Your outbound team already has the strongest first-party intent signals they’ll ever need; acceptances, replies, profile views, message opens, and meeting responses. The problem is simple: they’re buried inside dashboards no one checks twice.

If you’re leading an outbound sales or sales-ops team, you’ve felt this pain.

You run LinkedIn outreach campaigns, track KPIs, buy new third-party intent data tools, but still end up guessing which accounts are actually ready to buy. Reps chase every connected prospect the same way, waste sequences on low-intent accounts, and miss the behavioral engagement metrics that signal real interest.

This guide shows you how to fix that by turning your everyday campaign data into an intent-based outbound strategy your team can act on immediately.

You will learn how to turn your standard campaign exports (acceptances, replies, meeting bookings) into a dynamic intent-scoring dashboard that lets your team instantly see, segment, and prioritize the accounts with the highest likelihood of conversion, so your sales team stops guessing and starts focusing outreach where buying intent is highest.

Traditional intent data misleads your outreach targeting

Everyone’s chasing intent data these days. It’s become one of those must-have line items for B2B sales and marketing teams because who doesn't want to know who’s in-market before they ever reach out.

And it's completely understandable; there’s real value in understanding market-level activity. It gives your team context: who’s hiring, who’s expanding, who’s talking about your category. 

But the challenge is that most external buyer intent signals stop at prediction, not proof.

They can tell you who might be interested, but not who actually is, and that's where things get tricky and where most SaaS teams get stuck chasing shadows.
A lot of AI-driven intent data models rely on third-party signals, things like:

• Website visits, pricing page visits
• Content consumption patterns across the web
• Job postings or funding announcements
• Search and ad engagement trends

On paper, these look like signs of readiness. In practice, they’re often too far upstream to predict real buying intent. 

 The latency and decay problem

Signals like content consumption and search trends suffer heavily from intent-signal timing / decay. By the time the data is aggregated, analyzed, and delivered to your team, the prospect’s interest may have already cooled or their decision-making window closed.

2. Interest is not intent 

• Broad activity: A company might be hiring or reading about your category, but that doesn’t automatically mean they’re ready to talk to your sales team or purchase your specific solution.
• Wasted sequences: LinkedIn outbound is already hard work and very expensive. Every time your sales reps chase a false signal, you burn sequences, time, and pipeline momentum by misallocating resources to a low-conversion target.

3. The attribution gap

Oftentimes, many of the "wins” reported from these tools are actually accounts that were already warmed up by your own marketing efforts (ads, email lists, content engagement). When a deal eventually closes, the intent data takes the credit, but it really just sold you back a lead your own marketing efforts already warmed up.

Now, this does not mean that external intent data is useless. It just means it should guide, not drive, your targeting. A better way to use buying intent data is as context and clues, rather than confirmation.

The real proof of buying interest isn’t on the open web; it’s already inside your own data. When a prospect accepts your connection, replies to your personalized message, or books a meeting, they are using their own effort to engage with you. This is the highest-fidelity, zero-latency signal of active purchase intent you can acquire.

The next step is to build a systematic way to capture, score, and act on these clear signals at the right time.

Your real buying signals live in your LinkedIn outreach data

You don't need another expensive, complex intent platform. Your highest buying signals are already being generated 24/7 by prospects reacting to your LinkedIn outreach. 

These metrics are superior because they are quantitative intent signals; direct, measurable actions taken in response to your company's value proposition and touchpoints with your ideal customer profile.

For example, the data inside your HeyReach dashboard isn’t just campaign reporting, it’s a real-time feed of first-party intent data that tells you who’s actually moving closer to a buying decision.

Three core metrics that map to buying intent, more sales teams should be tracking

Inside your HeyReach dashboard or your LinkedIn sales prospecting tool of choice, three key metrics directly indicate an account's willingness to engage and buy. These are the Linkedin outreach metrics you must export and map to build your intent-scoring system.

