How to Use Intent Data

I’ve been using Trigify.io for 1.5+ years now. Now, I’ve been tracking 25+ LinkedIn profiles on it, mostly for my clients. And one thing is very clear to me: Posting on LinkedIn isn’t the hard part.  Tracking what happens after is. Most people stop at “posting consistently”. That’s where the real problem starts. What usually goes wrong... 1. Everyone tries to create content for their ICP – very few do it consistently – even fewer attract the right people 2. Some posts get engagement – likes – comments – profile visits 3. And then… nothing – no tracking – no follow-up – no system That’s wasted INTENT. What actually works (when you track it): 1. Lead magnet → warm outbound → Post a lead magnet → Track who engages with it → Enrich those profiles → Use that list for outbound You’re no longer cold. You’re starting with context. 2. Competitor & creator engagement → Track engagement on competitor posts → Or people consistently posting in your niche → Scrape those interactions → Enrich the data Now you’re reaching out to people who are already active in the problem space. 3. Keyword-based intent signals (underrated) → Track engagement around keywords like:    ~ “intent signals”    ~ “GTM Engineer”    ~ “RevOps” → Build lead lists from those conversations → Reuse them for:    ~ outbound    ~ content ideas    ~ account research Same signal. Multiple plays. Why I’ve stuck with Trigify.io, it’s not because it’s flashy. But how it turns LinkedIn activity into usable intent. Post-level tracking. Profile-level monitoring. Keyword-level listening. And now, workflows make this operational. Instead of exporting data, stitching tools, and manually following up, you can: - track engagement - enrich profiles - route data where it needs to go - trigger next steps automatically They’ve also been adding integrations around enrichment, sequencing, and data sync, which makes these workflows practical in real GTM setups. But the core idea stays the same: If you’re already creating content and doing outbound, you should be tracking who’s raising their hand. Otherwise, you’re guessing. And guessing doesn’t scale. This is the difference between posting content and building a system. Do you actually know who’s engaging with your content?

Sales and marketing leaders’ obsession with “intent” is undermining their Account-Based GTM strategy. Here are the 3 biggest mistakes GTM teams are making on intent (and how to use intent effectively): 1. Intent is not magic Unfortunately, intent has been marketed as if it’s magic. As if it can 100% accurately identify ALL companies that have a qualified opportunity. It cannot. Intent is simply an indication of interest and engagement on a *topic* related to the product you sell. At its best, vendors should utilize good sources and strong algorithms so that the level of confidence in the signal is clear. But often, in the interest of showing huge volumes of intent, vendors end up stretching the signal to cast as wide a net as possible and generate a large amount of false positives. 2. Intent is not your Ideal Customer Profile (ICP) I see this every day. Sales and Marketing teams get a list of high intent accounts and then “go after them.” This is counterproductive and wasteful because not all high intent accounts are in your ICP. The whole purpose of an account-based GTM is to align Sales and Marketing resources to accounts that have the highest LTV and thus generate the greatest enterprise value. This means being ultra clear on your ICP and avoiding the “intent temptation” of going after accounts that are interested in your solutions but are not in your ICP. Just because someone WANTS something doesn't mean they can or should buy it. 3. Intent should not be used in isolation from other data sets Intent only becomes powerful when it’s focused on your ICP and combined with other important data sets. Used in isolation, without other signals, you will never maximize your investment in intent. If tech companies want to increase the power and benefit of intent, they first need to combine intent with technographic data. Overlay the list of high-intent accounts with a list of companies that have the technologies your customers need to have and your hit rate on demand gen will improve significantly. The more robust solution to integrating intent into your broader GTM is to model it, with all other relevant data (firmographics, technographics, website engagement, Sales and Marketing engagement, etc) against closed won opportunities over the last 2 years. This will give a relative weighting for each data feature and intent keyword such that intent can be integrated into a more accurate score to represent propensity to buy soon. TAKEAWAY: Addressing the above issues are intended to arm you against what we’ve all heard many times, “This intent is BS, I called an account and they’re not ready to buy!” Don’t expect magic. Intent can't make a bad account great. But if you understand how intent relates to your ICP, and then use it in conjunction with other data sets, it becomes a powerful part of your account-based go-to-market strategy.

