Analytics
Analytics is where you decide whether your referral program is earning its keep — and where you find the lever to pull next. The dashboard moves from outcomes (who joined, how many converted, how much revenue followed) back through the funnel to behaviour (who saw the offer, who shared, on which channels). Read it in that order and a gap usually announces itself: plenty of impressions but few shares points at a weak incentive; strong first orders but thin repeat revenue points at retention, not acquisition.
You find these metrics in the Analytics tab. Pick a date range — last 7, 30, or 90 days, or a custom period — and the dashboard shows summary totals plus trends over time.
Best practice: Watch the ratio of successful referrals to shares and your subsequent referral revenue most closely. The first tells you whether shares actually convert (a fix for rewards or audience); the second tells you whether referred customers stick (a fix for retention). Revenue totals look good on a slide, but these two ratios are what you can act on.
Analytics are recorded from the moment the feature went live for your store. Data before that date is not available, so very early date ranges may look empty.
Which metrics matter, and what they mean
Some numbers are outcomes you report; a few are diagnostics you act on. This table sorts them by what each one tells you.
Total referrers
How many customers joined as referrers
Whether the program is being discovered at all
Successful referrals
Referrals that reached a rewarded purchase
The true output of the program — the number to grow
Shares
Share actions taken by referrers
Whether referrers act once they've joined
Entry-point impressions
How often your referral entry points were shown
Whether the program is visible enough to convert
Total referee revenue
Revenue from referred friends' orders
The top-line money the program brings in
First referral revenue
Revenue from each referee's first order
Acquisition value — how well the program wins new buyers
Subsequent referral revenue
Repeat-order revenue from the same referees
Retention value — whether referred customers stick
Welcome emails viewed
Invite emails opened (tracked by pixel)
Whether invites land and get seen
Share-channel performance
Which channels referrers use
Which share buttons to keep, promote, or drop
The two diagnostics worth watching above all others: share-to-referral conversion (do shares turn into rewarded purchases?) and subsequent revenue (do referred customers come back?).
Read the funnel: impressions → shares → conversions
A referral program is a funnel; the value of the dashboard is in the drop-off between stages, not any single total. Read it top to bottom:
Entry-point impressions — how many people saw the offer.
Shares — how many of them shared a link.
Successful referrals — how many of those shares became rewarded purchases.
Where the number falls off sharply is where your problem lives. Lots of impressions but almost no shares is a different problem from lots of shares but almost no conversions, and the dashboard is what tells them apart.
Diagnose by symptom
Read the funnel, find the cliff, then match the symptom to its likely cause. Change one thing at a time so you know what worked.
High impressions, few shares
The offer is seen but not compelling
Few impressions overall
The program is hard to find
Add entry points — post-purchase popup, landing page; see program visibility
Plenty of shares, few successful referrals
Friends click but don't buy
Sweeten the referee reward, lower or remove a minimum spend, check the referee popup
Strong first revenue, weak subsequent revenue
Referred customers convert but don't return
This is a retention problem, not a referral one — focus on post-purchase lifecycle, not the program
Few referrers joining
The audience is too narrow or the program is hidden
Widen the target audience and add entry points
One channel gets all shares, others none
The channel mix doesn't match your audience
Reorder or trim share channels toward what's used
When a fix involves real money — like a bigger reward — confirm it with an A/B test rather than rolling it out on a hunch.
What "good" looks like
Referral rates vary enormously by industry, price point, and how hard you promote the program. Judge your dashboard against itself over time rather than a borrowed target:
The trend beats the absolute. Shares and successful referrals climbing month over month matters more than hitting an external number.
Conversion should hold or rise as you scale. If shares grow but the share-to-referral rate falls, you are reaching less-engaged sharers — revisit the offer.
Subsequent revenue should build over time. Healthy repeat revenue from referees means you're acquiring customers who stay, which is the whole point.
Cost per referral should stay sane. A reward that wins on raw referral count can still lose money — read revenue alongside what each reward costs you.
For how these metrics translate into participation and conversion rates you can reason about, see referral sales strategy.
A worked example: reading the dashboard
All numbers are illustrative — not measured Bloop results.
Start at the top. Over 30 days the dashboard shows 8,000 entry-point impressions, 400 shares, and 40 successful referrals.
Find the cliff. Impressions to shares is 5% (400 of 8,000) — low. Shares to referrals is 10% (40 of 400) — healthy. The drop-off is at the share step: people see the program but don't share it.
Match the symptom. "High impressions, few shares" points at a weak or buried offer, not a conversion problem.
Pick one fix. Strengthen the referee reward and rewrite the widget copy to lead with it — one coordinated change to the share decision — and confirm it with an A/B test.
Re-read next month. Impressions hold at 8,000, but shares rise to 640 (8%) and successful referrals to 64. You then check subsequent referral revenue to confirm those referees are returning, not just converting once.
The number that mattered was never a total — it was the 5% drop-off that told you exactly which lever to pull.
Summary metrics
The top of the dashboard shows the headline numbers for the selected period:
Total referrers — how many customers have joined as referrers.
Successful referrals — referrals that reached a completed, rewarded purchase.
Total referrer revenue — revenue tied to orders that earned referrers a reward.
Total referee revenue — revenue from orders placed by referred friends.
Together these tell you whether your program is attracting referrers and turning shares into sales.
Revenue breakdown
Bloop separates referral revenue so you can see one-time versus repeat value:
First referral revenue — revenue from each referee's first order.
Subsequent referral revenue — revenue from a referee's repeat orders after the first.
Total referral revenue over time — a daily series of total referral-driven revenue.
Subsequent revenue shows whether referred customers keep buying, not just convert once.
Referee orders
Total referee orders — all orders from referred customers, first and repeat.
Total subsequent orders — repeat orders from referees over time.
Engagement and sharing trends
These trends show how customers move through the funnel before a purchase:
New enrolled referrers — how many referrers joined per day.
Shares — shares made by referrers in the period.
Welcome emails viewed — how often invite emails were opened, tracked by a pixel in the email.
Entry point impressions — how often your referral entry points (such as the widget) were shown.
Share channel performance — which channels referrers use to share.
Bloop records events such as referral link clicked, share channel clicked, referral link copied, welcome email opened, and entry point impression automatically once the program is live.
Common mistakes to avoid
Reading totals, ignoring ratios. Total revenue feels good but doesn't tell you what to fix. The drop-off rates between funnel stages do.
Peeking too early. A few days of data is noise. Let a date range gather real volume before you conclude a fix worked.
Acting on two changes at once. If you change the reward and the copy together, you can't tell which moved the needle. One lever, then re-read.
Chasing internet benchmarks. Referral rates vary wildly by store. Compare your dashboard against its own trend, not a borrowed number.
Confusing a retention problem with a referral one. Weak subsequent revenue is about whether customers return — the referral program already did its job by acquiring them.
Next steps
Adjust incentives in Referrer and referee rewards.
Tune who can refer in Target audience.
Confirm a fix before rolling it out with A/B testing.
Make sure the program is seen in making your referral program visible.
Get more shares with these ways to promote referral links.
Last updated