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Google Ads
| Campaign | Spend | Claimed | Actual (vs Claimed) | Gap |
|---|---|---|---|---|
| Brand | US | Search - Exact | $18,250.50 | $64,500.00 | $51,200.00 | +13.3k(26%) |
| Non-Brand | US | Search - Exact | $32,500.00 | $78,000.00 | $54,650.00 | +23.4k(43%) |
| Shopping | US | PMax | $45,000.00 | $180,000.00 | $125,500.00 | +54.5k(43%) |
| YouTube | Remarketing | 14d | $7,200.00 | $22,000.00 | $17,850.00 | +4.2k(23%) |
| Display | Retargeting | 7d | $9,500.00 | $34,000.00 | $27,500.00 | +6.5k(24%) |
| Competitor | US | Search | $11,350.00 | $38,000.00 | $29,600.00 | +8.4k(28%) |
Meta Ads
| Campaign | Spend | Claimed | Actual (vs Claimed) | Gap |
|---|---|---|---|---|
| Prospecting | Advantage+ | US | $15,800.00 | $62,000.00 | $41,200.00 | +20.8k(50%) |
| Retargeting | 7 Day | US | $9,800.00 | $36,000.00 | $28,950.00 | +7.0k(24%) |
| Reels | Broad | US | $26,800.00 | $92,000.00 | $71,500.00 | +20.5k(29%) |
| Catalog Sales | DPA | Retargeting | $13,400.00 | $52,000.00 | $41,850.00 | +10.2k(24%) |
| Collections | DPA | Prospecting | $8,900.00 | $28,000.00 | $21,300.00 | +6.7k(31%) |
| Video Views | Prospecting | US | $12,250.00 | $34,000.00 | $25,100.00 | +8.9k(35%) |
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LTV by First-Touch Source
30/60/90-day LTV by first-touch channel. Totals are weighted by cohort size.
Quick insights (click to drill down)
Highest 90-day LTV
klaviyo / flow LTV90 $138.07 on 856 clients.
Largest cohort
reddit.com / referral acquired 1,538 customers · LTV90 $113.93.
Fast payback (front-loaded)
$40.34 in 30d (62% of 90d) via shop / marketplace.
Customers40,186Rev 30d$2,226,228.79Rev 60d$3,215,377.00Rev 90d$4,031,727.96LTV 30d$55.40LTV 60d$80.01LTV 90d$100.33
- Klaviyo856$64,236.61$93,656.61$118,179.73$75.06$109.42$138.07
- Other835$61,718.20$91,131.18$113,983.45$73.92$109.14$136.51
- Other514$36,865.27$52,844.89$67,408.07$71.72$102.82$131.16
- Snapchat816$53,822.83$81,754.30$105,383.94$65.96$100.19$129.15
- WhatsApp771$52,837.54$77,470.59$97,958.90$68.55$100.61$127.05
- Mailchimp595$40,622.60$57,545.44$72,051.96$68.25$96.80$121.09
- Other686$43,856.03$64,925.83$79,329.98$63.94$94.67$115.71
- GooglePaid612$39,688.20$56,753.37$69,971.64$64.89$92.75$114.35
- Reddit1,538$98,256.54$136,997.86$175,215.92$63.89$89.06$113.93
- Amazon1,021$58,538.08$91,741.71$116,057.18$57.34$89.86$113.69
- TikTok730$45,346.57$64,718.72$81,015.79$62.11$88.67$111.00
- Bing598$36,440.97$52,671.82$65,090.51$60.92$88.05$108.84
- Other962$54,904.49$79,554.97$101,640.18$57.06$82.69$105.65
- Twitter764$46,665.64$67,072.09$80,538.67$61.08$87.81$105.42
- YouTube997$58,318.20$83,936.26$105,017.12$58.51$84.16$105.33
- Other1,036$60,367.93$83,920.68$108,570.40$58.27$81.00$104.85