• Acceptance rate: This measures the percentage of connection requests accepted by accounts. A high acceptance rate is a strong indicator of prospects’ interest in your profile, industry, or the specific value prop mentioned in the connection message. It’s the first step of engagement.
• Positive reply rate: The percentage of accounts responding positively.For example, if you are getting responses like "tell me more," "send demo link," or expressing a problem you can solve. Positive replies indicate that your outreach message is connected to a current need or active pain point. Quantitatively, this is one of the strongest predictors of deal progression.
• Meetings booked: This measures the number of accounts that convert to a booked call directly from your sequence. It is the clearest quantitative signal of intent. A booked call means an account has moved from curiosity to active evaluation, increasing the likelihood of a close.

Build a high-intent scoring system with just three key LinkedIn metrics

You can instantly surface hot, warm, and cold accounts by applying simple IF-rules to your exported campaign data in Google Sheets.

The true power of first-party intent signals is their immediate utility. 

This is a simple framework for turning raw campaign data into a dynamic intent-scoring dashboard for Linkedin lead generation, enabling you to instantly prioritize high-intent accounts and execute targeted, personalized outreach to close deals faster.

Step 1. Export your data

The first step in building your high-intent account-scoring system is to export the raw campaign data to show exactly which accounts are ready for outreach. If you already use HeyReach for your LinkedIn sales outreach, you can do this in less than five minutes. Follow the following steps:

1. Navigate to the HeyReach dashboard
2. Filter by timeframe: Set the timeframe to cover the period you wish to analyze (e.g., the last 30 or 90 days).
3. Export the account list as CSV: Make sure the export includes:

• Account name/Company
• Prospect name
• Campaign name
• Acceptance status
• Reply status (Crucial, as you need to identify positive replies)

4. Meetings booked via tagged replies or CRM sync. This is not native, and you need to integrate your CRM with HeyReach for easy data sync.

5. Data hygiene tip: Before mapping, check that your export data is clean. Look for common issues like duplicate accounts, prospects who were prematurely removed, or mis-categorized replies.

Once exported, this raw data is the blueprint you will use to map, score, and begin the process of segmenting high-intent accounts in a dedicated Google spreadsheet

Step 2. Calculate your engagement rates

Once your CSV is imported into Google Sheets, create three quick formulas to measure engagement.

• To calculate acceptance rate = Accepts ÷ Requests sent
• To calculate reply rate = Replies ÷ Accepts
• Meetings = Number of booked calls or demos

These three engagement metrics mirror the buyer journey: acceptance (awareness), reply (interest), and meeting (evaluation). They’re also the cleanest first-party intent signals you can measure.

Step 3. Classify accounts with simple IF-rules

This step defines your lead scoring logic, turning your content engagement rates into actionable tiers (HOT, WARM, COLD).

To separate strong intent from weak engagement, use clear, measurable thresholds. We will use industry benchmarks as a strong starting point. 

Belkin’s 2024 LinkedIn outreach study, which analyzed over 20 million LinkedIn outreach campaigns, found that ~30% acceptance and ~10% reply rates are generally healthy benchmarks for LinkedIn outbound campaigns.

Here’s how to translate that into a basic scoring formula:

• HOT LEADS: Acceptance ≥ 30% and Reply ≥ 10%
• WARM LEADS: Acceptance ≥ 20% and Reply ≥ 5%
• COLD LEADS: Acceptance < 20% or Reply < 5%

These aren’t absolutes and should rather be used as starting points. Your sales team should tailor them based on your internal historical data, industry niche, and stakeholder expectations.

A ready-to-copy Google Sheet template

To make this easy, we’ve prepared a ready-to-copy Google Sheet you can duplicate and plug your HeyReach export into.
👉 Access the intent scoring template 

Timing and decay: the importance of reading signals while they’re still hot

Even the best lead scoring model loses power if you ignore signal timing and decay. A reply from the right accounts is only valuable if it’s acted upon immediately. To keep your system reliable, add this:

• Decay check: Use your Google Sheet's creation date column to see the gap between the initial acceptance/reply (when intent was shown) and the current date. A three-week-old "HOT" account from a large segment may need an immediate re-activation sequence rather than a standard AE handoff.

