Tag: Perplexity

The Review Blind Spot Costing Irish Tech Companies Millions in Lost Business

Your Prospects Are Checking Reviews Before They Contact You – Most Irish Tech Companies Haven’t Noticed

The final stage of almost every B2B purchase decision now includes the same step: the prospect checks reviews. After the website visits, the demo requests, the shortlisting conversations – before they sign, they validate. They search your company name, scan Google results, check Trustpilot, look at G2 or Clutch or whatever platform covers your sector.

What they find in those final moments often determines whether you win or lose the deal. And most Irish tech companies have given this stage almost no attention at all.

Walk through the buying process yourself. You’re evaluating two software vendors or two agencies or two consultancies. Both seem capable. Both have decent websites. But one has a strong review presence – dozens of reviews across multiple platforms, consistent ratings, recent feedback. The other has a handful of reviews, or reviews only on one platform, or nothing recent. Which creates more confidence?

ProfileTree, the Belfast digital agency that has deliberately built review presence across multiple platforms over its twelve-year history, sees this pattern repeatedly when working with tech companies across Ireland and the UK. Strong products and genuine expertise undermined by weak visible credibility. Deals that should close but don’t. Sales cycles that drag because prospects can’t easily validate claims.

The cost isn’t theoretical. It shows up in conversion rates, in sales cycle length, in the opportunities that never materialise because prospects chose competitors who simply looked more trustworthy at the moment of decision.

Why Reviews Have Become Non-Negotiable

The shift toward review-influenced purchasing has been gradual but comprehensive. What started as a consumer behaviour – checking Amazon reviews, reading TripAdvisor before booking – has migrated fully into B2B decision-making.

Today’s business buyers have grown up checking reviews before every purchase. They don’t switch off that behaviour when making professional decisions. If anything, the stakes being higher makes validation more important, not less. Nobody wants to recommend a vendor to their organisation only to have it fail publicly.

This creates a simple reality: your prospects will check reviews. The only question is what they’ll find when they do.

The challenge for many Irish tech companies is that they’ve treated reviews as something that happens passively rather than something they build actively. They wait for customers to spontaneously leave feedback rather than systematically requesting it. The result is review profiles that don’t reflect actual customer satisfaction – thin, outdated, or skewed by the reality that dissatisfied customers review unprompted while satisfied customers rarely do.

The gap between reality and visible perception costs revenue. A company with excellent delivery and happy customers but weak review presence loses to competitors whose customers are simply more visible.

The AI Amplification Effect

Reviews have always influenced purchase decisions. What’s changed is that AI systems now use review presence as a primary signal when deciding which businesses to recommend.

When someone asks ChatGPT, Perplexity, or Google’s AI Overview “Which software development agencies should I consider in Ireland?”, the AI synthesises information from multiple sources to generate recommendations. Review presence – the volume of reviews, ratings, distribution across platforms – heavily influences which companies make that recommendation.

AI systems treat reviews as independent validation. Your website contains claims you make about yourself. Reviews represent claims others make about you. AI weights third-party validation more heavily because it’s harder to manufacture and more likely to reflect genuine experience.

Companies with strong review profiles across multiple platforms appear more credible to AI. Those with thin or absent review presence trigger lower confidence. The practical result: AI recommendations increasingly favour companies that have invested in review strategy, regardless of how their actual quality compares to competitors.

This creates compounding advantage. Companies appearing in AI recommendations attract more customers, generating more opportunities for reviews, strengthening review profiles further, increasing likelihood of future AI recommendations. Companies absent from AI recommendations miss these opportunities entirely.

As explored in TechBuzz Ireland’s analysis of why Irish tech companies are failing at sustainability marketing, the sector repeatedly demonstrates strong capabilities paired with weak communication of those capabilities. Reviews are another manifestation: companies with satisfied customers who haven’t converted that satisfaction into visible proof that prospects and AI systems can find.