- Meta825$45,710.43$69,461.69$86,266.80$55.44$84.80$104.54
- DuckDuckGo797$48,100.79$67,349.74$82,777.52$60.35$84.50$103.86
- Other984$56,461.63$83,018.10$100,219.71$57.37$84.39$101.85
- Meta833$49,641.00$68,462.77$84,552.89$59.59$82.20$101.50
- Other270$15,772.39$22,140.56$27,207.34$58.42$82.00$100.77
- Other644$37,984.87$52,276.22$64,727.93$58.98$81.17$100.19
- Other1,008$51,758.76$78,349.24$100,596.15$51.35$77.70$99.60
- Meta522$28,516.90$41,023.90$51,765.58$54.62$78.57$99.16
- GooglePaid864$49,965.72$69,255.20$86,007.72$57.83$80.15$99.08
- Untagged680$37,483.02$53,058.17$66,677.76$55.12$78.62$98.05
- GooglePaid791$43,157.73$60,116.05$77,215.00$54.55$75.98$97.62
- Other691$37,705.49$52,427.55$65,805.78$54.54$75.85$95.20
- Taboola1,418$68,130.67$105,803.04$134,598.39$48.04$74.62$94.92
- Pinterest623$32,392.07$46,167.19$58,407.43$52.00$74.12$93.77
- Other1,160$56,637.48$83,345.47$108,207.46$48.83$71.86$93.28
- Discord309$16,877.12$23,022.85$28,797.65$54.62$74.55$93.22
- Other1,010$47,343.78$73,462.98$94,050.57$46.90$72.74$93.17
- Other840$45,286.22$61,477.48$77,556.07$53.90$73.19$92.33
- Other841$43,068.25$62,425.40$77,529.23$51.20$74.23$92.20
- Linktree167$9,313.43$12,563.32$15,376.24$55.78$75.22$92.07
- Telegram497$25,064.85$36,942.98$45,738.19$50.42$74.33$92.01
- Quora878$47,251.34$65,034.60$79,582.70$53.83$74.09$90.65
- Other407$19,997.74$29,327.83$36,752.76$49.14$72.06$90.32
- Bing744$37,135.52$52,604.85$66,086.94$49.93$70.72$88.86
- Meta478$24,839.72$33,861.72$42,409.37$51.94$70.82$88.72
- Other608$28,925.34$42,726.49$53,828.86$47.59$70.28$88.57
- GooglePaid676$33,426.79$48,755.94$59,784.53$49.46$72.11$88.43
- LinkedIn767$38,323.63$54,712.92$67,579.77$49.97$71.35$88.12
- Other834$39,809.51$57,925.47$71,363.88$47.73$69.46$85.56
- TikTok392$19,026.57$27,057.60$33,463.75$48.53$69.05$85.38
- Outbrain846$35,646.49$55,575.66$71,351.33$42.12$65.70$84.33
- Yahoo849$39,321.22$57,393.11$71,309.49$46.31$67.61$83.98
- Other447$20,654.10$29,680.72$37,233.61$46.22$66.36$83.28
- Other210$10,148.12$13,862.07$17,224.41$48.33$66.01$82.97
- YouTube498$23,164.98$32,558.02$40,590.28$46.53$65.40$81.54
- Other371$17,434.66$24,554.02$29,993.97$46.98$66.19$80.83
- Other548$24,643.58$35,033.20$44,148.38$44.97$63.92$80.58
- TikTok222$10,348.57$14,805.54$17,846.60$46.61$66.66$80.39
- Etsy387$17,338.72$25,129.81$31,060.33$44.79$64.94$80.25
- Amazon104$4,802.96$6,648.89$8,177.30$46.19$63.93$78.61
- Other229$10,322.09$14,826.79$17,553.09$45.10$64.79$76.67
- Yahoo149$6,765.98$9,165.03$11,257.04$45.41$61.51$75.55
- Other358$14,855.77$21,407.11$26,515.04$41.47$59.78$74.05
- Other79$3,187.09$3,883.39$5,119.68$40.34$49.16$64.81
LTV is calculated as revenue per acquired client within 30/60/90 days of first touch. Cohorts are grouped by first-touch channel; “Direct” can be hidden.