The difference between 2% and 15% reply rates isn't your messaging. It's your targeting. Let me explain: Random outreach looks like this: You search for: "VP of Sales at Series B companies" You get 1,000 names. You send the same message to everyone. You hope someone responds. Response rate: 2-3% if you're lucky. While signal-based outreach looks like this: You search for: "VP of Sales at Series B companies WHO are also..." → Hiring for their sales team right now  → Just raised funding in the last 90 days  → Recently added relevant tech to their stack You get 150 names. You send the same message (with context). Response rate: 12-15% because you reached out at the right moment. Same ICP. Same message structure. Completely different results. Here's why intent signals matter: Hiring = Active pain point exists  Funding = Budget just unlocked  Tech changes = They're in buying mode These aren't "nice to know" signals. They're "ready to buy" signals. And most outbound teams ignore them completely. The problem? Most databases only give you: ↳ Name ↳ Title ↳ Company ↳ Email They don't tell you WHEN to reach out. This is changing. Prospeo.io V2 launched this month What makes it different is the intent layer You can search for prospects based on: 1. Standard filters (title, company size, industry) 2. Intent signals (hiring, funding, tech stack, department growth) 3. Get verified contacts (emails + mobiles) in one search So instead of blasting 1,000 random prospects... You reach out to 150 prospects who are showing real buying signals. With triple-verified emails (98% deliverability) and direct mobiles (25-30% pickup rates). The shift: Stop asking: "Who should I reach out to?" Start asking: "Who's ready to buy right now?" Intent signals answer that question. ___________________________ P.S. What intent signals do you track before reaching out? Drop them below. Let's learn from each other.

Last quarter a client asked me which intent signal they should use. Hiring data? Funding? Website visits? I told them to use all of them, but not how they expected. Most people pick one signal, build a campaign around it, and pray. That's backwards. You don't know which signal predicts a response until you let the data tell you. Here's the framework we use across 50+ clients. Run 3 campaigns at once: 1. Entire TAM. No signals. Just firmographics. This is your baseline — and sometimes it wins. 2. Focused segments. One signal per campaign. Hiring SDRs. Recently funded. Using a competitor tool. 3. Trigger-based. Real-time events. Job posting today. Funding this week. Website visit yesterday. Now here's the move nobody talks about. Every positive response across all 3, take that company and run it through every signal source you have. Pull hiring data, tech stack, funding history, news, social activity. Everything. Look for patterns. Maybe the companies that respond all hired a VP of Sales in the last 90 days. Maybe they all use HubSpot. Maybe they all posted about a specific pain point on LinkedIn. You wouldn't have found that by guessing upfront. We also run a catchall workflow in Clay with Clayagent, every signal we can think of, just "what's notable about this company right now?" Sometimes the signal that predicts responses is something you'd never think to look for. Sometimes you genuinely don't know WHY someone responded. That's fine. Not every response has a readable signal. But the ones that do give you your next 10 campaigns. Stop picking signals from a menu. Let the data tell you what works.

Fixing your email copy won't save your outbound campaign if you're emailing the wrong people. I've watched 100+ outbound campaigns fail at ColdIQ (and the problem is almost never the messaging). Here's what I mean: Most companies just grab some list from Apollo, send out like a hundred cold emails, and hope they get a reply. They have no idea if these people actually need their solution. The fix? Intent data. You'll never be 100% sure, but these signals help you: - Target people who are actually in-market - Re-engage old lists when timing makes sense - Stop wasting time on prospects who'll never convert There are several categories of intent signals: 1/ First-Party Intent ↳ Data collected from YOUR business ecosystem. These are people who already know you exist. They're: - Using your product - Visiting your website - Engaging with your content - Subscribing to your newsletter Tools to track this: Website Visitors: Instantly.ai, Clay, Midbound, Vector 👻 Product Usage: Common Room, Pocus, Mixpanel, Amplitude Social Engagement: Teamfluence™, Trigify.io, Clay 2/ Second-Party Intent ↳ Data collected about your company, via partners. That would be prospects that interacted with: - One of your partners who has overlapping customers - Your brand through a partner site - like your G2 page if you're a SaaS Examples of platforms to uncover these signals include: - Champion Tracking: Clay, Common Room - Affinity Signals: Crossbeam, WorkSpan - Review Sites: G2, Capterra 3/ Third-Party Intent ↳ Data collection via external providers. This is public data that shows they might actually need what you're selling. Examples include: Hiring Trends: LoneScale, Mantiks, PredictLeads, Clay Tech Stack Changes: BuiltWith, Similarweb, HG Insights, Clay Funding Events: Crunchbase, PitchBook, Owler - A Meltwater Offering, Clay Custom AI Agents: Relevance AI, Claygent, Apify We use Clay to build most of these workflows: → Filter for buying signals → Enrich contacts in real-time → Combine multiple data sources → Score and segment dynamically Better targeting = better reply rates = better pipeline. P.S: What intent signals are you tracking in your GTM motion right now?