Why Tech Companies Specifically Struggle

Several factors explain why technology companies tend to underperform on reviews compared to other sectors.

Engineering-driven cultures undervalue marketing fundamentals. Tech companies often prioritise product development over marketing basics. Reviews can feel like a “soft” concern compared to feature development or technical capabilities. This cultural bias means review strategy rarely receives serious attention or resources – even when the commercial impact is significant.

The assumption that B2B is different. Many tech leaders assume reviews matter for consumer products but not enterprise sales. “Our buyers conduct proper procurement,” they reason. “They don’t check Google reviews like consumers do.” This assumption doesn’t match reality. B2B buyers absolutely check reviews – they simply use different platforms than consumers, like G2, Capterra, Clutch, and Trustpilot.

Discomfort with asking. Requesting reviews feels awkward to many technical professionals. Engineers and technical founders especially can struggle with what feels like self-promotion. This discomfort produces inaction, even when satisfied customers would happily provide reviews if asked directly.

No systematic process. Without deliberate systems, review generation depends on customers spontaneously deciding to leave feedback. This happens rarely. Dissatisfied customers tend to review without prompting; satisfied customers typically don’t think to do so unless asked. The result is review profiles that underrepresent actual customer satisfaction.

Platform fragmentation. Unlike retail where Google and Amazon dominate, tech reviews scatter across Google, Trustpilot, G2, Capterra, Clutch, industry-specific platforms, and LinkedIn recommendations. Companies unsure where to focus often focus nowhere, spreading effort too thin or avoiding the question entirely.

https://www.youtube.com/watch?v=giMFm8NUwoQ 

What Effective Review Strategy Looks Like

Companies that build strong review presence share common characteristics in their approach.

Systematic rather than sporadic. Effective review generation isn’t a campaign that runs once – it’s a process embedded in ongoing customer interactions. Successful companies identify optimal moments to request reviews (after successful project delivery, following positive support interactions, at contract renewals) and build requests into standard workflows.

Multi-platform presence. Distributing reviews across relevant platforms creates resilience and reach. For Irish tech companies, this typically means Google Business Profile, Trustpilot, and relevant industry platforms (G2 or Capterra for software companies, Clutch for agencies, sector-specific platforms where they exist). Concentration on a single platform creates vulnerability; distribution builds credibility.

Response to all reviews. Companies that respond to reviews – positive and negative – demonstrate engagement and care. Responses to negative reviews particularly influence perception. Prospects often judge companies more by how they handle criticism than by the criticism itself. A thoughtful, professional response to a complaint can actually build trust; no response or a defensive response raises concerns.

Integration with customer success. Review requests work best when connected to genuine customer success moments rather than arbitrary timing. Asking customers who’ve just achieved results with your product or service yields better response rates and more substantive reviews than generic requests sent on a schedule.

Making it easy. Every barrier reduces completion rates. Direct links to review platforms, clear simple instructions, and minimal friction increase the likelihood that willing customers actually follow through. Companies that require customers to navigate complex processes receive fewer reviews than those who make the path simple.

ProfileTree’s approach demonstrates this strategy in practice. The agency maintains over 60 five-star reviews on Trustpilot and a Google Business Profile with 450+ five-star reviews. This distributed presence across platforms creates the signals that influence both human prospects conducting due diligence and AI systems assessing which businesses to recommend.

Building this presence took consistent effort over years – not a quick campaign but an ongoing commitment to asking satisfied customers to share their experience where it can help future customers make informed decisions.

youtube.com/watch?v=afVwigrGLVI 

Platform Strategy for Irish Tech Companies

Different platforms serve different purposes, and effective strategy allocates effort appropriately.

Google Business Profile provides foundational local visibility and influences Google search results directly. For companies serving Irish markets, a strong Google profile with substantial review volume is essential. This platform also feeds AI systems extensively – Google reviews are among the most commonly referenced sources when AI assistants evaluate local business credibility.