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Who boosts whom? (A influences finishing on B)
Sorted by Expected extra B purchases = Δ of B chance × Purchases with A.
Show pairs where A is…
…and where B is…
Influence (A → B)
Expected extra B purchases
Lift ×
Seen in
Per 100 with A: +8.0kPurchases with A: 9,331A & finished on B: 8,210B base rate: 15.4%
747.1k
estimated incremental B’s
11.10
8,210
When A is present, shoppers are 11.10× more likely to finish on B (≈ 88% vs 7.9%), seen in 8,210 purchases — roughly +8.0k extra B’s per 100 with A.
Chance of finishing on B when A happened88%
Chance of finishing on B when A did NOT happen7.9%
Per 100 with A: +8.8kPurchases with A: 6,940A & finished on B: 6,940B base rate: 18%
611.4k
estimated incremental B’s
8.40
6,940
When A is present, shoppers are 8.40× more likely to finish on B (≈ 100% vs 11.9%), seen in 6,940 purchases — roughly +8.8k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen11.9%
Per 100 with A: +8.5kPurchases with A: 6,535A & finished on B: 6,535B base rate: 21%
552.7k
estimated incremental B’s
6.48
6,535
When A is present, shoppers are 6.48× more likely to finish on B (≈ 100% vs 15.4%), seen in 6,535 purchases — roughly +8.5k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen15.4%
Per 100 with A: +8.9kPurchases with A: 5,972A & finished on B: 5,972B base rate: 16.7%
529.1k
estimated incremental B’s
8.77
5,972
When A is present, shoppers are 8.77× more likely to finish on B (≈ 100% vs 11.4%), seen in 5,972 purchases — roughly +8.9k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen11.4%
Per 100 with A: +4.3kPurchases with A: 11,065A & finished on B: 6,492B base rate: 20.2%
478.7k
estimated incremental B’s
3.81
6,492
When A is present, shoppers are 3.81× more likely to finish on B (≈ 58.7% vs 15.4%), seen in 6,492 purchases — roughly +4.3k extra B’s per 100 with A.
Chance of finishing on B when A happened58.7%
Chance of finishing on B when A did NOT happen15.4%
Per 100 with A: +9.0kPurchases with A: 4,103A & finished on B: 4,103B base rate: 13.8%
368.7k
estimated incremental B’s
9.85
4,103
When A is present, shoppers are 9.85× more likely to finish on B (≈ 100% vs 10.1%), seen in 4,103 purchases — roughly +9.0k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen10.1%
Per 100 with A: +2.2kPurchases with A: 12,708A & finished on B: 4,824B base rate: 18.6%
281.2k
estimated incremental B’s
2.40
4,824
When A is present, shoppers are 2.40× more likely to finish on B (≈ 38% vs 15.8%), seen in 4,824 purchases — roughly +2.2k extra B’s per 100 with A.
Chance of finishing on B when A happened38%
Chance of finishing on B when A did NOT happen15.8%
Per 100 with A: +8.0kPurchases with A: 3,378A & finished on B: 3,378B base rate: 22.8%
270.0k
estimated incremental B’s
4.98
3,378
When A is present, shoppers are 4.98× more likely to finish on B (≈ 100% vs 20.1%), seen in 3,378 purchases — roughly +8.0k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen20.1%
Per 100 with A: +9.4kPurchases with A: 2,425A & finished on B: 2,425B base rate: 8.7%
226.8k
estimated incremental B’s
15.47
2,425
When A is present, shoppers are 15.47× more likely to finish on B (≈ 100% vs 6.5%), seen in 2,425 purchases — roughly +9.4k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen6.5%
Per 100 with A: +542.80Purchases with A: 39,837A & finished on B: 5,205B base rate: 9.8%
216.2k
estimated incremental B’s
1.71
5,205
When A is present, shoppers are 1.71× more likely to finish on B (≈ 13.1% vs 7.6%), seen in 5,205 purchases — roughly +542.80 extra B’s per 100 with A.
