If you’re in B2B sales, marketing, or customer success, you’ve probably heard you should be tracking “account engagement.” You also probably know it’s not as easy as it sounds. This guide is for folks who want to use Lift-ai analytics to actually make sense of account engagement—without getting lost in a sea of data or buying into every shiny dashboard.
We’ll walk through the practical steps, what metrics actually matter, and what to skip. No fluff, no theory—just what works, what doesn’t, and how to keep your sanity.
Why bother tracking account engagement?
Let’s be real: not every account in your CRM is actually engaged. Tracking engagement tells you which companies are paying attention, who’s slipping away, and who’s just milking your content for free. Done right, this helps you:
- Prioritize outreach (talk to people who might actually buy)
- Reduce churn (catch “at risk” accounts before it’s too late)
- Spot upsell and expansion opportunities
But only if you track the right stuff and don’t waste time chasing vanity metrics.
Step 1: Get your data house in order
Before you even open Lift-ai, make sure you’ve got the basics sorted out. Otherwise, even the best tools will just spit out noise.
What you need:
- A clean account list: No duplicates, weird naming, or zombie accounts.
- User-to-account mapping: You need to know which users belong to which company. (If people sign up with Gmail addresses, you might have some cleanup to do.)
- Consistent tracking scripts: Make sure the Lift-ai tracking code is actually firing on the pages you care about—product, docs, pricing, etc.
Pro tip: If you’re not sure your data is clean, pull a random account and see if the activity history makes sense. Garbage in really does mean garbage out.
Step 2: Know what “engagement” actually means for you
Every company talks about engagement, but the details matter. Don’t just track what’s easy—track what actually signals interest or intent.
Ask yourself:
- What actions show a healthy account?
- Is it logging in regularly?
- Inviting teammates?
- Using key features?
- Reading support docs or ignoring them?
- What are red flags?
- Logins drop off
- No new activity in 30+ days
- Support tickets spike
Don’t just rely on pageviews or logins. Those can be empty calories—someone could be logging in every day and doing nothing.
Step 3: Configure Lift-ai for account-level tracking
Lift-ai is built for B2B, but you still need to set it up with account tracking in mind. Here’s how to avoid rookie mistakes:
1. Identify accounts, not just users
- Use Lift-ai’s account identification API to tie individual user actions back to company accounts.
- Wherever possible, send Lift-ai the account ID from your CRM or billing system—not just the company name (names change, IDs don’t).
2. Set up custom events
Don’t settle for tracking just logins or pageviews. Set up custom events for things like:
- Creating a project
- Upgrading a plan
- Inviting a user
- Downloading a key resource
3. Group by account in your dashboards
- In the Lift-ai UI, make sure you’re grouping activity by account, not just by user. This gives you the real picture, especially at renewal time.
Step 4: Pick the right engagement metrics (and ignore the rest)
There are a million things you could track, but only a handful really matter for account engagement.
Metrics that actually tell you something:
- Active users per account: Is usage spreading beyond one or two champions?
- Key feature usage: Are they using the things that make your product sticky?
- Frequency of activity: Are they logging in daily, weekly, or… never?
- Expansion signals: Adding users, increasing usage, accessing premium features.
- Support interactions: Are they reaching out more (bad) or less (maybe good)?
Metrics that usually waste your time:
- Raw pageviews: Doesn’t matter if they’re just refreshing the dashboard.
- Email opens: Easy to fake, easy to misinterpret.
- Time on site: Not helpful unless you know what they’re doing.
Pro tip: Pick 3-5 metrics you’ll actually check. More than that, and you’ll end up ignoring all of them.
Step 5: Build simple, actionable reports
Your goal isn’t to make a pretty dashboard no one reads. You want reports that tell you what to do next.
How to make it useful:
- Segment accounts: New, active, slipping, dormant.
- Highlight changes: Who’s trending up? Who’s dropping off?
- Set up alerts: Use Lift-ai to ping you (or your CSMs) when an account hits a risk threshold.
Example: Weekly “At Risk Accounts” report
- Accounts with a drop in active users >30% in the last 14 days
- Accounts with zero logins in the last month
- High-value accounts with a spike in support tickets
Don’t overcomplicate it. A simple spreadsheet or Slack alert beats a fancy BI tool that sits unused.
Step 6: Use engagement data to actually do something
This is where most teams fall down. Data is only useful if it leads to action.
What to do with what you find:
- Prioritize outreach: Focus on at-risk accounts for check-ins, QBRs, or personalized help.
- Celebrate healthy accounts: Find out what’s working and double down.
- Feed sales and marketing: Let sales know when accounts are heating up, or when a competitor’s “champion” goes dark.
What not to do:
- Don’t use engagement scores as the only signal for renewal or upsell. Sometimes the quiet accounts are happy, and the noisy ones are shopping around.
- Don’t pester active accounts just because they’re active. Sometimes the best thing you can do is get out of their way.
Step 7: Review, adjust, repeat
Account engagement isn’t set-and-forget. Your product, your accounts, and your team’s goals will change.
- Review your metrics every quarter.
- Drop what isn’t useful.
- Add new signals if you spot patterns.
If you’re not sure a metric is adding value, try going without it for a month. If no one misses it, it wasn’t that important.
A few honest pitfalls to watch for
- Overengineering: More tracking doesn’t always mean more insight. Start with the basics.
- Chasing “perfect” data: You’ll never have it. Get something good enough and iterate.
- Mistaking noise for signal: Not every dip in activity is a crisis.
- Ignoring context: A big customer going quiet after a big rollout might just be… using the product.
Keep it simple. Iterate.
Tracking account engagement with Lift-ai should help you do your job, not add more busywork. Don’t let dashboards or “AI-powered insights” distract you from what really matters: talking to your customers, spotting real problems, and helping your team win.
Start small. Measure what matters. Adjust as you go. The rest will take care of itself.