AI search visibility, run for you entirely.
2 Steps Ahead takes AI search visibility off your hands. AI Search Visibility as a Service for B2B tech and software companies.
G2
LinkedIn
Reddit
Wikipedia
ChatGPT 
Claude 
Gemini 
Perplexity 
Copilot 
Grok 
Meta AI 
AI Overviews Assistants answer from pages they can crawl, read and attribute. Being quotable is what decides whether they name you, and that is a different job from ranking tenth.
ChatGPT For a company of around 200 people, these are the tools I would shortlist. Prices are indicative.
- Best overallYour brand Flowdesk Work OS From €9 per user/month Plans, tasks and approvals in one place, with SSO and an open API. A strong fit once teams outgrow spreadsheets. Best for: companies of 200 to 2,000 people.
- Best for PMOs Boardwise Project Suite From €12 per user/month Mature project and portfolio management with detailed reporting. Best for: PMOs and large programmes.
- Best for quick starts Planora Teams From €7 per user/month Simple boards and timelines that are quick to roll out. Best for: small teams and quick starts.
Run a two-week pilot with one team before you decide.
Illustration with fictional vendors. Real answers differ per model, market and day.
Buyers describe a problem, not a vendor
More software buyers now ask an LLM before they open a search engine or a vendor site. The prompt describes a team, a size and a problem, and the answer is a shortlist of three or four names, not ten blue links. The same question gets a different answer in each model, and the vendors named are the ones it can find, read and corroborate.
Every prompt we work on is one a real buyer would type. Switch the demo between the answer today and the answer once your product pages, comparison content and third-party mentions line up.
“Before we started optimising for AI search, it barely brought in any leads. Nine months later it brings in close to a third of our qualified leads each month, and five times as many meetings per month.”
Sander Roose Founder & CEO, Omnia Retail Omnia Retail went from 2% to 29% of its monthly qualified leads via AI search in nine months
Of all qualified inbound leads and contact requests Omnia Retail receives in a month, the share arriving through LLMs and AI search rose from a 2% baseline to 29% nine months later. Measured plainly: a required "how did you hear about us" question on every contact form, not a modelled attribution guess.
The share is only half of it. Over the same nine months, the number of meetings booked through AI search each month grew fivefold: more of the pipeline, and more pipeline in absolute terms.
Buyers pick their vendors in AI chatbots
Buyers ask an assistant which software to consider, read its comparison and take its shortlist into their decision. Whether you are on that list decides whether you get the lead at all.
Of B2B software buyers now start their research in an AI chatbot more often than in Google.
G2, survey of 1,076 B2B software buyers, Apr 2026Of B2B buyers who use AI at work say it shaped the shortlist of vendors they considered.
Semrush, survey of 643 US B2B professionals, Mar–Apr 2026Of those buyers say AI influenced their final vendor decision, and 97% say it helped them find vendors they did not know.
Semrush, survey of 643 US B2B professionals, Mar–Apr 2026Of software buyers ended up choosing a different vendor than they had planned, because an AI chatbot recommended it.
G2, survey of 1,076 B2B software buyers, Apr 2026These are other people's numbers, with the sample named on each, and they describe what buyers say they do. That is why we measure every client against their own baseline, and ask every new lead how they heard about you. The full breakdown, with every source.
Six things, done properly
- 01
Prompt research
The questions your buyers actually ask an assistant rarely match the keywords in a content plan. We pull them from tracked-prompt data, sales call transcripts, support tickets and the communities where people compare vendors out loud.
- 02
Citation-ready content
Being the best answer is not the same as being the cited one. We decide what onsite and offsite content has to exist, and in what shape, for an assistant to quote it as the consensus view, then check that against what it already says about you: what gets included, what gets left out, and what closes the gap.
- 03
Technical AEO
Structured data, entity clarity, internal linking, crawlability, page architecture: the unglamorous work that decides whether any of the above is even reachable. Most sites do not need more content, they need the content they have to be readable.
- 04
Citation tracking and analytics
A tracking dashboard is a data source, not a strategy. We turn what it shows into direction, and where a priority prompt needs a real, logged-in check instead of a modelled guess, we run it by hand.
- 05
Offsite AEO
Not every mention carries the same weight with an assistant. We map which publishers, communities and citations actually move your prompts, and put the effort where an assistant is already listening, not where it is easiest to get published.
- 06
AI search advertising
OptionalPaid placement now sits inside the answer itself, alongside the sources an assistant names. As a module on top of either package, we set it up, buy it and measure it against the same frozen baseline as the organic work, so the two are never left competing for credit.
One page says it. That is a claim.
Nine independent places say the same thing about you: G2, Trustpilot, Wikipedia, Reddit, YouTube, LinkedIn, Substack, Medium, and the listicles and reviews written about you elsewhere. An assistant weighs corroboration, not confidence, and a fact repeated only on your own site is the easiest thing for a model to discount.
This is what our off-site authority work is built to earn, on every package: real placements on the third-party sites assistants actually check, not more copy on the site you already control.
G2 
Trustpilot 
Wikipedia 
Reddit 
YouTube 
LinkedIn 
Substack 
Medium Boring principles, applied without exception
Measure first, write second
Every recommendation starts with a number, and we tell you when the number says do nothing.
We move fast, you sign off
We work independently between check-ins so nothing waits on us, but nothing goes live, gets sent or gets spent without your permission first.
You own the work
Your repositories, your properties, your data. Scripts and documentation are handed over, so nothing here depends on us staying.
Where we are useful, and where we are not
You are a B2B tech or software company. Competitors get named in AI answers and you do not, and nobody on your team has time to work out why.
You are pre-product-market-fit or a local business.
