$1.8Minbound pipeline, built from zero
WeSoftYou
Rebuilt inbound from scratch — 100% YoY SQL growth, 207% more traffic, domain rating from 12 to 45, and 141 articles shipped.
- 100% YoY SQL growth
- 207% traffic increase
Service · AI Search Optimization (AEO/GEO) for IT Consulting Companies
AI search optimization for IT consulting companies that need to be the firm a buyer's AI assistant recommends to trust with a high-stakes transformation — not a name a model skips for Accenture or Deloitte.
Before a CIO, CFO, or VP of Technology shortlists a consulting firm for a major transformation, modernization, or advisory engagement, they ask ChatGPT, Claude, Perplexity, or Google's AI Overviews who to call. The model returns three to five names, and if yours is not among them you are invisible at the moment the buying decision begins. We get your IT consulting firm into those AI-generated answers for the high-intent advisory and transformation prompts your buyers actually run — positioned as the specialist who earns trust before the pitch, not another brand-name also-ran — and we tie every recommendation back to booked meetings and CRM-tracked pipeline. Across our work we hit an 80% recommendation success rate on targeted commercial prompts.
- B2B tech companies worked with
- 60+
- Years marketing to technical & executive buyers
- 9+
- CRM-tracked marketing-led revenue
- $30M+
- AI Search recommendation success rate
- 80%
- Build your commercial prompt set: the "best IT consulting firms for [sector] transformation," "how to choose a technology advisor," "top boutique consultancies for [cloud/platform/modernization]," "[boutique] vs [global SI] for [transformation type]," "who should I hire to advise on [build vs buy / vendor selection / architecture decision]," and "why do [IT initiatives] fail" prompts that precede a real advisory engagement — prioritized by deal value and your specialization, not raw search volume.
- Run a baseline AI visibility and framing audit across ChatGPT, Claude, Perplexity, Gemini, and AI Overviews: whether you are named at all, whether the model hands the buyer to Accenture or a global SI instead of an independent firm, and whether your framing reads as genuine strategic advisory or as staff augmentation with a nicer slide deck.
- Map the citation landscape models pull from to recommend an IT consulting firm — analyst surfaces, sector-specific review and comparison platforms, editorial authority on transformation and decision-stage topics, and named-principal content — and target the ones worth earning placement on.
- Fix machine-readability so a model frames you past the generic advisory bucket: entity consistency, structured data, and crisp definitions that tie your firm to a specific sector, transformation type, and advisory depth rather than the undifferentiated "digital transformation, end-to-end, trusted advisor" phrasing every competitor uses.
- Seed verifiable trust facts that stop the brand-gravity default: outcome-led case studies organized by sector and transformation type that lead with the decision you got right and the risk you removed, named principals with a visible track record, and a clear "is this real advisory or staff augmentation" proof layer so the model has an authoritative, accurate source rather than a generic characterization.
- Rebuild proof into citable signal: case studies, framework content, and decision guides organized by sector and transformation type, framed so both the model and the economic buyers — the CIO, CFO, and board sponsor — can use them to screen a firm on judgment rather than capability claims.
- Engineer answer-shaping content built for this category — sector- and transformation-specific advisory guides, "how to choose between a boutique and a global SI," "what to expect from a [transformation type] assessment," and "build vs buy vs advise for [capability]" explainers written to become the source a model cites, not another services page the brand-names and analyst platforms outrank.
- Track the prompt set on a recurring cadence, attribute AI-sourced leads through a long, committee-gated advisory cycle in your CRM, and report movement as a pipeline channel — not a vanity mention dashboard.
How the system works
How the AI Search system works for an IT consulting firm.
Diagnose the market
We define and prioritize the advisory, sector-specific, and transformation prompts that decide engagements in your practice, then baseline where you stand on each across ChatGPT, Claude, Perplexity, Gemini, and AI Overviews. Because framing is a disqualifier here, we do not just check whether you are named — we check whether you are surfaced as a strategic advisor or mis-labeled as staff augmentation, whether the model skips independent boutiques and defaults to a global SI or the software vendor, and whether your sector and transformation specialization is reflected accurately or lost in abstraction. You get an honest map of which advisory conversations you win, which you lose to brand gravity, and where mis-framing is costing you deals.