Trustpilot carries significant weight for B2B credibility, particularly in UK and European markets. Irish companies serving these markets benefit from Trustpilot presence. The platform’s verification processes and public transparency make reviews particularly credible to sceptical prospects.

G2 and Capterra dominate software category research. Tech companies with software products should prioritise these platforms, where purchase-stage prospects actively compare options. Reviews here directly influence shortlisting decisions for software purchases.

Clutch matters for professional services – agencies, consultancies, development shops. The platform’s verified review process and detailed review structure provide credibility for services where trust is paramount. Being well-reviewed on Clutch signals legitimacy to prospects evaluating agencies.

LinkedIn recommendations contribute to company credibility, particularly for B2B services. While not a traditional review platform, accumulated recommendations on company pages and key personnel profiles create social proof that prospects encounter during research.

Industry-specific platforms vary by sector. Fintech, healthtech, edtech, and other verticals often have dedicated review platforms or directories where presence carries disproportionate influence within the niche.

The goal isn’t presence everywhere – it’s meaningful presence on the platforms your specific prospects use during their decision-making process.

The Competitive Landscape

Most Irish tech categories have surprisingly weak review competition. This represents opportunity for companies willing to invest in building review presence while competitors neglect it.

Conducting competitive review analysis reveals the landscape. How many reviews do leading competitors have on each relevant platform? What are their ratings? How recent are their reviews? Which platforms do they neglect?

In many Irish tech categories, achieving strong review presence doesn’t require hundreds of reviews. Meaningful competitive advantage might come from 30-50 reviews on key platforms – numbers any company with reasonable customer volume can generate within a year of focused effort.

This window won’t remain open indefinitely. As more companies recognise the importance of reviews for both human decision-making and AI visibility, competition will intensify. Early movers who build review presence now accumulate advantages that later entrants struggle to match.

Starting From Behind

Companies with weak existing review profiles face the challenge of building from a deficit. The approach differs from companies starting fresh.

Understand what you’re working with. Before launching review initiatives, assess your current state honestly. What’s your rating across platforms? How many reviews do you have? How recent are they? What do negative reviews say?

Address underlying issues first. If existing reviews reveal genuine problems, fix those problems before seeking more volume. More reviews won’t help if the same issues keep appearing. Use negative feedback as insight into what needs improving.

Start with your strongest relationships. Begin outreach with customers most likely to provide positive reviews – recent successful projects, long-term relationships, accounts where you’ve delivered clear results. Early positive reviews create momentum and improve overall rating.

Don’t try to bury negatives artificially. Seeking floods of positive reviews specifically to drown out legitimate criticism looks suspicious and platforms may detect the pattern. Instead, respond professionally to negatives and build genuine positive reviews over time through consistent good work and systematic asking.

Be patient with improvement. Ratings improve gradually. A company with a 3.5-star rating and 20 reviews won’t reach 4.8 stars quickly. Each positive review shifts the average slightly. Consistency over 12-18 months produces meaningful improvement.

Ciaran Connolly, founder of ProfileTree, observes: “Most tech companies treat reviews as something that happens to them rather than something they build deliberately. That passive approach is expensive. Every satisfied customer who doesn’t leave a review is a missed opportunity to strengthen your credibility for the next prospect evaluating their options.”

The True Cost of Neglect

Review neglect costs Irish tech companies in multiple interconnected ways.

Lost deals during final research. Prospects who reach shortlisting stages often conduct final validation before signing. Weak review profiles at this critical moment push deals to competitors with stronger visible credibility. These losses are particularly painful because the sales investment has already been made – the prospect was ready to buy.

Extended sales cycles. Prospects uncertain about vendors due to thin review presence require more reassurance through other channels. Sales teams spend additional time providing references, arranging calls with existing customers, and addressing trust concerns that strong reviews would have resolved automatically.