Segment high-intent accounts to focus on what actually converts

Segmenting your target accounts helps you clearly see where your outreach is resonating and where it’s missing the mark, allowing you to optimize campaign resources and refine messaging for maximum conversion.

Once you’ve built your intent scoring system, the next step is to analyze who’s showing up in each tier: Hot, Warm, and Cold, and why. This is where campaign data becomes decision intelligence.

You can achieve this level of analysis directly using simple filters or pivot tables in Google Sheets.

How to segment your outreach data

Filtering your data by common firmographics helps you interpret behavioral engagement metrics and adjust your strategy:

1. Segmentation by prospect role 

Grouping accounts by the prospect's job title or seniority reveals which groups are easiest to capture (Acceptance rate) and which lead to a conversation (Reply rate).

For example, let’s say your pivot table or data shows:

• SDRs: 40% acceptance, 9% reply
• Founders: 18% acceptance, 10% reply

This paints a clear picture:

• SDRs connect easily (high top-of-funnel engagement) but rarely convert to replies. They are likely not the decision makers or simply curious. Recommended action to take here: Downgrade the initial "HOT" tiering for SDRs unless a meeting is booked; focus sequences on referral asks, not hard selling.
• Founders are harder to reach but worth the effort once they engage; fewer, but higher-quality replies. Recommended action to take here: These are high-value, high-intent accounts. Prioritize them for higher-touch messaging and fast follow-up; ensure AE ownership of WARM/HOT leads immediately.

2. Segmentation by company size 

Company size often dictates the speed and complexity of the buying cycle.

• Small/Mid-market (10-50 Employees): If you see high accept/reply rates and quick conversions to the HOT tier, it signifies a short conversion cycle. Action: Deploy shorter sequences with highly focused value propositions. The goal is a quick meeting—no lengthy nurturing.
• Enterprise (500+ Employees): If these accounts show high accept rates but low initial reply rates, it suggests a need for internal alignment before responding. Action: Insert a nurture step (e.g., share a specific case study or resource via email/InMail) between sequence steps to build internal consensus.

3. Segmentation by industry

Intent behaviors are heavily influenced by industry norms. A Fintech prospect might require more proof points, while a Marketing Agency might respond better to quick growth hacks.

• Example: If accounts in the "E-commerce" industry consistently score WARM, their messaging might be too generic. Action: Use this segment's data to inform a new, highly-specific sequence using industry language for outreach personalization based on intent.

Use these insights to adjust your overall LinkedIn growth strategy from messaging, sequencing, and prioritization. Then, tie each pattern back to your ‘Hot/Warm/Cold tiers’ to guide decision-making:

• Hot segments = audiences that consistently hit or exceed your reply/meeting benchmarks.
• Warm segments = audiences that show interest but need stronger personalization.
• Cold segments = low engagement; consider excluding or retesting later.

Turn intent signals into action with tiered routing rules

Intent data only drives revenue when it activates immediate, differentiated action. 

Assigning clear ownership and specific effort levels to each intent tier (hot, warm, cold) helps you create efficient routing workflows that guarantee high-intent accounts receive appropriate high-touch follow-up immediately.

The simplest way to do this is to create a “Hot/Warm/Cold” routing matrix that defines how every tier should be handled inside your outbound motion.

Hot/Warm/Cold routing matrix to determine intent tiers

Your execution checklist for implementing tiered routing in HeyReach

Use this checklist to turn your Google Sheet analysis into operational workflows using HeyReach's native features and integrations:

1. Tag each account in HeyReach: Use HeyReach's tagging feature to categorize each prospect with clear tags like TIER_HOT, TIER_WARM, or TIER_COLD. This is your single source of truth for all follow-ups. You can also tag accounts by tiers in HeyReach once you’ve connected Claude to HeyReach through MCP server.
2. Establish automated hand-offs: Integrate HeyReach with your CRM (HubSpot) and Slack using Zapier or Make.

• Set up a rule: IF prospect receives the TIER_HOT tag in HeyReach, THEN send a priority Slack alert to the assigned AE and log a high-priority task in the CRM. This ensures AEs are instantly notified of the most ready-to-buy accounts.