Compare against known IT consulting patterns
We line your visibility up against the citation and recommendation patterns we have seen across 60+ B2B tech companies, consulting and advisory firms included. That tells us fast whether the gap is missing sector-specific outcome-led case proof, a thin editorial authority footprint on the decision-stage topics buyers search, weak entity data that lets the model abstract your practice into a generic bucket, or an absent "why us rather than the Big Four" story a model needs to defend recommending an independent firm. We diagnose the cause specific to this brand-gravity-dominated, judgment-gated category instead of applying generic GEO tactics.
Choose the right growth path
We pick the smallest set of moves that will actually change answers for your prompts: earning placement on the analyst and review surfaces models cite for IT advisory firms, correcting entity and framing data so you are tied to your real sector and transformation type rather than the generic bucket, publishing the decision-stage and "boutique vs global SI" content that becomes a citable source, or seeding the named-principal authority content that makes your judgment legible before the first call. No fluff retainer — only the levers that shift recommendations toward booked, advisory-led engagements rather than researcher noise.
Build the service system
We execute the chosen path as a repeatable program: editorial and review-signal work on the surfaces models trust for IT consulting, entity and schema cleanup that ties your firm to your actual sector and transformation type, verifiable judgment and advisory-depth proof seeding, outcome-led case studies reworked as citable proof organized by sector and engagement type, and answer-shaping advisory and selection-stage content — sequenced so each piece reinforces the others. In a market where brand gravity is the default and one generic framing confirms the staff-augmentation suspicion, AI Search becomes a compounding, defensible asset rather than a one-off experiment.
Optimize against CRM and sales feedback
Every cycle we re-measure the prompt set, re-check for new brand-gravity defaults, generic framing, or staff-augmentation mis-labels, attribute AI-sourced leads through your long sales cycle in the CRM, and pull your sales team's read on which calls were real advisory or strategy conversations versus researchers and job seekers. Prompts that produce qualified pipeline that clears the committee and the procurement function get more investment; the ones that pull informational traffic get cut. The system tunes toward tracked SQLs and won engagements, month over month.
The XQL difference
Why our AI Search system works for an IT consulting firm a generic GEO retainer cannot help.
- 01
Market memory
We have marketed for 60+ B2B tech companies over nine years — IT consulting and advisory firms among them — so we already know the commercial prompts that precede an advisory engagement and how they fork by sector, transformation type, and buyer role. "IT consulting" attracts students, junior researchers, and competitors; "best technology consulting firms for a financial-services modernization" or "who should we hire to advise on a build vs buy decision for [capability]" attracts a CIO or VP with a funded, board-approved initiative and a 90-day decision horizon. We start from the prompt set we have watched convert to signed engagements in this category — not a discovery exercise that learns what consulting buyers want on your budget.
- 02
Faster diagnosis
Most IT consulting firms cannot say whether a model names them at all, names the Big Four instead, mis-frames them as staff augmentation, strips their vertical or transformation specialization, or describes their practice so generically that nothing distinguishes them. We baseline your presence across the advisory and transformation prompts that matter in your practice on day one across ChatGPT, Claude, Perplexity, Gemini, and AI Overviews: who is named, who is cited, where you are flattened into a generic bucket, and where the model's framing contradicts how you actually position and sell. Within weeks you know exactly which transformation conversations you are absent from and why — rather than running blind for quarters.
- 03
Smarter channel selection
For an IT consulting firm, the lever that moves an AI answer is rarely your own website copy alone — it is the signal a model already trusts: sector-specific outcome-led case studies it can parse, your presence on the analyst and review surfaces it cites for advisory firms, your editorial authority on the transformation and decision-stage topics buyers search, and clean entity data that ties your firm to a specific sector, advisory depth, and transformation type. We fund only the moves that shift recommendations toward a specialist advisory framing — not a generic content checklist that ignores how this judgment-gated, referral-driven market actually gets cited.
- 04
Sales feedback loop
An AI recommendation is worthless if it sends researchers, job seekers, or prospects with no real initiative. We sit close to your sales team, review which AI-sourced leads booked real advisory scoping or strategy calls versus informational inquiries, and learn which prompts and framings produce qualified conversations — the buyers with a funded, live transformation and a decision-maker on the call. That feedback retargets the prompt set monthly toward the sectors and transformation types your team actually closes, so the program optimizes for engagements that clear procurement and the committee rather than raw mention counts.