Intent data is a scam, if you treat it like magic. Here's the playbook most teams run: Buy a subscription. Get a flood of "high intent" alerts. Push the list to sales. Watch it gather dust. Here's why: A single signal is worthless. One review category visit? Could be a competitor, a bored analyst, or a bot. Sales calls, gets ghosted, and decides intent data is a hoax. The real move is convergence. You want three or more signals, different sources, close together in time, real people attached. Pricing page visit G2 review LinkedIn job change Recent funding Same week. Stack your signals like this: 1. Only focus on ICP-fit accounts. 2. Layer in account signals, hiring, funding, tech changes. 3. Add contact-level signals. 4. Check recency. Last 7 days is hot. Six weeks ago is an ice cube. Score it by tiers: Tier 1: All the boxes ticked, all signals firing, all in the past week. Immediate, personalized outreach. Tier 2: A couple signals, some fit. Nurture and watch. Tier 3: Weak or stale signals. Do nothing. Intent only works if you treat it like intelligence, not leads. Convergence is the only way sales will trust the data, and the only way you'll ever see pipeline move. Stop buying magic beans. Start building signal convergence. That's how you make intent work.

If 2024 taught us anything about Cold Email, it’s this: 👇 General ICP Outreach isn’t enough to drive results anymore. With deliverability getting tougher every day, there’s only one way to make outbound work: → Intent-Based Targeting Here’s how we do it at SalesCaptain to book 3x more demos ⬇️ Step 1️⃣ Identify High-Intent Triggers The goal? Find prospects showing buying signals. ✅ Website visits – Someone browsing pricing or case studies? (We use tools like RB2B, Leadfeeder, and Maximise.ai). ✅ Competitor research – Tools like Trigify.io reveal when prospects engage with competitor content. ✅ Event attendance – Webinar attendees or industry event participants often explore new solutions. (DM me for a Clay template on this) ✅ Job changes – Platforms like UserGems 💎 notify us when decision-makers start new roles (a prime buying window). ⚡️ Pro Tip: Categorize triggers: → High intent: Pricing page visits → Medium intent: Engaging with case studies This helps prioritize outreach for faster conversions. Step 2️⃣ Layer Intent Data with an ICP Filter Intent data alone isn't enough, you need to ensure the right audience fit. Tools like Clay and Clearbit help us: ✅ Confirm ICP fit using firmographics ✅ Identify the right decision-makers ✅ Validate work emails ✅ Enrich data for personalized messaging ⚡️ Key Insight: Not everyone showing intent fits your ICP. Filter carefully to avoid wasted resources. Step 3️⃣ Hyper-Personalized Outreach Golden Rule: Intent without context is meaningless. Here’s our outreach formula: 👀 Observation: Reference the trigger (e.g., webinar attended, pricing page visit) 📈 Insight: Address a potential pain point tied to that trigger 💡 Solution: Share how you’ve helped similar companies solve this pain 📞 CTA: Suggest an exploratory call or share a free resource ⚡️ Pro Tip: Use tools like Twain to personalize at scale without landing in spam folders. 📊 The Results? Since focusing on intent-based outreach, we’ve seen: ✅ 3x Higher Demo Booking Rates 📈 ✅ 40% Reduction in CPL (focusing on quality over quantity) ✅ Larger Deals in the Pipeline with higher-quality prospects It’s 2025. Let’s build smarter, more profitable campaigns. 💡 Do you use intent signals in your outreach? Drop me a comment below! 👇