Higher customer acquisition costs. When reviews don’t provide social proof, marketing must work harder through other channels. Companies compensate for weak reviews with larger advertising budgets, more content marketing, and heavier sales investment – all more expensive than systematic review generation.

AI invisibility. Companies with weak review profiles are increasingly invisible to AI recommendation systems. This represents a growing category of lost opportunity that traditional analytics don’t even capture.

Valuation impact. For companies seeking investment or acquisition, review profiles contribute to perceived brand strength. Due diligence increasingly includes review analysis. Weak review presence raises questions about customer satisfaction and market position.

The Integration Imperative

Review strategy doesn’t exist in isolation. It connects to broader digital presence and overall marketing effectiveness.

Strong review presence amplifies other marketing investments. Website visitors who see review badges feel more confident. Sales conversations can reference review credibility. Marketing materials cite customer ratings. The investment pays dividends across channels.

Conversely, weak review presence undermines other investments. Marketing campaigns that generate interest lose impact when prospects research and find thin review profiles. Sales efforts stall when prospects can’t easily validate claims. Website conversions suffer when social proof is absent.

For Irish tech companies, reviews represent unusually high-leverage investment. The cost of systematic review generation is modest compared to most marketing activities – primarily process and consistency rather than budget. The impact spans prospect conversion, sales cycle acceleration, AI visibility, and competitive differentiation.

Few other investments deliver comparable return for the effort required. The companies recognising this are building review assets now. Those waiting will face increasingly strong competitors and an increasingly difficult climb.

Frequently Asked Questions

How many reviews do we actually need?

There’s no universal number, but competitive position matters more than absolute count. Assess your competitors’ review presence on each relevant platform and aim for parity or advantage. The goal is being well-reviewed relative to the alternatives prospects might also evaluate, not hitting an arbitrary target.

Won’t asking for reviews seem pushy or unprofessional?

Customers expect to be asked. Most satisfied customers are willing to leave reviews but simply don’t think to do so unprompted. A professional, appropriately-timed request is standard business practice. The key is timing (after positive outcomes) and making the request easy to fulfil.

What should we do about negative reviews?

Respond professionally, acknowledging the concern and offering to resolve it. Don’t argue, dismiss, or ignore. Prospects reading negative reviews often judge companies by their response more than by the complaint itself. A thoughtful response to criticism demonstrates maturity; no response or a defensive response suggests problems.

Can we incentivise customers to leave reviews?

You can reduce friction and express genuine gratitude, but you cannot pay for reviews or offer rewards conditional on positive content – this violates platform policies and can result in review removal or worse. Appropriate approaches include donating to charity for each review received, or simply thanking customers for taking the time. Incentivise the act of reviewing, never the specific content of reviews.

How do we get reviews on B2B platforms like G2 or Clutch?

The process mirrors consumer platforms but with business context. Request reviews after successful implementations, following positive quarterly reviews, or when customers express satisfaction. Make the specific platform link easily accessible and explain why their review matters – usually honestly: “It helps other companies like yours find solutions that work.”

Should we respond to positive reviews too?

Yes. Responding to positive reviews demonstrates engagement and appreciation. Keep responses genuine rather than templated – customers who took time to write thoughtful reviews deserve individual acknowledgment, not copy-paste replies.

How long does it take to build strong review presence?

Building meaningful review presence typically takes 12-18 months of consistent effort. This isn’t a quick campaign but an ongoing process. Companies that embed review requests into their customer workflows and maintain consistent activity see steady accumulation over time. Starting sooner means finishing sooner.

ProfileTree is a Belfast-based digital agency specialising in web design, SEO, content marketing, video production, and AI training for businesses across Ireland and the UK. The agency has built review presence deliberately over twelve years, maintaining over 60 five-star reviews on Trustpilot and 450+ five-star reviews on Google – demonstrating the multi-platform approach that builds credibility with both prospects and AI systems.