- 05
CRM attribution
We treat AI Search as a measurable channel for a long, trust-led advisory deal. Beyond a visibility report, we instrument how an AI-discovered prospect enters your CRM and tie prompt-set movement to booked meetings, SQLs, and won engagements — with the analyst-check, reference-check, and procurement stages tracked as their own statuses, because that is where IT consulting contracts quietly stall for quarters. You see the line from "now recommended as a specialist for [sector] transformation" to "signed engagement that cleared the buying committee" — the same CRM discipline behind the $30M+ in marketing-led revenue we have tracked for clients.
Why XQL vs alternatives
Why XQL vs the alternatives, for an IT consulting firm.
DimensionTypical approachThe XQL way
Generalist GEO / marketing agencyBolts "AI optimization" onto a content retainer, tweaks your own website, and reports mentions — with no idea which advisory and sector-specific prompts decide consulting engagements, or why a model defaults to Accenture or mis-labels your firm as staff augmentation.Starts from the sector, transformation, and judgment prompts that move IT consulting buyers and works backward to the outcome-led proof, editorial authority, and entity data that get you recommended as a specialist past brand gravity.
Traditional SEO agencyChases broad terms like "IT consulting" or "digital transformation" you will never outrank the global SIs and analyst platforms on, and treats AI recommendations as a side-effect of search rankings — so you can rank somewhere and still be invisible or mis-framed when a buyer asks a model who to call.Optimizes for the advisory, sector-specific, and decision-stage prompts and the citation sources models actually pull from for IT consulting firms, while keeping the selection-stage SEO foundation that still feeds those answers.
PR / brand agencyProduces thought-leadership content and coverage for awareness without a view of whether it lands on the surfaces LLMs trust for IT advisory recommendations, or whether it ever changes the answer a model gives to a buyer in evaluation.Earns only the editorial placements and named-principal coverage on surfaces models already weight for advisory and transformation recommendations, then measures whether each one moves you on the prompts that matter.
In-house marketerUsually one stretched owner without the model-by-model baseline tooling, the IT consulting citation patterns, or the bandwidth to run a disciplined AI Search program across a 6-to-12-month advisory cycle — and rarely a way to catch a model characterizing the firm as staff augmentation or stripping the sector specialization entirely.Brings nine years and 60+ B2B tech engagements of pattern memory, a defined measurement and framing-audit system, and a team that runs the program end to end and reports it into your CRM.
Do nothingCedes the AI-generated shortlist to global brand gravity and better-positioned competitors — before a buyer ever reads your website, submits a contact form, or asks a trusted colleague for a referral.Gets you onto the shortlist for the advisory and transformation prompts your buyers actually run, before the brand-names and the analyst gatekeepers realize the question was even asked.
Commercial outcomes
Proof from the same playbook.
Strategy first, channels second, sales feedback always. We measure by the qualified demand and revenue we can trace back inside the CRM.
Selected results
Senior operators on every account. Never a junior pod.- +1,413%organic traffic growth
DBB Software
Built the marketing function from zero — website, SEO, paid, AI search — from 166 to 2,513 monthly clicks and 3 enterprise deals won.
- 28 SQLs from zero
- 3 deals won
Client signal
What B2B tech founders and CEOs say
Thanks to XQL Group's efforts, we've seen a 207% increase in web traffic and an improvement in domain rating from 12 to 45. The team has successfully optimized our SEO strategy and gained around 160 backlinks. Overall, they're responsive and thorough in their project management.
Since working with XQL Group, our domain rating has improved from 27 to 44. In addition, we've seen a 15% increase in monthly traffic within nine months. The team completes work on time and within the agreed budget. Moreover, their subject matter expertise is highly impressive.
XQL Group's efforts have resulted in 44 leads from paid campaigns and improved web traffic from Germany by 5x. The team is responsive, quickly surfaces issues, and communicates regularly through chats and virtual meetings. Their expertise and proactiveness have impressed our team.
Organic traffic has increased by 10–15% each month, and we have started receiving our first inbound requests. XQL Group's optimization tips have also helped improve keyword rankings, and internal stakeholders are impressed with the team's collaborative approach.
XQL Group has successfully defined a clear marketing strategy and established our company's unique value proposition. The team has also helped hire critical specialists for our marketing team. They are communicative and organized, and their expertise in the tech industry is impressive.