Chance of finishing on B when A happened13.1%
Chance of finishing on B when A did NOT happen7.6%
Per 100 with A: +2.2kPurchases with A: 9,856A & finished on B: 4,110B base rate: 22.2%
213.6k
estimated incremental B’s
2.08
4,110
When A is present, shoppers are 2.08× more likely to finish on B (≈ 41.7% vs 20%), seen in 4,110 purchases — roughly +2.2k extra B’s per 100 with A.
Chance of finishing on B when A happened41.7%
Chance of finishing on B when A did NOT happen20%
Per 100 with A: +814.40Purchases with A: 19,335A & finished on B: 2,222B base rate: 4.9%
157.5k
estimated incremental B’s
3.43
2,222
When A is present, shoppers are 3.43× more likely to finish on B (≈ 11.5% vs 3.3%), seen in 2,222 purchases — roughly +814.40 extra B’s per 100 with A.
Chance of finishing on B when A happened11.5%
Chance of finishing on B when A did NOT happen3.3%
Per 100 with A: +1.4kPurchases with A: 8,140A & finished on B: 1,898B base rate: 10.7%
112.1k
estimated incremental B’s
2.44
1,898
When A is present, shoppers are 2.44× more likely to finish on B (≈ 23.3% vs 9.5%), seen in 1,898 purchases — roughly +1.4k extra B’s per 100 with A.
Chance of finishing on B when A happened23.3%
Chance of finishing on B when A did NOT happen9.5%
Per 100 with A: +296.10Purchases with A: 37,343A & finished on B: 4,461B base rate: 10.1%
110.6k
estimated incremental B’s
1.33
4,461
When A is present, shoppers are 1.33× more likely to finish on B (≈ 11.9% vs 9%), seen in 4,461 purchases — roughly +296.10 extra B’s per 100 with A.
Chance of finishing on B when A happened11.9%
Chance of finishing on B when A did NOT happen9%
Per 100 with A: +611.70Purchases with A: 17,491A & finished on B: 2,448B base rate: 8.9%
107.0k
estimated incremental B’s
1.78
2,448
When A is present, shoppers are 1.78× more likely to finish on B (≈ 14% vs 7.9%), seen in 2,448 purchases — roughly +611.70 extra B’s per 100 with A.
Chance of finishing on B when A happened14%
Chance of finishing on B when A did NOT happen7.9%
Per 100 with A: +159.00Purchases with A: 11,363A & finished on B: 1,544B base rate: 12.2%
18.1k
estimated incremental B’s
1.13
1,544
When A is present, shoppers are 1.13× more likely to finish on B (≈ 13.6% vs 12%), seen in 1,544 purchases — roughly +159.00 extra B’s per 100 with A.
Chance of finishing on B when A happened13.6%
Chance of finishing on B when A did NOT happen12%
To view insights like this for your own site, book a demo.
Predict revenue.
Track campaigns across search, social, and offline channels. Create confident predictions of revenue forecasts. Merge marketing analytics with effective data science. Get the big picture you need, with support tailored to complex brand campaigns.
Even Attribution — Platforms
Equal credit per touch event between previous and current purchase. “Direct” only when no eligible touches exist.
Platform
Orders
Revenue
Order %
Revenue %
Orders
34.7%
Revenue
36.5%
Orders
20.5%
Revenue
20.7%
Orders
14.5%
Revenue
13.8%
Orders
12%
Revenue
9.6%
Orders
6%
Revenue
6.4%
Orders
3.5%
Revenue
3.7%
Orders
1.9%
Revenue
2%
Orders
1.9%
Revenue
1.9%
Orders
1.2%
Revenue
1.3%
Orders
1.1%
Revenue
1.1%
Orders
0.6%
Revenue
0.7%
Orders
0.6%
Revenue
0.6%
Orders
0.5%
Revenue
0.5%
Orders
0.4%
Revenue
0.4%
Orders
0.3%
Revenue
0.3%
Orders
0.3%
Revenue
0.3%
Total Orders Credit:3,171.200
Total Revenue Credit:$355,055.00
To view insights like this for your own site, book a demo.
