If you've got a mountain of business contacts and want your CRM to tell you who actually matters, you're not alone. Relationship scoring in Introhive promises to do the heavy lifting—surfacing your warmest connections, flagging neglected accounts, and maybe, just maybe, giving your team one less thing to argue about in the pipeline meeting. This guide is for admins, ops folks, or anyone tasked with making Introhive give you real insight instead of just another dashboard you ignore.
Let's break down how to actually set up automated relationship scoring in Introhive—without getting lost in the weeds or wasting time on things that don't move the needle.
What Is Automated Relationship Scoring (and Why Bother)?
Automated relationship scoring tries to answer a simple question: How strong is our connection with this person or company, really? Instead of gut feeling, it uses data—like how often you email, meet, or call—to spit out a score.
Why care? Because it gives you:
- A way to prioritize accounts and contacts that aren’t just “big logos”
- Early warnings if key relationships are fading
- Less hunch-based decision making (which, let’s be honest, is often just guessing)
But it’s not magic. A score won’t tell you everything. It’s a starting point, not a verdict.
Step 1: Prep Your Data and Decide What 'Relationship' Means for You
Before you even log in to Introhive, take a beat. The tool can only work with the data you feed it, and the scoring logic has to match your business reality.
What you need: - Clean, deduplicated contact and account data in your CRM - Email/calendar integration set up for your users (the more complete, the better) - Agreement on what a "good" relationship looks like for your team (frequency of contact? Meetings? Seniority?)
Pro tips: - If your CRM is a mess, fix that first. Garbage in, garbage out. - Don’t chase perfection—80% clean data beats endless cleanup. - Get buy-in from at least one sales or client leader—relationship scoring is wasted if nobody uses it.
Step 2: Make Sure Your Systems Are Connected
Introhive pulls data from your systems. If integrations aren’t set up, you’ll get blank scores or, worse, misleading ones.
Checklist: - Is your CRM (Salesforce, Dynamics, etc.) connected and syncing? - Is your email/calendar system (Outlook, Google Workspace) connected for all relevant users? - Are user permissions configured so Introhive can actually see the data?
What to skip:
Don’t bother with partial rollouts (“let’s just try it with one team for now”) unless you have a very small pilot group. Relationship scoring only works when you have enough data across your firm—otherwise, the results are skewed.
Step 3: Configure Relationship Scoring Rules
This is where most people get bogged down. Introhive has default scoring logic (typically weighting things like email frequency, meeting invites, and calendar overlap), but you can tweak this.
How to actually do it: 1. Go to the Admin or Settings area in Introhive. - Look for “Relationship Scoring” or “Scoring Configuration.”
- Review the default logic.
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Usually, it’s something like:
- +5 points for each email exchanged
- +10 for meetings
- Bonus for recent activity
- Decay for inactivity
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Decide what matters most to you.
- If meetings are your gold standard, bump that weight up.
- If emails are mostly noise, lower their impact.
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Ignore fields that don’t apply (for example, phone calls if nobody logs them).
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Set thresholds for “strong,” “neutral,” and “weak” relationships.
- Don’t overthink this. You can adjust later. Start with defaults if you’re unsure.
Pro tips: - Keep it simple at first. Fancy custom rules sound great, but they’re usually a pain to maintain. - Document your settings. Next year, you’ll forget why you set “strong” at 75 points. - If you’re not sure what to adjust, talk to your CSM or Introhive support. Don’t let this step block you for weeks.
Step 4: Test and Validate Scoring
This is the most ignored step—and it’s why a lot of relationship scoring projects flop. Don’t trust the scores blindly.
What to do: - Pick a handful of known accounts (good, bad, and in-between). - Look up their scores. Do they match reality? - Ask frontline users for their take. Does the “strong” relationship really feel strong? Or is it just a bunch of pointless email chains? - Adjust the weights if results don’t pass the sniff test.
What not to do: - Don’t rely on “sample data” alone. Use your actual, messy data. - Don’t expect scores to be perfect. You’re looking for “good enough to be useful.”
Pro tip:
If possible, check the scores against closed deals or lost clients from the past year. Do the numbers line up with your team’s experience? If not, keep tweaking.
Step 5: Roll Out to Users (and Actually Show Them the Scores)
Once you’re happy with the scoring, make sure your team can see and use the results. If it’s buried in a tab nobody checks, you’ve wasted your time.
How to roll out: - Add relationship score fields or columns to your CRM views or dashboards. - Train users on what the score means (and what it doesn’t mean). - Show examples: “This is what a strong relationship looks like in the system.” - Encourage action: flag weak relationships for follow-up, celebrate strong ones, etc.
Honest take:
Most teams ignore new fields unless you make it part of their workflow. Tie scores to something real—account reviews, pipeline meetings, or client check-ins.
Step 6: Monitor and Iterate
Your first version won’t be perfect. That’s fine—just don’t set it and forget it.
What to monitor: - Are users engaging with the scores? Or just ignoring them? - Any obvious errors or outliers? (e.g., the “strongest” relationship is with a former intern who left two years ago) - Feedback from the team—do they trust the numbers?
How to adjust: - Tweak scoring weights based on feedback every couple of months. - Prune out irrelevant data sources if they’re muddying the waters. - Periodically clean your contact and activity data.
Don’t:
Don’t let “perfect” be the enemy of “good enough.” Automated scoring will never capture every nuance of a relationship. Use it as a guide, not gospel.
What Works, What Doesn’t, and What to Skip
What actually works: - Keeping scoring simple and transparent - Reviewing scores with the team regularly - Using scores to flag neglected accounts
What doesn’t: - Overcomplicating the logic with a dozen custom rules - Expecting everyone to care about the score without context - Trusting the score to replace real human knowledge
What to skip: - Chasing every new data source (“let’s also score based on Twitter likes!”) - Endless debates about threshold numbers (just pick and move on) - Ignoring user feedback (“they’ll get used to it eventually” is wishful thinking)
Keep It Simple, Keep It Useful
Automated relationship scoring in Introhive can save you time and surface real insights—if you keep it practical. Start with the basics, involve your team, and don’t expect perfection. Iterate as you go. The goal isn’t to have a perfect algorithm; it’s to help your team spend more time with the people who matter, and less time guessing. If you stick to that, you’re already ahead of most.