3. Clarify ownership and SLAs: Formally assign ownership: AEs handle all HOT leads, SDRs focus on converting WARM leads, and automation manages COLD nurturing.

• Enforce a tight SLA for HOT accounts (e.g., AE must engage within 2 hours of the tag assignment) to maximize conversion when intent is highest.

4. Optimize sequence safety and volume: If a segment (e.g., all Enterprise accounts) moves into the HOT tier and triggers a large volume of activity, ensure your team adheres to safe limits for connection and message volume.

5. Review and re-sequence: Conduct a weekly review of the tier matrix performance to see which tiers had the highest booking rates.

• Adjust the initial thresholds (e.g., a 30% acceptance rate is too high for your industry) and resequence accounts that have decayed from WARM to COLD into a new, light-touch campaign.

Systemizing these follow-ups with tiered routing workflows ensures that your investment in intent-based outreach is spent only on the accounts that genuinely justify the effort.

Next steps: Run a weekly intent review to keep your buying signals fresh

Your prospects are constantly moving through their buyer’s journey, meaning a warm account this week could be cold next week, or conversely, a quiet prospect could suddenly enter the hot tier. To make sure your intent-based outbound strategy maintains peak efficiency, implement a simple, recurring review process.

Use this checklist every week to maintain the integrity of your High-Intent Account Identification System:

1. Review score/tier movement

• Re-export your campaign performance metrics from HeyReach and paste the data into your intent scoring Google Sheet.
• Check for significant score movement and tier changes. Were any COLD accounts reactivated to WARM, or did a WARM account fail to convert and drop back to COLD?

2. Audit account engagement:

• Review all accounts tagged as TIER_HOT. Has the AE made contact? Has the meeting been booked? If the account is still marked HOT after 7 days without a booked meeting, review the AE’s outreach and potentially re-assign or re-sequence with a higher-urgency message.
• Ensure newly engaged accounts are tagged correctly in HeyReach.
• Adjust SDR and AE ownership as needed.

3. Inspect sequence drop-offs

• Identify which tier segments are experiencing the highest mid-sequence drop-off rate. A high drop-off rate for WARM accounts might indicate that the messaging is too aggressive or the personalization is insufficient.
• Connect this data back to your segmentation analysis to see if a specific role or industry requires a different sequence path.
• Decide whether to re-sequence, adjust messaging, or move to a longer-term nurture.

4. Clean your data

• Remove duplicates or inactive accounts.
• Fill in missing replies or meeting info to maintain accurate scoring.
• Perform list hygiene for COLD accounts. If they have been COLD for over 60 days, mark them for removal from active campaigns to keep your sender accounts safe and your data clean. Re-enroll them in a quarterly nurture list instead.

5. Review routing alerts

• Verify that your routing workflows (Zapier/Slack/CRM alerts) are functioning correctly and that AEs are acting on the alerts within the defined SLA. A breakdown here means missed revenue opportunities.

6. Plan next week's actions

• Highlight the top HOT accounts for AE focus.
• Note: WARM accounts for SDR nurturing.
• Confirm COLD accounts are in automated sequences only.

Pro tip: Keep this under 15 minutes. A disciplined weekly check keeps your intent scoring engine accurate and actionable without overloading your team.

Use your sales outreach data to drive better account intelligence today.

The world of outbound sales is a high-stakes environment, and success is not defined by the volume of sequences you send.

Instead of guessing who’s ready to buy, leverage the clear, first-party intent signals already generated within your HeyReach campaigns or in your sales outbound tools and give your team a repeatable, data-driven framework so;

• Hot accounts get immediate, high-touch attention.
• Warm accounts receive personalized nurturing.
• Cold accounts are kept in the pipeline with low-touch automation.

The result will be a smarter, faster, and more predictable outbound sales engine that allows your team to focus on the accounts most likely to convert, all from the signals already hidden in your campaign data.

Start today by exporting your HeyReach campaign data and building your own intent-scoring dashboard.