Agencies
Automate reporting.
Google Ads
| Campaign | Spend | Claimed | Actual (vs Claimed) | Gap |
|---|---|---|---|---|
| Brand | US | Search - Exact | $18,250.50 | $64,500.00 | $51,200.00 | +13.3k(26%) |
| Non-Brand | US | Search - Exact | $32,500.00 | $78,000.00 | $54,650.00 | +23.4k(43%) |
| Shopping | US | PMax | $45,000.00 | $180,000.00 | $125,500.00 | +54.5k(43%) |
| YouTube | Remarketing | 14d | $7,200.00 | $22,000.00 | $17,850.00 | +4.2k(23%) |
| Display | Retargeting | 7d | $9,500.00 | $34,000.00 | $27,500.00 | +6.5k(24%) |
| Competitor | US | Search | $11,350.00 | $38,000.00 | $29,600.00 | +8.4k(28%) |
Meta Ads
| Campaign | Spend | Claimed | Actual (vs Claimed) | Gap |
|---|---|---|---|---|
| Prospecting | Advantage+ | US | $15,800.00 | $62,000.00 | $41,200.00 | +20.8k(50%) |
| Retargeting | 7 Day | US | $9,800.00 | $36,000.00 | $28,950.00 | +7.0k(24%) |
| Reels | Broad | US | $26,800.00 | $92,000.00 | $71,500.00 | +20.5k(29%) |
| Catalog Sales | DPA | Retargeting | $13,400.00 | $52,000.00 | $41,850.00 | +10.2k(24%) |
| Collections | DPA | Prospecting | $8,900.00 | $28,000.00 | $21,300.00 | +6.7k(31%) |
| Video Views | Prospecting | US | $12,250.00 | $34,000.00 | $25,100.00 | +8.9k(35%) |
To view insights like this for your own site, book a demo.
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Show clients exactly what’s working with clear attribution and insights. Automate reporting with drag-and-drop templates. Integrate with Looker Studio and simplify your marketing tool stack.
E-commerce
Grow sales profitably.
LTV by First-Touch Source
30/60/90-day LTV by first-touch channel. Totals are weighted by cohort size.
Quick insights (click to drill down)
Highest 90-day LTV
klaviyo / flow LTV90 $138.07 on 856 clients.
Largest cohort
reddit.com / referral acquired 1,538 customers · LTV90 $113.93.
Fast payback (front-loaded)
$40.34 in 30d (62% of 90d) via shop / marketplace.
Customers40,186Rev 30d$2,226,228.79Rev 60d$3,215,377.00Rev 90d$4,031,727.96LTV 30d$55.40LTV 60d$80.01LTV 90d$100.33
- Klaviyo856$64,236.61$93,656.61$118,179.73$75.06$109.42$138.07
- Other835$61,718.20$91,131.18$113,983.45$73.92$109.14$136.51
- Other514$36,865.27$52,844.89$67,408.07$71.72$102.82$131.16
- Snapchat816$53,822.83$81,754.30$105,383.94$65.96$100.19$129.15
- WhatsApp771$52,837.54$77,470.59$97,958.90$68.55$100.61$127.05
- Mailchimp595$40,622.60$57,545.44$72,051.96$68.25$96.80$121.09
- Other686$43,856.03$64,925.83$79,329.98$63.94$94.67$115.71
- GooglePaid612$39,688.20$56,753.37$69,971.64$64.89$92.75$114.35
- Reddit1,538$98,256.54$136,997.86$175,215.92$63.89$89.06$113.93
- Amazon1,021$58,538.08$91,741.71$116,057.18$57.34$89.86$113.69
- TikTok730$45,346.57$64,718.72$81,015.79$62.11$88.67$111.00
- Bing598$36,440.97$52,671.82$65,090.51$60.92$88.05$108.84
- Other962$54,904.49$79,554.97$101,640.18$57.06$82.69$105.65
- Twitter764$46,665.64$67,072.09$80,538.67$61.08$87.81$105.42