Why Irish Tech Companies Are Invisible to AI Search (And Losing Customers Without Knowing It)

A Growing Number of Business Decisions Now Start With an AI Query – Not a Google Search

Something fundamental has shifted in how businesses and consumers find service providers. When a procurement manager needs to shortlist software vendors, when a marketing director researches agency options, when a business owner looks for specialist expertise – increasingly, the first question goes to an AI assistant rather than a search engine.

ChatGPT, Google’s AI Overviews, Perplexity, Microsoft Copilot – these tools now handle a growing proportion of “who should I hire?” and “which company should I use?” queries. The businesses appearing in those AI-generated answers get considered. Those invisible to AI don’t even know they’ve been excluded from the conversation.

ProfileTree, the Belfast-based digital agency that works with tech companies across Ireland and the UK, has been tracking this shift since AI search tools gained mainstream adoption. The pattern emerging is clear: Irish tech companies with strong products and genuine expertise are losing visibility to competitors who’ve adapted their digital presence for how AI systems evaluate and recommend businesses.

This isn’t a distant future concern. It’s happening now, and most Irish tech companies haven’t recognised the shift – let alone responded to it.

The Shift from Rankings to Recommendations

Traditional search worked on a simple model: optimise your website, build backlinks, rank higher, get more clicks. Companies invested in SEO, achieved good rankings for target keywords, and generated steady organic traffic. This model still functions – but it’s no longer the complete picture.

AI recommendation operates differently. When someone asks an AI assistant “Who are the best cybersecurity firms in Ireland?” or “Which agencies handle B2B tech PR in Dublin?”, the AI doesn’t return a list of ten blue links to evaluate. It synthesises information from across the web and recommends two or three companies it deems most credible – often explaining its reasoning.

The implications are significant. In traditional search, appearing on page one meant visibility alongside nine competitors. In AI recommendation, appearing at all often means being one of just a handful of mentioned options. And not appearing means complete exclusion – prospects never learn your company exists.

Gartner and other analyst firms have projected that up to 25% of organic search traffic could migrate to AI-powered interfaces in the coming years. For B2B tech companies, where purchase decisions often begin with research queries, the shift may be more pronounced.

Why Strong SEO Doesn’t Guarantee AI Visibility

Irish tech companies that invested heavily in SEO over the past decade often assume those efforts protect them. They rank well for target keywords, generate steady organic traffic, and see their brand appear in traditional search results. This creates dangerous complacency.

AI recommendation rewards different signals than traditional SEO. Search engine optimisation focuses on technical factors, backlink profiles, and keyword targeting. AI recommendation focuses on clarity, consistency, credibility signals, and the breadth of your digital footprint across multiple sources.

A company might rank first on Google for “Dublin fintech development” through solid SEO work, yet never appear when someone asks ChatGPT the same question. The AI isn’t simply replicating Google’s rankings – it’s forming its own assessment of which companies are credible enough to recommend based on information synthesised from across the web.

This explains an emerging pattern: established players with strong SEO being overlooked while smaller competitors with clearer digital positioning appear in AI recommendations. The smaller company might have inferior backlink profiles but superior clarity – consistent descriptions everywhere, reviews on multiple platforms, clear statements of expertise. AI systems find them easier to understand and trust.

The pattern parallels other marketing blind spots in Irish tech. As explored in TechBuzz Ireland’s analysis of why Irish tech companies are failing at sustainability marketing, the sector repeatedly demonstrates strong operational capabilities but poor communication of those capabilities. AI visibility is the latest manifestation: companies doing excellent work that AI systems can’t identify or recommend because the digital signals are missing or muddled.

What AI Systems Actually Look For

Understanding what AI assistants evaluate when recommending businesses reveals why many Irish tech companies fail the test.

