Every company claims AI now. Your PPC challenge isn't awareness; it's credibility. We build campaigns that reach technical decision-makers who can evaluate your AI capabilities beyond the buzzwords, and business leaders who understand the ROI of implementing your solution.
AI is simultaneously the most hyped and most misunderstood technology category. Your PPC needs to navigate this gap between market excitement and buyer sophistication.
Every SaaS product claims 'AI-powered.' Your campaigns need to demonstrate specific, measurable AI capability, not generic claims. Technical credibility separates real AI companies from AI-washing.
Engineers evaluate your model architecture. CTOs assess integration fit. CEOs care about business impact. Your campaigns encounter all three with fundamentally different information needs.
AI solutions almost always require a proof-of-concept before purchase. Your PPC goal is to generate POC requests from qualified companies, not direct sales.
Enterprise AI evaluation involves data compatibility assessment, model validation, integration planning, and organizational change management. 6-18 month sales cycles are standard.
'AI platform' is too broad. 'AI-powered demand forecasting for retail' is a campaign. Every use case is a separate market with different buyers, different competition, and different value propositions.
Developer-focused AI tools sell through developer communities and product-led growth. Enterprise AI sells through direct sales and LinkedIn ABM. Same company, potentially two different GTM motions.
AI buying spans developer communities, enterprise evaluation, and technical content platforms.
Target CTOs, CDOs, and VP Engineering at companies with data infrastructure maturity. Sponsored Content with benchmark reports, case studies, and POC offers. LinkedIn is where enterprise AI purchasing decisions begin.
Use-case keywords: 'AI demand forecasting software', 'NLP customer service automation', 'computer vision quality inspection'. Each use case with dedicated landing pages showing relevant demos and case studies.
Product demo videos, technical architecture walkthroughs, and use-case-specific explainers. YouTube builds technical credibility with engineering leaders who evaluate through video content.
AI evaluations take months. Progressive remarketing with deeper technical content, customer case studies, and POC invitation offers nurtures prospects through extended evaluation.
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Get a Free Proposal →AI PPC is about reaching qualified buyers who can evaluate your technology credibly and have budget to implement.
Each use case gets its own campaign with specific keywords, audiences, and landing pages. 'AI for fraud detection in banking' is a campaign. 'AI platform' is not.
White papers, benchmark results, architecture documentation, and peer-reviewed references. AI buyers need technical proof. Marketing fluff kills credibility with this audience.
Campaigns optimized for POC requests, not demo requests. POC requests signal genuine evaluation intent and budget authority. Demo requests can come from students and researchers with no buying intent.
Track from content engagement through POC request, POC completion, contract negotiation, and signing. Measure pipeline ARR contribution per campaign.
Enterprise POC requests grew from 3 to 14/quarter. LinkedIn ABM campaigns targeting CDOs at Fortune 500 companies. 5 enterprise contracts signed. Average annual contract: ₹42L. Total new ARR: ₹2.1Cr.
Customer service automation demos grew 3x. Use-case-specific Google campaigns ('AI chatbot for ecommerce') outperformed product campaigns by 5x on conversion rate. Average deal size: ₹8L.
Manufacturing quality inspection POC requests grew from 1 to 8/quarter through LinkedIn campaigns targeting plant managers and quality heads. 3 annual contracts signed. Total ARR: ₹1.5Cr.
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Get My Free Proposal →Technical specificity. Instead of 'AI-powered analytics', say 'real-time anomaly detection using transformer models with 99.2% accuracy on manufacturing defect data.' Specific claims with verifiable benchmarks attract serious buyers and repel tire-kickers.
Depends on your GTM motion. Product-led growth (self-serve): target developers through Google and technical communities. Sales-led growth: target CTOs and CDOs through LinkedIn ABM. Most AI companies need both but at different ratios depending on product maturity.
₹30,000-1,50,000 per qualified POC request. Against annual contract values of ₹10L-1Cr, this is strong economics. The key metric is pipeline ARR:spend ratio, which should be 10:1 or higher.
Set expectations internally that PPC-originated deals close 6-18 months after first touch. Track pipeline value monthly as leading indicator. POC completion rate and contract conversion rate as lagging indicators.
Yes. Google campaigns for technical searches ('how to implement [specific AI technique]'), YouTube technical tutorials, and GitHub-linked content. Developer acquisition through PPC feeds product-led growth motions.
Essential. AI buyers need technical proof before engaging sales. White papers, benchmark reports, and architecture documentation are your campaign assets. PPC distributes this content to the right audience. Without substance behind the ads, click-to-conversion drops to near zero.
Strategy, platform recommendations, timelines, and pricing built around your business.
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Use-case-specific campaigns were the breakthrough. 'AI for fraud detection in banking' brought us exactly the right prospects. Generic 'AI platform' campaigns had been attracting researchers and students.
5 enterprise contracts from PPC-originated pipeline in the first year. Total new ARR: ₹2.1 Crore. LinkedIn ABM found CDOs at companies we'd been trying to reach through cold outreach for years.
The technical credibility approach resonated with our buyers. Benchmark results and architecture docs in campaigns attracted CTOs who could evaluate our technology properly. No more wasting demos on unqualified leads.
Get a free proposal with use-case targeting, technical content strategy, and projected pipeline ARR.