Solutions
One operated loop, translated into your language. Pick the page that speaks to your role or your market and see exactly what SkuLift changes for you — in B2B and in D2C.
Who is SkuLift for?
SkuLift is for any team whose customers now ask AI engines before buying — CMOs, CEOs, SEO teams, e-commerce leaders, and whole sectors. It works for B2B pipelines and D2C catalogs alike.
Generative engines — ChatGPT, Perplexity, Gemini, Claude — now answer the questions your buyers used to type into Google. Whether you sell a contract or a cart, the same problem applies: are you the answer the AI cites, or the one it never mentions?
SkuLift is deliberately audience-agnostic. A B2B software company worries about category and comparison queries that feed pipeline; a D2C brand worries about product and shopping queries that feed demand. The measurement, the loop and the maturity ladder are identical — only the data and the wording change. That is why every Solutions page below covers both sales models explicitly.
The role pages translate the offer for the person reading: a CMO running a control tower, a CEO treating AI authority as a strategic asset, an SEO team extending its craft into AEO and GEO, an e-commerce leader turning a catalog into citable assets. The sector pages translate it for a market: the typical queries of retail, B2B SaaS, financial services, travel and hospitality, or manufacturing, and the trajectory each can realistically follow.
Underneath, nothing changes. We measure your share of voice across AI engines, analyze where and why you are cited or ignored, recommend the highest-leverage moves, execute them with a human gate, and re-measure to prove the lift. Pick your entry point; the method that follows is the one documented on our methodology, AEO and GEO pages.
The reason we split the family into roles and sectors is that the same offer needs two different doors. A function leader wants to know what changes for their team and their numbers; a buyer in a specific market wants to recognize their own queries, their own data, and a trajectory that looks like theirs. Both doors lead to the same operated loop, so it does not matter which one you walk through first.
And because generative engines now answer in their own words rather than handing back a list of blue links, presence is no longer a binary of "ranked or not". You can be mentioned favorably, mentioned with the wrong framing, or omitted while a competitor is named as the default. Every page in this family treats that nuance directly, with measurement that separates being present from being recommended.
The same loop also explains why a single audit is never enough. Engines update, competitors publish, and your own catalog or content changes; a position that looked strong last quarter can quietly erode. That is why SkuLift is operated rather than sold as a one-off report — the measurement runs continuously and the backlog is reprioritized as the landscape moves, so the page you pick today keeps telling you the truth six months from now.
Whichever door you choose, the promise is the same: a clear read on where you stand in AI answers, an honest comparison against the competitors who currently out-cite you, a prioritized set of moves, and a measured lift you can defend internally. The role and sector pages simply make that promise concrete in the language you already use to run your part of the business.
It is worth being explicit about why this is urgent rather than interesting. The share of buying journeys that begin — and increasingly end — inside an AI answer is rising every quarter, and the engines tend to reward the sources that were citable first. Authority compounds: the brand an engine learned to trust this year is the easier one to surface next year. Starting late is not neutral, because a competitor who starts now is building the very signal that will keep them ahead. The pages below are designed to help you start where the return is highest, today, rather than wait for a perfect plan.
One last note on scope. SkuLift does not ask you to rebuild your site, replace your CMS, or abandon the SEO and paid programs that already work. The loop sits alongside them, reading the AI layer they do not touch and feeding back a backlog your existing teams can execute through a human gate. Whether you arrive as a CMO, a CEO, an SEO lead, an e-commerce owner, or a buyer evaluating for an entire sector, the commitment is the same shape: measure honestly, fix what matters most, and prove the lift — then decide how far to take it. And because the method below is identical across every role and sector page, you can compare two entry points side by side and trust that any difference you read is genuinely about your market and your data, never about the offer itself — so the door you pick first is simply the one that names your reality most directly.
By role
Four entry points for the people who own AI visibility — strategy, marketing, search, and commerce.
- SkuLift for CMOsYou do not know if, where, or against whom AI engines cite your brand.
- SkuLift for CEOsAI authority is becoming a strategic asset — and you have no read on it.
- SkuLift for SEO teamsClassic SEO no longer captures the zero-click value moving to AI answers.
- SkuLift for e-commerce leadersYour products do not surface in AI shopping answers and recommendations.
By sector
Five markets, each with its own typical AI queries, its own citable data, and its own trajectory.
- SkuLift for RetailShoppers ask AI for product picks; your catalog is invisible to them.
- SkuLift for B2B SaaSBuyers ask AI for the best tool; competitors get cited, not you.
- SkuLift for Financial ServicesCustomers ask AI for the best offer; trust and compliance are at stake.
- SkuLift for Travel & HospitalityTravellers ask AI where to go and stay; you are not in the answer.
- SkuLift for ManufacturingBuyers ask AI for a supplier or a spec; your technical authority is uncited.
How to read a Solutions page
Every page follows the same plan, so you can scan it in two minutes and act with confidence.
Each page opens with a one-paragraph answer, then states the pain in your terms for both B2B and D2C. It shows the SkuLift loop applied to your context, the KPIs that actually matter to you, and a trajectory from absent to leader. It ends with the maturity tier we would recommend — described by what you get, never by a price — and a short FAQ.
Use the role pages if you are choosing on behalf of a function, and the sector pages if you want to see your market’s queries and data named directly. The two views reinforce each other: a CMO in retail will recognize both the role page and the sector page, and either is a valid place to start a pilot.
Throughout, we describe the recommended maturity tier by what you get, never by a price — engagement is quoted for your scope. The tiers map to where you stand: a contained pilot to prove the model, or a continuously operated loop once you want the AI layer managed like any other channel. The FAQ on each page answers the objections that role or sector raises most often, so you can decide without a call.
You do not need to read all nine pages. Find the one that matches your role or your market, scan its answer-first opener and its KPIs, and check that the trajectory and recommended tier fit where you are today. If two pages apply — say a function and a sector — read both; they will agree on the method and differ only on the queries and data they name, which is exactly the cross-check a careful buyer wants before committing to a pilot.