Clarity of identity and offering. AI systems need to understand precisely what a company does, who it serves, and where it operates. Vague descriptions like “innovative technology solutions” or “digital transformation partner” give AI nothing concrete to work with. Specific statements – “enterprise software development for financial services companies across Ireland and the UK” – are far more useful for AI trying to match queries to recommendations.

Consistency across sources. AI cross-references multiple sources when assessing a business. If your website describes you as a “software development agency,” your LinkedIn says “technology consultancy,” and your Google Business Profile lists “IT services,” the inconsistency reduces AI confidence. Companies with identical core descriptions across every platform signal reliability.

Third-party validation. AI systems weight independent sources heavily. Review profiles on platforms like Trustpilot, Google, Clutch, and industry platforms create external validation AI can reference. Press coverage, industry awards, directory listings, and professional body memberships all contribute. Companies relying solely on their own website claims lack the corroborating evidence AI needs to recommend with confidence.

Breadth of digital presence. Appearing across multiple credible platforms – industry directories, review sites, professional networks, local business listings – creates the distributed footprint AI trusts. A company with strong presence only on their own website appears less established than one appearing consistently across relevant platforms.

Specificity of proof. AI favours concrete, verifiable information over vague claims. Statements like “12 years in operation,” “worked with over 1,000 clients,” or “5-star rating across 450 reviews” give AI something to reference confidently. “Extensive experience” and “trusted by many clients” cannot be verified or cited.

ProfileTree, for example, has built the kind of distributed digital presence AI systems can assess: founded in 2011, over 450 five-star reviews on Google, 60+ five-star reviews on Trustpilot, presence on industry platforms, and consistent service descriptions across sources. These signals create the clarity AI needs when recommending digital agencies for Belfast and Northern Ireland queries.

The Sectors Facing Greatest Risk

Certain Irish tech sectors face disproportionate exposure to AI invisibility.

B2B SaaS companies depend on being discovered during research phases of purchasing decisions. When procurement teams and department heads increasingly use AI assistants for initial research, companies invisible to AI miss the shortlist entirely. Unlike consumer products where existing brand awareness might carry through, B2B tech purchases often begin with open-ended queries where AI invisibility can be fatal.

Professional services firms – consultancies, development agencies, managed service providers – compete in categories where AI recommendations carry particular weight. Queries like “best IT consultancies in Dublin” or “top software development agencies in Ireland” produce AI answers that directly influence which companies get contacted.

Emerging technology specialists in AI, cybersecurity, fintech, and medtech face intense competition where differentiation matters. These sectors attract new entrants constantly, and AI systems may recommend newer companies with clearer digital positioning over established players with stronger track records but weaker digital signals.

Regional tech companies outside Dublin face compounded challenges. AI systems drawing on web-wide data may default to Dublin-centric recommendations unless companies in Cork, Galway, Limerick, and elsewhere have explicitly clear geographic signals. A Galway software company with ambiguous location information might never appear in “tech companies in the West of Ireland” queries.

The Measurement Problem

Most Irish tech companies can’t quantify their AI visibility because they’ve never measured it. Traditional analytics track website visits, keyword rankings, and conversion rates – none of which capture whether you’re being recommended by AI assistants.

This measurement gap allows the problem to grow undetected. Companies continue investing in SEO and paid advertising while a growing channel – AI recommendation – delivers enquiries to competitors. Without tracking, the lost opportunities remain invisible.

Basic measurement requires regularly testing how AI systems respond to queries your customers might ask. What happens when you ask ChatGPT, Perplexity, or Google’s AI Overview “Who are the best [your category] companies in Ireland?” Does your company appear? How is it described? Which competitors show up instead?

Companies that conduct these audits often discover uncomfortable gaps between their perceived market position and their AI visibility. Testing takes minutes and costs nothing – yet most companies have never done it.

What’s Actually Required

Fixing AI invisibility isn’t about gaming algorithms or implementing quick tricks. It requires fundamental clarity about how you present your business across the digital landscape.