- YouTube997$58,318.20$83,936.26$105,017.12$58.51$84.16$105.33
- Other1,036$60,367.93$83,920.68$108,570.40$58.27$81.00$104.85
- Meta825$45,710.43$69,461.69$86,266.80$55.44$84.80$104.54
- DuckDuckGo797$48,100.79$67,349.74$82,777.52$60.35$84.50$103.86
- Other984$56,461.63$83,018.10$100,219.71$57.37$84.39$101.85
- Meta833$49,641.00$68,462.77$84,552.89$59.59$82.20$101.50
- Other270$15,772.39$22,140.56$27,207.34$58.42$82.00$100.77
- Other644$37,984.87$52,276.22$64,727.93$58.98$81.17$100.19
- Other1,008$51,758.76$78,349.24$100,596.15$51.35$77.70$99.60
- Meta522$28,516.90$41,023.90$51,765.58$54.62$78.57$99.16
- GooglePaid864$49,965.72$69,255.20$86,007.72$57.83$80.15$99.08
- Untagged680$37,483.02$53,058.17$66,677.76$55.12$78.62$98.05
- GooglePaid791$43,157.73$60,116.05$77,215.00$54.55$75.98$97.62
- Other691$37,705.49$52,427.55$65,805.78$54.54$75.85$95.20
- Taboola1,418$68,130.67$105,803.04$134,598.39$48.04$74.62$94.92
- Pinterest623$32,392.07$46,167.19$58,407.43$52.00$74.12$93.77
- Other1,160$56,637.48$83,345.47$108,207.46$48.83$71.86$93.28
- Discord309$16,877.12$23,022.85$28,797.65$54.62$74.55$93.22
- Other1,010$47,343.78$73,462.98$94,050.57$46.90$72.74$93.17
- Other840$45,286.22$61,477.48$77,556.07$53.90$73.19$92.33
- Other841$43,068.25$62,425.40$77,529.23$51.20$74.23$92.20
- Linktree167$9,313.43$12,563.32$15,376.24$55.78$75.22$92.07
- Telegram497$25,064.85$36,942.98$45,738.19$50.42$74.33$92.01
- Quora878$47,251.34$65,034.60$79,582.70$53.83$74.09$90.65
- Other407$19,997.74$29,327.83$36,752.76$49.14$72.06$90.32
- Bing744$37,135.52$52,604.85$66,086.94$49.93$70.72$88.86
- Meta478$24,839.72$33,861.72$42,409.37$51.94$70.82$88.72
- Other608$28,925.34$42,726.49$53,828.86$47.59$70.28$88.57
- GooglePaid676$33,426.79$48,755.94$59,784.53$49.46$72.11$88.43
- LinkedIn767$38,323.63$54,712.92$67,579.77$49.97$71.35$88.12
- Other834$39,809.51$57,925.47$71,363.88$47.73$69.46$85.56
- TikTok392$19,026.57$27,057.60$33,463.75$48.53$69.05$85.38
- Outbrain846$35,646.49$55,575.66$71,351.33$42.12$65.70$84.33
- Yahoo849$39,321.22$57,393.11$71,309.49$46.31$67.61$83.98
- Other447$20,654.10$29,680.72$37,233.61$46.22$66.36$83.28
- Other210$10,148.12$13,862.07$17,224.41$48.33$66.01$82.97
- YouTube498$23,164.98$32,558.02$40,590.28$46.53$65.40$81.54
- Other371$17,434.66$24,554.02$29,993.97$46.98$66.19$80.83
- Other548$24,643.58$35,033.20$44,148.38$44.97$63.92$80.58
- TikTok222$10,348.57$14,805.54$17,846.60$46.61$66.66$80.39
- Etsy387$17,338.72$25,129.81$31,060.33$44.79$64.94$80.25
- Amazon104$4,802.96$6,648.89$8,177.30$46.19$63.93$78.61
- Other229$10,322.09$14,826.79$17,553.09$45.10$64.79$76.67
- Yahoo149$6,765.98$9,165.03$11,257.04$45.41$61.51$75.55
- Other358$14,855.77$21,407.11$26,515.04$41.47$59.78$74.05
- Other79$3,187.09$3,883.39$5,119.68$40.34$49.16$64.81
LTV is calculated as revenue per acquired client within 30/60/90 days of first touch. Cohorts are grouped by first-touch channel; “Direct” can be hidden.
