Your best targeting signal already lives in your CRM—past acceptances, declines, and engagement data. Most IR and corporate access teams build invite lists the same way every quarter: start with last year’s list, add a few new names, and send invites to everyone. The result is 50% acceptance rates and wasted time chasing investors who were never going to say yes. Use the data you already have to rank targets by likelihood to accept and engage, and watch your yes rates climb.
What You’ll Achieve
- A target score model that improves acceptance rates by 15–25%
- Faster invite cycles with fewer dead-end outreach attempts
- Data-driven prioritization that replaces gut-feel targeting
Build the Target Score Model
Start by identifying the features that predict whether an investor will accept your invitation and show up engaged. You already have most of this data—you just need to organize it.
Core features to track:
- Past acceptance rate: How many of your last five invitations did they accept? Investors who accepted three or more are high-probability targets. Investors who declined or ignored four or five are low-probability.
- Past attendance and engagement: Did they show up on time, ask substantive questions, stay for the full meeting, and request follow-up? Or did they no-show, join late and multitask, or ghost after the meeting? High-engagement investors score higher.
- Recency of last interaction: Investors who met with you in the last 90 days are warmer targets than those you haven’t spoken with in two years. Recency matters because relationships decay without ongoing contact.
- Investment thesis fit: Does their fund strategy align with your company profile? A growth fund covering your sector is a strong fit. A value fund focused on a different industry is weak fit. Use publicly available data (fund websites, 13F filings, sell-side lists) to score fit.
- AUM and ownership potential: Larger funds with the capacity to take meaningful positions score higher than small funds that can’t move the needle on your shareholder base. But don’t ignore emerging managers—they can become top holders over time.
- Decision-maker access: Are you reaching the portfolio manager or senior analyst (high value), or getting stuck with junior associates (lower value)? Track the seniority of past meeting attendees.
Weight features by your objective. Not all features matter equally, and the right weights depend on what you’re trying to accomplish:
- Discovery objective (meeting new investors): Weight thesis fit (30%), AUM (25%), decision-maker access (20%), past acceptance rate (15%), engagement (10%). You’re prioritizing investors who match your profile and have the capacity to become holders, even if you’ve never met them.
- Diligence objective (deepening existing relationships): Weight past engagement (35%), past acceptance rate (30%), recency (20%), decision-maker access (15%). You’re prioritizing investors who have shown consistent interest and engagement in past meetings.
- Maintenance objective (staying in touch with holders): Weight ownership status (40%), recency (25%), past acceptance rate (20%), engagement (15%). You’re prioritizing current holders and recent investors who need regular check-ins.
Calculate a score for each target. For each investor, multiply their score on each feature by the weight, then sum to get a total score from 0 to 100. Rank your full target list by score, and you have a data-driven priority order.
Construct Your Invite List
Now that you have scored and ranked your targets, use that ranking to build invite lists that maximize your acceptance rate and meeting quality.
Start with your top 20 by score. These are your highest-probability targets—investors who have accepted in the past, match your thesis, and have the capacity to matter. Invite them first, and give them priority access to prime meeting slots (in-person over virtual, preferred time zones, access to senior executives).
Add strategic wild cards. Scores predict probability, but they’re not perfect. Include 5 to 10 strategic adds—investors who score lower but represent important coverage gaps (a top fund in a geography you’re underweight, an emerging manager with strong sector expertise, a holder who just trimmed their position and needs re-engagement). These wild cards keep you from getting stuck in an echo chamber of the same 20 investors every quarter.
Tier your outreach. Don’t send all invitations at once. Send to your top tier (top 20 by score) first and give them 48 to 72 hours to respond. Once you’ve locked 60–70% of your target meeting count, send to tier two (next 20 by score) to fill remaining slots. This ensures your best targets get first access and you’re not over-committed if too many people say yes.
Optimize timing and messaging by segment. High-scoring targets who have accepted before can get shorter, more direct invitations: “We’d like to schedule a follow-up on Q3 results and FY26 guidance—are you available October 14 or 15?” Low-scoring or new targets need more context and value proposition: “We’re a $2B cybersecurity company that just posted 40% revenue growth and raised FY guidance. We’d value 30 minutes to share our roadmap and answer questions.” Test different subject lines and opening paragraphs by segment and track which versions book better.
Build a Feedback Loop
Target scoring isn’t a one-time exercise—it’s a continuous improvement process. After each event or campaign, update your data and refine your model.
Capture outcomes for every invitation. Track four outcomes: accepted and attended (best), accepted but no-showed (disappointing), declined (neutral data point), or no response (treat as decline). Log these outcomes in your CRM or spreadsheet so you can calculate updated acceptance rates for each investor.
Score meeting quality, not just attendance. After each meeting, score the quality on the dimensions that matter: seniority (did you get the PM or an associate?), engagement (did they ask questions and request follow-up?), and strategic fit (did the conversation advance your relationship?). Use these quality scores to adjust future targeting—an investor who accepts every invite but sends a junior associate who multitasks should score lower than an investor who accepts selectively but shows up engaged.
Update feature weights quarterly. Every quarter, review which features best predicted acceptance and engagement. If thesis fit was the strongest predictor this quarter, increase its weight. If AUM didn’t matter much (because small funds were just as likely to accept as large funds), reduce its weight. This keeps your model calibrated to current market conditions and your evolving investor base.
Share learnings across the team. After each major event or NDR cycle, run a 30-minute retro with your IR and access teams. What worked? Which segments over-performed or under-performed versus their scores? What messaging or timing changes improved acceptance rates? Document these insights and apply them to the next campaign. The teams that improve fastest are the ones that learn from every cycle.
Start Scoring Your Targets Today
Request a demo to see how WeConvene automatically scores and ranks investor targets based on acceptance history, engagement data, and thesis fit—so you can focus on high-probability meetings instead of guessing.