that serve that decision. Each screen answers one question, and every number should have a clear unit and time.

Keep it lean: a sentence that says what the product does, a landing page with a demo and a short document for investors. Do case studies once clients are actually using it.

Tell Sinh Vũ about your technology

A few lines about the product, the buyers and where they don't yet understand is enough. Sinh Vũ reads it and replies within one working day.