Audit your current state. Test AI responses to relevant queries. Document where you appear and where you don’t. Identify competitors who appear when you don’t and analyse what makes their digital presence more AI-friendly.

Establish consistent identity. Ensure your business name, description, location, and service offerings are identical across your website, Google Business Profile, LinkedIn, industry directories, and every other platform where you appear. Eliminate variations that create confusion.

Build distributed credibility. Develop presence across relevant platforms beyond your website. Industry directories, review sites, professional networks, local business listings, and sector-specific platforms all contribute to the breadth of footprint AI systems evaluate.

Accumulate third-party validation. Systematically build reviews across multiple platforms – not just Google. Pursue press coverage, industry recognition, and directory inclusions that create independent corroboration of your credibility.

Create AI-friendly content. Ensure your website contains clear, specific, factual statements about your expertise, experience, and credentials. AI systems need quotable information they can reference with confidence. Marketing language designed to sound impressive but say little gives AI nothing useful to work with.

Maintain and update. AI systems favour current information. Outdated content, old team information, and stale descriptions signal neglect. Regular updates demonstrate active, credible operation.

The Window of Opportunity

The current period represents an unusual opportunity for Irish tech companies willing to adapt quickly. AI search is growing but hasn’t yet become universal. Most competitors haven’t recognised the shift or taken action. Companies that establish strong AI visibility now build advantage before the market catches up.

This mirrors patterns from early SEO adoption. Companies that invested in search optimisation in the early 2000s built positions that later entrants struggled to displace. AI visibility may follow similar dynamics – early movers establishing presence that becomes difficult for latecomers to challenge.

The risk of inaction compounds over time. As AI assistants become more prevalent, the proportion of opportunities influenced by AI recommendations grows. Companies invisible to AI today lose a small percentage of potential business; the same companies invisible to AI in two years may lose dramatically more.

Ciaran Connolly, founder of ProfileTree, puts it directly: “Irish tech companies have spent years building products, expertise, and reputations that genuinely deserve recognition. The frustration is watching them miss opportunities because AI systems can’t find or understand them. AI visibility isn’t about being the best – it’s about being clear enough that AI can see what you offer.”

The Broader Context

AI invisibility connects to broader challenges in how Irish tech companies communicate their value. Strong operational capabilities paired with weak external communication is a recurring pattern – evident in sustainability marketing challenges, employer branding struggles, and now AI search visibility.

The common thread is a gap between what companies actually do and what the outside world – including AI systems – can perceive and understand. Closing that gap requires treating external communication with the same rigour applied to product development and operations.

For Irish tech companies, the immediate priority is clear: assess your current AI visibility, identify gaps, and begin building the digital presence that AI systems can understand and trust. The companies taking action now will capture opportunities; those waiting will wonder why enquiries are going elsewhere.

Frequently Asked Questions

How do I check if my company appears in AI recommendations?

Test the AI assistants your customers might use – ChatGPT, Google’s AI Overview, Perplexity, Microsoft Copilot. Ask questions like “Who are the best [your service] companies in Ireland?” or “Which [your category] providers should I consider in [your city]?” Note whether you appear, how you’re described, and which competitors are recommended instead. Repeat monthly to track changes.

Does Google ranking still matter if AI is becoming important?

Traditional Google rankings still matter significantly – AI hasn’t replaced conventional search, and won’t entirely. However, AI recommendation is growing as an additional channel. Companies need both: strong SEO for traditional search visibility and clear digital presence for AI recommendation. The clarity that helps AI visibility often improves traditional SEO performance too.

How long does it take to improve AI visibility?

Meaningful improvement typically takes three to six months of consistent effort. Some elements – fixing inconsistencies, updating content – can be addressed quickly. Others – building reviews, accumulating press coverage, establishing directory presence – require sustained activity over time.

Is this relevant for smaller companies or mainly large enterprises?

