DEV Community: FRANKY FRANKYHOO

I built for a keyword Google Trends says doesn't exist

FRANKY FRANKYHOO — Mon, 02 Nov 2026 04:31:42 +0000

Disclosure: I work on FORMAT, a tool that turns interior renders into short videos. The keyword data and Search Console numbers below come from our own accounts. No affiliate links.

I work on FORMAT, a small tool that turns one interior render into a 15-second video. Before writing a line of marketing copy, I did what every SEO guide tells you to do: keyword research.

The result was the most useful negative result I've had.

Every interior-specific keyword measured zero

I used Google Trends (US, 12 months) with gpts as a fixed benchmark, because absolute volume was not available to me. Relative to the benchmark:

Phrase	Relative interest
`photo to video`	64.8
`image to video ai`	58
`gpts` (benchmark)	13.2
`real estate video`	31.2, falling to ~4 by the time I checked
`room to video`	51.5 average, but collapsing week over week
`interior design video`	0
`interior design video generator`	0
`interior design video maker`	0
`architectural visualization`	0
`interior walkthrough`	0
`3d render video ai`	0

Every phrase that described our actual customer returned zero. The only phrases with volume were generic: "photo to video", "image to video".

That felt wrong, so I checked a competitor. Lupa AI is a paid product in the same niche. Its brand search volume was also zero. If people were finding tools like ours through Google, a paid product with customers would have some branded search. It had none. Its search results page was seven TikTok, Instagram and YouTube links and two official pages.

The conclusion: for this category, demand is stimulated, not pre-existing. People see a video on social media, learn the category exists, then look for a tool. They do not wake up and Google "interior design video generator".

What we changed

We retargeted the main page from the natural-but-dead phrase ("AI interior video generator") to the phrase with actual demand ("photo to video"), while keeping "interior design" as the qualifier. Same visitor, same product, better-matched entry point.

We kept the use-case guides — render-to-video, Reels, client presentations — but stopped pretending they would bring search traffic. They exist to answer questions for people who already arrived, and to give AI answer engines something specific to quote.

The part nobody warns you about: AI answer engines

I asked ChatGPT, in a fresh session, two kinds of questions.

Branded: "What is FORMAT by VIXL?" It answered accurately, including the fixed five-move camera path and the 15-second length.

Category: "Best AI tool to turn an interior render into a short video?" FORMAT did not appear at all. It recommended Kling, Runway, Luma, Veo, Seedance, Pika and Firefly.

When I asked it to explain why, the answer was blunt: the information about FORMAT came almost entirely from FORMAT's own website, and that does not count as independent evidence. LLMs recommend what third parties recommend.

That changed our roadmap more than any keyword spreadsheet did. We stopped treating our own marketing pages as the main lever and started treating them as the thing a third party can point at.

The numbers after three months

Real Search Console numbers, not a growth screenshot:

93 impressions, 11 clicks in three months.
Every query was branded (vixl, vixl ai, and some misspellings).
Zero non-brand impressions on any FORMAT-related phrase.
9 of 53 pages indexed. Most of the rest were "discovered, not indexed".

None of that is alarming for a three-month-old site with no links. It is also not a strategy. Impressions follow indexing, indexing follows links and crawl demand, and we had neither. Publishing more pages would have added to a queue, not to traffic.

Five things I'd tell someone starting today

Check that the demand exists before you check difficulty. I nearly built for a term with a low difficulty score and no searches. Low KD on a zero-volume phrase is a trap: it is easy to rank and worthless to rank.
A competitor with zero branded search is information. It usually means distribution is not search. Look at where their traffic actually comes from.
For stimulated demand, the product has to be visible where the stimulation happens. That means social, creators, communities — not a comparison table on your own domain.
GEO is a third-party problem. Your own page can be accurate, complete, and still ignored by LLMs. Independent reviews, directories and community posts are what get quoted.
Narrow tools win on trust, not features. Our best-performing content was honest about limits — fixed camera path, 15 seconds, possible drift. The pages that said "it just works" converted worse than the ones that told people when not to use it.

What I'm doing next

Directories and community mentions, in that order, with a strict rule: only where the product is actually relevant. Then a creator or two in the interior visualization niche, because that is where this category is discovered.

If you are building a tool for a professional niche and your keyword research comes back empty, I would not immediately conclude you picked the wrong niche. I would conclude that Google is the wrong front door — and go find the right one.

I work on FORMAT (vixl.art). No affiliate links. The keyword data and Search Console numbers are from our own account.

Turning an interior render into a video: the 7 checks that separate a usable clip from a pretty demo

FRANKY FRANKYHOO — Sun, 01 Nov 2026 07:34:11 +0000

Disclosure: I work on FORMAT (vixl.art), a tool that turns interior renders into short videos. I'll mention it once, near the end, and I'll also say where generic models are the better choice. Everything else in this post is about how to evaluate any tool, including ours.

Most interior visualization teams already have good stills. V-Ray, Corona, Enscape, D5, Lumion — the render is done, approved, and sitting in a folder.

Then someone asks: "Can we get this as a reel?"

That request is where things get expensive. Animating a camera path in the 3D scene means reopening the file, keyframing, and rendering 360–450 frames for a 15-second clip. AI image-to-video promises to skip that. Sometimes it does. Sometimes it returns a beautiful clip where the sofa has quietly changed shape and the doorway leads somewhere that doesn't exist.

