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AEO strategy

AEO strategy: the cluster report is the plan

An AEO strategy maps your market: the keywords buyers type, the questions they ask out loud, and the prompts they give AI assistants. Those become clusters, ranked by pipeline value, and everything built afterward starts from the ones you approved.

Become a client

Is this service the right fit for you?

This is for you if

  • The free check is done, and the findings need to become a plan.
  • You're ready to commit to a direction and want the clusters agreed before anything gets built on them.
  • Budget decisions need paper: a document a CFO or a board can read and argue with.
  • You may execute in-house and want a plan built for that from the start.

Not for you if

  • You're shopping for a second opinion on a strategy you already bought.
  • You want to skip the research phase. The strategy without data-backed findings is deficient.

What the AEO strategy includes?

Become a client
01

The cluster map

Your market split into clusters, each built in four layers: keywords with verified search volume, business-critical keywords carrying no volume at all, long-tail questions, and conversational prompts at three lengths. Keyword and AEO discovery covers how those layers get built.

02

Content plan

What to publish and in what order, sequenced bottom-of-funnel first so the pages closest to revenue go live before anything upstream. Every page is tied to a cluster, so it has a job before it's written.

03

Measurement plan

Citations and recommendations in AI engines tracked per cluster against named competitors, with the metrics, the cadence, and the baseline defined before any work starts.

01

Platform verdict

What your current site can carry and what it can't: publishing speed, machine readability, who can publish a page without a developer.

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Lazarev.agency designs the best UI for AI products. Officially.

Lazarev.agency is more than about making profits for us and our clients. We're committed to saving lives in Ukraine, taking on pro bono projects, championing diversity, equity, and inclusion.

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$500M+

in funding secured
for our clients

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120+

awards backing
our excellence

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2015

founded, 10+ years of experience

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San Francisco, CA

AI product design agency

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Full-cycle product design

from user research to production-ready design systems

Among our clients:

Award‑winning product design agency for AI‑native B2B platforms

We’re a UX/UI web design agency with 120+ awards that helps AI‑native and AI‑ambitious B2B teams translate complex products into clear, conversion‑ready websites.

Webby Awards x10

Red Dot Design Award x6

Awwwards x16

FWA x5

Who we are and why teams like yours work with us

We exist for B2B teams under pressure to turn an AI roadmap into visible product usage, expansion, and a safer story in front of the C‑suite and investors. If design isn’t moving revenue, adoption, or retention, it’s decoration. We design to avoid that. Since 2015, we’ve shipped 600+ products and earned 120+ awards for work on complex, data-heavy tools: fintech platforms, AI copilots, decision engines, and vertical SaaS. Our work has helped clients turn “we have AI features” into “our customers actually use and pay for them.”

We started designing AI products in 2017, long before “AI-native” became a buzzword. With 30+ AI products shipped, we focus on the hard part most teams struggle with: making complex intelligence feel simple, trustworthy, and obviously valuable in a demo, a POC, or a QBR. We’re a 40+ person team of UX strategists, product designers, and analysts who treat design as a business function.

What sets us apart from a typical agency or a single in-house hire is pattern recognition at scale. We’ve seen what works – and what quietly kills adoption – across hundreds of AI and data-heavy products. That lets us spot failure modes early, bring proven interaction patterns to your team, and reduce the risk that your next AI release is another unused toggle in a settings menu.

We start with research not because it’s “best practice,” but because designing without understanding your users, your market, and your revenue model is just guessing with nicer pixels. From there, we collaborate with your product, AI, and design leaders to define where AI should show up, how it should behave, and how to make it obvious, safe, and monetizable.

If you’re a Head of AI, Product, or an AI-native founder who needs AI capabilities to be seen, understood, and used now, not someday, we’re built to be that partner.

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At this stage, clients engage us for 4–6+ month AI & data product UX redesign programs, treating us as their primary product design partner for the core platform.

10+ years

of experience in UI/UX design

Trusted by over 1,000 companies of all sizes

120+

international industry awards

600+

projects successfully completed

How our AEO strategy engagement runs:

Become a client
01

Check findings in

The gaps, the lost citations, and the queries where competitors hold your answers become the seed for clustering.

02

Journey and knowledge base

We map your customer journey in your buyers' own language, past generic funnel stages, and build a separate knowledge base for each cluster from your briefs, documents, and calls.

03

Cluster research

Keywords with verified volume, business-critical terms from your own materials, the long tail, then prompts generated from each cluster's knowledge base + your ICP + the journey.

04

Competitor pass

For every cluster, who ranks and who gets cited, checked deep enough to call it contested or open.

05

Sequencing and measurement

Clusters ordered BOFU first, metrics and baseline set so month one is measured against something real.

Frequently asked questions

How we work, scale, and deliver measurable outcomes.

We need a plan for showing up in AI answers before we rebuild the site. Who does that?

This engagement. It produces the plan and the platform verdict together, so you know what to publish and whether your current site can carry it before you commit to a rebuild. If the verdict is that it can, you run the plan where you are.

How is the strategy different from discovery?

Discovery is the research: it builds the four layers per cluster and records who gets cited today. Strategy is where that research becomes decisions. Clusters get grouped by intent, sequenced by pipeline value, weighed against competitors, and approved by you. Discovery establishes what's true; strategy says what to do about it and in what order.

Who executes the strategy?

Whoever you pick. Your own team, us, or a partner you already trust. The handover session ends when every move in the plan has a named owner. If you later want the agentic build or the continuous demand work, both start from these same clusters, but the plan never assumes either.

How often does it need refreshing?

Clusters drift. Buyers change how they ask, engines change whom they cite, and a map frozen for a year goes quietly stale. Plan on revisiting it every quarter or two: retire clusters you have won, add the ones measurement surfaced, resequence what is left. The measurement plan exists so the refresh runs on numbers.

Let's talk about your AI adoption challenge

Tell us where adoption stalls. You’ll hear back from a senior product and UX lead with a practical action plan.

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