AI visibility may actually benefit smaller companies more than large ones. AI systems don’t automatically favour market leaders – they favour clarity and credibility signals. A focused smaller company with clear positioning, strong reviews, and consistent presence can appear in AI recommendations ahead of larger competitors with muddled digital footprints.

What’s the single most important thing to fix first?

Consistency. Ensure your business description, services, and location are identical across your website, Google Business Profile, LinkedIn, and any directories where you appear. Inconsistencies are a common reason AI systems lack confidence to recommend businesses. This fix requires no budget – just attention to detail across platforms you already control.

ProfileTree is a Belfast-based digital agency working with tech companies across Ireland and the UK on web design, SEO, content strategy, and AI visibility. The agency holds 60+ five-star reviews on Trustpilot and over 450 five-star reviews on Google, demonstrating the distributed review presence that influences AI recommendation.

Samsung Launches First-Ever Perplexity AI-Powered TV App

Samsung Electronics today announced the launch of the Perplexity TV App, the first-ever Perplexity AI-powered TV app on the market. Elevating Samsung’s Vision AI Companion, which brings smart, generative AI support to the largest communal screens, the Perplexity TV App offers a new and innovative AI-powered experience to help users quickly find what they’re looking for and discover new favorites.

Perplexity is an AI-powered answer engine that draws from credible sources in real time, accurately answering questions, performing deep research, and suggesting additional questions that allow curious users to engage more deeply with the content they consume.

“The first-of-its-kind Perplexity AI-powered app, now available only on Samsung TVs, broadens our Vision AI Platform offering for a more unique and personalized user experience,” said Dan Glassman, Senior Director & Head of New Business Development for Samsung Electronics. “Samsung continually brings innovative and first-to-market experiences to our device owners, and this partnership with Perplexity is the latest that will deliver cutting-edge AI technology, redefining how Samsung owners interact with their TVs.”

“Curiosity can strike at any time. Perplexity’s mission is to serve the world’s curiosity by bridging the gap between traditional search and innovative AI-driven interfaces,” said Ryan Foutty, VP of Business at Perplexity. “Samsung is the number one television brand in the world, and we are excited to bring the functionality that Perplexity users know and trust to Samsung’s television screens and device owners around the world.”

Elevating the Vision AI Companion Experience
Unveiled earlier this month at IFA 2025, the Vision AI Companion brings the next evolution of AI-powered displays to Samsung TVs and smart monitors by integrating Samsung’s most advanced AI features into a single, intuitive AI experience. As part of the Vision AI Companion, the Perplexity TV App is now available as a standalone AI agent, offering even more innovative AI-powered experiences to Samsung users.

Navigate to the Perplexity TV App on your TV’s home screen and click on it to launch. From there, Perplexity can help with planning a trip, finding which movies were directed by the Russo Brothers or creating the ultimate fantasy lineup, all directly from your TV.

 

Getting Started

The Perplexity TV App offers a sleek and visually appealing experience, going beyond text-only responses. When you ask Perplexity a question, results appear with high-quality, glanceable cards made just for Samsung TVs.

How It Works:
Access: Navigate to the Perplexity TV App via the Apps Tab or in Samsung’s Vision AI Companion, accessible via the AI Button.
Activation: Users must accept the terms and conditions and allow Perplexity to access their microphones before using the AI voice component.

(Optional): For those who don’t want to use voice commands, the onscreen keyboard or USB keyboard can be used to search with the Perplexity TV App.
Ask for anything: Whether you want recommendations for Halloween entertainment or help with an everyday task, Perplexity knows the answer.

Availability
The Perplexity TV App is now available on all 2025 Samsung TVs and will be available on 2023 and 2024 TVs with the latest OS upgrade later this year. As a bonus, Perplexity is offering a free 12-month subscription to Perplexity Pro for all users. Simply scan the QR code on the Perplexity TV app to redeem.

To learn more, visit www.samsung.com