The difference between those two outcomes is not the model's demo reel. It's whether the tool was built for this specific job. Here are the checks I'd use to tell the two apart, and a protocol to run them on your own renders.

The failure modes that matter

Every image-to-video model can produce an impressive 5-second shot of a landscape. Interiors are harder because the viewer knows what "correct" looks like: walls are straight, materials are consistent, furniture doesn't move on its own.

In practice, the failures cluster into five groups:

Furniture drift and resizing. A chair grows, a table shifts 10 cm, a lamp changes shape. Individually small; together they make the room feel wrong.
Geometry invented beyond the frame. Point the camera at a doorway and the model fills the unseen room with whatever it likes. This is why "one continuous walkthrough" rarely works from a single still.
Thin-structure breakdown. Chair legs, cables, rails, and window mullions are the first things to melt.
Reflections and glazing. Mirrors and glass are approximated frame by frame rather than ray-traced, so they shimmer.
Camera motion that's too fast. A fast orbit reveals corner detail the model never saw. Slow, human-scale moves hold up far better.

If a tool's marketing shows a sweeping orbit through a whole apartment, that's a signal to test the hard cases, not to trust the demo.

The 7 checks

1. Can it start from one still, with no prompt?

Prompt-free is not a gimmick. If the tool requires you to describe the camera move, you've moved the skill bottleneck from 3D software to prompt writing — and the result still varies per attempt. Ask: can a designer upload a render and get a usable clip without writing anything?

2. Is the camera path predictable?

Two different questions get mixed up here:

Controllable — you can request a specific move (dolly in, truck left).
Predictable — the same input produces the same kind of move every time.

Controllable is great for a music video. Predictable is what lets a studio hand a render to a junior and get consistent output across a 40-unit project. Decide which one you actually need.

3. Does the design survive?

Score this on a 1–5 scale against the original render: layout, materials, lighting direction, window position, furniture proportions. Do it side by side, not from memory. This is the check that decides whether the clip can go to a client.

4. What do you actually get out?

Four numbers:

Length — 4s, 15s, 30s?
Resolution — 720p, 1080p, 4K?
Aspect ratio — 16:9 for the website, 9:16 for reels?
Extras — close-ups, stills, or just one clip?

A 15-second 720p clip is often the right trade-off for social; it is not the right output for a showroom screen. Match the spec to the destination before you compare prices.

5. Can you get more than one shot from one render?

A single clip per render means a multi-room walkthrough is several uploads plus an edit. Some tools return extra angles or detail shots alongside the main clip, which cuts the number of generations per deliverable. Count generations per finished deliverable, not per clip.

6. What does a usable clip cost?

This is where per-second pricing misleads. If you generate four times before one clip is client-ready, the real cost is 4× the listed price. Track:

cost per usable clip = (generations ÷ usable clips) × price per generation

Run that number for two or three tools before you commit to a subscription.

7. Does it fit the workflow you already have?

Export format, watermark, how files are named, whether there's an API, whether the output is silent so you can add your own music. Small things that decide whether the tool survives week two.

A 30-minute test protocol

Pick three of your own renders — not stock images:

Render	Why
A wide living room with a clear focal point	Tests overall motion and composition
A detail shot (kitchen counter, bathroom)	Tests material fidelity and thin structures
A space with glass, mirrors, or a doorway	Tests the known weak spots

Then, for each tool:

Upload the same three images with the same settings.
Generate once per image. Do not retry — you're measuring first-attempt quality, which is what a busy designer gets.
Score each clip 1–5 on design fidelity (check 3).
Count how many of the three you'd actually send to a client.
Multiply generation price by attempts ÷ usable clips.

Six clips per tool is enough to separate "demo" from "tool". It is not a benchmark, and it shouldn't be — the point is whether your renders survive.

When a general model is the better choice

To be fair to the other side of this:

You need a specific, unusual camera move, or several motion ideas to choose from.
You're shooting something other than interiors — character work, stylized worlds, product macro.
You need longer single takes (30s+) or higher-end formats.
You want to iterate on prompts and treat the first result as a draft.

In those cases a general model such as Kling, Runway, Luma, or Veo is the right call. The trade-off is setup and variance, not quality.

What we built, and why

FORMAT sits on the other side of that trade-off. One interior render goes in; a 15-second video plus four close-up stills come out, at 720p with an optional 2K upgrade, in 9:16 or 16:9. There is no prompt field and no camera path to set: the same five moves run every time, in the same order. Under the hood it runs ByteDance's Seedance 2.0 Mini model inside a fixed pipeline — the model isn't exposed for free-form prompting, which is deliberate.

That design is worse for someone who wants to direct a specific shot, and better for a studio that needs the same output across forty renders. Both answers are legitimate; they're different products.

The checklist, condensed

[ ] Accepts one still, no prompt required
[ ] Same input → same kind of camera move
[ ] Design fidelity scored 1–5 vs the original render
[ ] Outputs: length / resolution / aspect ratio / extras
[ ] Generations per finished deliverable counted
[ ] Cost per USABLE clip, not per generation
[ ] Fits the existing export + delivery workflow

Run it on three of your own renders before you buy anything. The tool that survives is usually not the one with the best demo reel.