Thanks to XQL Group's efforts, we have defined our marketing strategy and hired key developers for our website. The team has launched retargeting campaigns on LinkedIn and developed a strong content marketing strategy. XQL Group's marketing expertise is a hallmark of the engagement.
They were not just talking about AI search in theory; they knew how to approach it practically.
What impressed us most was their deep specialization in working with software development companies.
They've brought structure, strong execution, and constant initiative to improve outcomes.
They operated with the discipline and initiative of an internal senior marketer.
Their ability to combine strategic vision with hands-on execution was particularly valuable.
Their focus on results and true interest in making things work set them apart.
XQL Group's project management was exemplary.
The quality of their work is consistently high.
FAQ
Questions about this service.
Increasingly they do both — but an AI assistant is faster and more specific than waiting for an analyst briefing, and it surfaces firms a buyer's personal network has never mentioned. The buyers who reach for an assistant are typically in the early pre-qualification stage: they have a funded initiative, a 90-day decision horizon, and they want a first cut before they spend political capital asking the board or a peer for a recommendation. The shortlist the assistant generates sets the frame for everything that follows. If your firm is not in it, you are absent from a conversation that decides whether you get called — and you will never know it happened.
It is one of the few surfaces where it can — which is why it matters now. A model does not weight brand budget or logo recognition the way a cautious CIO does when a board is watching; it weights specific, credible evidence. Named, outcome-led case proof in a sector, editorial authority on the decision-stage topics buyers search, clean entity data that ties your firm to a transformation type and advisory depth the global SIs cannot credibly claim for a mid-market or vertical-specific engagement, and a defensible point of view the model can cite — that is how an independent boutique appears on the same shortlist as Deloitte for a specific problem. The analyst gatekeeping and word-of-mouth that traditionally reproduced the global brand advantage do not control this surface. That is the opening.
That is the most damaging failure mode in this category and the one most firms do not know is happening. When a model has thin, contradictory, or generic evidence — "IT consulting, end-to-end, trusted advisor" — it fills the gap with the cheapest interpretation of what consulting means, and the buyer who needed a strategic advisor screens you out before the first call. Our baseline audit explicitly checks for this mis-framing, then fixes the upstream causes: entity and schema data that distinguishes advisory and judgment from delivery and capacity, outcome-led case studies that lead with the decision you got right and the risk you removed rather than the methodology slide, and named-principal content that makes your seniority and thinking visible before a buyer commits a dollar. The goal is a recommendation that reads as real consulting, because that is what converts.
Commercial, high-intent advisory prompts — the queries a funded buyer with an active initiative runs, not informational how-to searches. Examples: "best IT consulting firms for [sector] modernization," "top boutique technology consultancies," "who should we hire to advise on a cloud migration strategy," "how to choose between a boutique and a global SI for [transformation type]," "what to expect from a technology assessment," and "build vs buy vs advise for [capability]." We prioritize by deal value and your actual specialization, then track them against real pipeline rather than raw mention counts.
We baseline your presence across a defined prompt set — who is named, how you are framed, which prompts are owned by global brands — then track movement over time. The part most programs skip: we instrument how AI-discovered prospects enter your CRM and follow them through the stages IT consulting deals actually stall in — first touch, strategy or scoping call, SQL, analyst-check, reference-check, procurement — through to a signed engagement. You see the line from "now recommended for [sector] transformation advisory" to "engagement that cleared the buying committee," not a vanity citation dashboard.
Because referral and reputation growth is real but bounded — it does not reach the buyers who have no one in their network to ask, does not surface when a buyer's AI assistant generates a shortlist at 11 PM before a board presentation, and cannot be forecasted as a pipeline channel. AI Search is not a replacement for the judgment and outcomes that earn referrals; it is the mechanism that makes that same reputation legible to buyers who have never met you. For an IT consulting firm, being on the AI-generated shortlist for your specific advisory and sector prompts is the closest thing to being on the analyst radar without the analyst relationship — and WeSoftYou's path from effectively zero inbound to $1.8M of tracked marketing-led pipeline shows how a firm with a genuine track record can build that visibility deliberately rather than waiting for word-of-mouth to travel far enough.
Ready when you are
Let's talk.
Bring your offer, channels, and revenue goals. We'll show you where the biggest growth constraint is and what to build next.
Danylo FedirkoFounder
For B2B tech companies selling complex expertise to serious buyers.
- B2B tech clients
- 60+
- Revenue generated
- $30M+