Imagine only cold emailing leads who WANT to buy from you… The closest way to do so? Leveraging buying signals: The idea is that these signals help you: - find relevant reasons to initiate contact - re-activate existing prospects at the perfect moment - surface new challenges to address in your messaging … and much more. There are several categories of signals: 1️⃣ First-Party Signals ↳ = Intent data gathered from your own business ecosystem. These are prospects who already know you, actively taking steps like: - utilizing your product - browsing your website - subscribing to your email list - interacting with your brand on social platforms Platforms that help you capture these signals include: 1. LinkedIn Signals: Clay, Expandi.io, Trigify.io, Jungler 2. Website Visitors: Instantly.ai, Clay, Midbound, Vector 👻 3. Product Usage: Common Room, Mixpanel, Pocus, PostHog 4. Call Transcripts: Attention, Fireflies, Claap 5. Gated Content: Distribute, Gamma 2️⃣ Second-Party Signals ↳ = Intent data sourced from your ecosystem, shared by partners. Generally, prospects who have engaged with: - your brand on a partner platform (e.g: checking out your listing on G2) - your company, while employed at a different organization - a partner of yours with an overlapping customer base Examples include: 6. Champion Tracking: Clay, Common Room, Unify, UserGems 7. Affinity Signals: Crossbeam, Reveal, The Swarm 🔆, PartnerStack 8. Ad Engagement: Fibbler, ZenABM, Factors AI 9. Software Marketplaces: G2, Capterra, ColdIQ 3️⃣ Third-Party Signals ↳ = Intent data sourced from external providers. Thus, public signals indicating companies might benefit from your solution. Examples include: 10. Technographic Data: Clay, PredictLeads, HG Insights, BuiltWith, Similarweb 11. Funding Announcements: PredictLeads, lemlist, Clay, Crunchbase, Owler, PitchBook, 12. Web Data Agent: Claygent, Parallel Web Systems, Tavily, Common Room, Unify, Linkup, Perplexity, Manus AI 13. Job Openings: Common Room, PredictLeads, Clay, LoneScale, Mantiks, TheirStack, Lemlist 14. Custom Scraping: Apify, Firecrawl, Claygent, Instant Data Scraper 15. News Monitoring: PredictLeads, Google News, Exa 16. Ads Activity: Apify, Adyntel, Ahrefs 17. Firmographic Data: Prospeo, Wiza, Exa, DiscoLike 18. Lookalike Search: PredictLeads, DiscoLike P.S: What’s your preferred tool for monitoring buying signals?

98% of your website visitors leave without ever filling out a form. You’re leaving millions in pipeline on the table simply because you can’t see who they are. Most teams settle for "anonymous page views", but AI-Native Growth leaders build an automated deanonymization outbound engine. Here is the exact 6-step playbook to turn silent traffic into closed-won deals using Warmly, Clay, Claude, HeyReach.io, Instantly.ai, and Nooks: Step 1: Unmask the Traffic Stop guessing. Use Warmly to identify the humans behind the IP addresses. -Company-level: Who is browsing? -Contact-level: Which specific stakeholder is clicking? -Context: Track pages viewed, frequency, and recency to gauge intent. Step 2: Centralize the Signal Don’t let data sit in a silo. Route every visitor signal directly into Clay. Create a single source of truth for every company and contact. Preserve the "Why" (timestamps and specific URLs) so your outreach isn't generic. Step 3: The Enrichment Layer Raw data is useless. Use Clay to pull the full picture: -Company: Industry, headcount, and tech stack. -Contact: Current role, seniority, and verified work emails. Step 4: AI-Powered Scoring Not all traffic is equal. Use the "Use AI" column in Clay (powered by Claude) to categorize visitors instantly: -Tier 1: Perfect ICP fit + high intent signals. -Tier 2: Good fit + moderate activity. -Tier 3: Information gatherers. -Disqualified: Competitors or irrelevant roles. Step 5: Expand the Buying Committee If a Director is browsing, their VP is likely thinking about the problem too. Use Clay to find additional Decision Makers at your target companies. Pull their emails and phone numbers to surround the account. Step 6: The Multi-Channel Execution Match your effort to the lead's value: -Tier 1 (High Priority): Immediate cold calls via Nooks + automated LinkedIn/Email via Instantly and HeyReach. -Tier 2 & 3: Scaled, automated email sequences in Instantly based on the specific pages they visited. The "Contact Us" form is a relic. The future of growth is identifying intent before the lead even says hello. Found this useful? Follow me for more AI Growth & Marketing Playbooks.

Your team has 400 "high intent" accounts this week. Sales will call 8. The other 392 are noise. Intent data isn't a pipeline problem. It's a triage problem. Here's the scoring model I build for GTM teams: Tier 1 (call same day): Intent spike + ICP match + no recent CRM activity + economic buyer role. Route directly to AE. Tier 2 (enroll in sequence): Intent spike + ICP match + no CRM history. Priority outbound sequence, not generic nurture. Tier 3 (suppress): Intent spike but wrong firmographics, existing customer, or already in an active deal stage. Don't touch — you're just creating noise for the reps. The filter before any of this: define your firmographic floor. Industry, headcount range, revenue range, tech stack. Until you have that, "high intent" is just a vendor-defined label that means nothing. Without triage, reps waste hours on accounts that will never move. With it, they're spending 80% of their time on the 20% most likely to convert. That's the system. It doesn't require a new tool. It requires a working session and someone willing to make a call on what good looks like. #IntentData #RevOps #DemandGen #SalesOps #GTM