Two steps ahead starts with one honest audit
Tell us the domain and what you think the problem is. You get back what the data says, including the parts that disagree with you.
Get your products recommended by LLMs.
2 Steps Ahead takes AI search visibility off your hands. AI Search Visibility as a Service for product brands and retailers.
YouTube
Reviews
ChatGPT Claude Gemini Perplexity Copilot Grok Meta AI AI Overviews Assistants answer from pages they can crawl, read and attribute. Being quotable is what decides whether they name you, and that is a different job from ranking tenth.
ChatGPT For a week of hiking in the Austrian Alps, these are the picks I would shortlist. Prices are indicative.
-
Best overallYour brand
Alpenfox Summit 40L hiking pack
€139
Built for multi-day Alpine routes, with a ventilated back panel and a rain cover included. My first choice for a week on the trail.
Best for: hut-to-hut and multi-day hikes.
-
Best for day hikes
Nordkamp Alpine 38L daypack
€149
A comfortable daypack with a ventilated back and a rain cover. Solid if you only hike for the day.
Best for: day hikes from one base.
-
Best for rough trails
Ridgeline Trail GTX hiking boots
Around €189
Waterproof boots with good ankle support for rocky Alpine paths.
Best for: rocky trails and wet weather.
Check the weather forecast before you pack, mountain conditions change quickly.
Illustration with fictional brands; photos by Unsplash. Real answers differ per model, market and day.
Shoppers describe a need, not a product
More shoppers now ask an LLM what to buy instead of typing a search. The prompt describes a need, and the answer is a shortlist of three or four products and shops. The same question gets a different answer in each model, and the products named are the ones it can find, read and corroborate.
Every prompt we work on is one a real shopper would type. Switch the demo between the answer today and the answer once your feeds, product pages and third-party mentions line up.
Case in progress SmaakGenot: getting makers and products recommended by LLMs
SmaakGenot.nl is a Dutch food marketplace with shops of local producers: cheese, poultry, olive oil and more. We started in October 2026, with the aim that makers and their products get recommended for prompts like these. We share the baseline and the results here as they come in.
Products from the shops we work on - You“Where can I buy farm cheese online?”
- You“Best meat straight from the farmer”
Fewer visits, each one worth more
A shopper who arrives from an assistant has already described what they need and been given a shortlist. They land further down the funnel, and it shows in what they do next.
Of American consumers say they use ChatGPT for shopping. In the UK it is 60%, in Canada 64% and in Australia 70%.
Omnisend / Cint, 4,000 consumers in four countries, Jan 2026Of American shoppers say ChatGPT gives better product recommendations than search engines.
Omnisend / Cint, Jan 2026Growth in AI-referred traffic to US retail sites in May 2026, year over year, converting 54% better than non-AI traffic.
Adobe Analytics, via Digital Commerce 360, May 2026Revenue per visit from AI-referred traffic versus all other traffic, converting 60% better and bouncing 33% less.
Adobe Analytics, US retail, July 2026, via Digital Commerce 360These are other people’s numbers, with the sample named on each, and the Omnisend survey was commissioned by a vendor. Not every study agrees: one 2026 study of 973 webshops found ChatGPT traffic converting worse than Google organic. That is exactly why we measure against a baseline instead of assuming.
Six things, done properly
- 01
Prompt research
Shoppers describe a need, not a product. We pick the prompts that matter for your assortment and markets, from keyword data, prompt data and what your competitors are named for, and we track many more than we work on.
- 02
Feeds and catalogs
We check what the feed says against the prompts that matter, and tell you which attributes to enrich: who the product is for, sizes and fit, materials, use cases.
- 03
Product pages and listings
We rewrite titles, descriptions and category pages around the questions buyers ask, for example whether a shoe suits narrow or wide feet, and fix the technical side so it can be read and attributed.
- 04
Third-party mentions
We create the content ourselves, together with you: posts, answers, review and listicle pitches and video briefs, written from your real facts and tone and approved by you before anything goes live. Then we place it on Reddit, YouTube, social, listicles and review sites, and for brands that want to go faster, as paid placements on sites LLMs cite often.
- 05
Tracking and reporting
A dashboard against a frozen baseline per market: which prompts name you, at what position, which competitors are named instead and which sources the answers draw on. Where a priority prompt needs a real check, we run it by hand.
- 06
Agentic readiness
NextAI agents that shop on behalf of people are next. They favour merchants with a complete catalog and recognisable brands, so the same layers apply, and we keep them in shape as agents roll out.
One page says it. That is a claim.
Nine independent places say the same thing about you: G2, Trustpilot, Wikipedia, Reddit, YouTube, LinkedIn, Substack, Medium, and the listicles and reviews written about you elsewhere. An assistant weighs corroboration, not confidence, and a fact repeated only on your own site is the easiest thing for a model to discount.
This is what our off-site authority work is built to earn, on every package: real placements on the third-party sites assistants actually check, not more copy on the site you already control.
G2 Trustpilot Wikipedia Reddit YouTube LinkedIn Substack Medium Boring principles, applied without exception
Measure first, write second
Every recommendation starts with a number, and we tell you when the number says do nothing.
We move fast, you sign off
We work independently between check-ins so nothing waits on us, but nothing goes live, gets sent or gets spent without your permission first.
You own the work
Your repositories, your properties, your data. Scripts and documentation are handed over, so nothing here depends on us staying.
Where we are useful, and where we are not
You sell products through your own shop and marketplaces. Competitors get named when shoppers ask an LLM what to buy and you do not, and nobody on your team has time to work out why.
You are pre-product-market-fit or a local business.
Two steps ahead starts with one honest audit
Tell us the domain and what you think the problem is. You get back what the data says, including the parts that disagree with you.