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Who boosts whom? (A influences finishing on B)
Sorted by Expected extra B purchases = Δ of B chance × Purchases with A.
Show pairs where A is…
…and where B is…
Influence (A → B)
Expected extra B purchases
Lift ×
Seen in
Per 100 with A: +8.0kPurchases with A: 9,331A & finished on B: 8,210B base rate: 15.4%
747.1k
estimated incremental B’s
11.10
8,210
When A is present, shoppers are 11.10× more likely to finish on B (≈ 88% vs 7.9%), seen in 8,210 purchases — roughly +8.0k extra B’s per 100 with A.
Chance of finishing on B when A happened88%
Chance of finishing on B when A did NOT happen7.9%
Per 100 with A: +8.8kPurchases with A: 6,940A & finished on B: 6,940B base rate: 18%
611.4k
estimated incremental B’s
8.40
6,940
When A is present, shoppers are 8.40× more likely to finish on B (≈ 100% vs 11.9%), seen in 6,940 purchases — roughly +8.8k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen11.9%
Per 100 with A: +8.5kPurchases with A: 6,535A & finished on B: 6,535B base rate: 21%
552.7k
estimated incremental B’s
6.48
6,535
When A is present, shoppers are 6.48× more likely to finish on B (≈ 100% vs 15.4%), seen in 6,535 purchases — roughly +8.5k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen15.4%
Per 100 with A: +8.9kPurchases with A: 5,972A & finished on B: 5,972B base rate: 16.7%
529.1k
estimated incremental B’s
8.77
5,972
When A is present, shoppers are 8.77× more likely to finish on B (≈ 100% vs 11.4%), seen in 5,972 purchases — roughly +8.9k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen11.4%
Per 100 with A: +4.3kPurchases with A: 11,065A & finished on B: 6,492B base rate: 20.2%
478.7k
estimated incremental B’s
3.81
6,492
When A is present, shoppers are 3.81× more likely to finish on B (≈ 58.7% vs 15.4%), seen in 6,492 purchases — roughly +4.3k extra B’s per 100 with A.
Chance of finishing on B when A happened58.7%
Chance of finishing on B when A did NOT happen15.4%
Per 100 with A: +9.0kPurchases with A: 4,103A & finished on B: 4,103B base rate: 13.8%
368.7k
estimated incremental B’s
9.85
4,103
When A is present, shoppers are 9.85× more likely to finish on B (≈ 100% vs 10.1%), seen in 4,103 purchases — roughly +9.0k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen10.1%
Per 100 with A: +2.2kPurchases with A: 12,708A & finished on B: 4,824B base rate: 18.6%
281.2k
estimated incremental B’s
2.40
4,824
When A is present, shoppers are 2.40× more likely to finish on B (≈ 38% vs 15.8%), seen in 4,824 purchases — roughly +2.2k extra B’s per 100 with A.
Chance of finishing on B when A happened38%
Chance of finishing on B when A did NOT happen15.8%
Per 100 with A: +8.0kPurchases with A: 3,378A & finished on B: 3,378B base rate: 22.8%
270.0k
estimated incremental B’s
4.98
3,378
When A is present, shoppers are 4.98× more likely to finish on B (≈ 100% vs 20.1%), seen in 3,378 purchases — roughly +8.0k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen20.1%
Per 100 with A: +9.4kPurchases with A: 2,425A & finished on B: 2,425B base rate: 8.7%
226.8k
estimated incremental B’s
15.47
2,425
When A is present, shoppers are 15.47× more likely to finish on B (≈ 100% vs 6.5%), seen in 2,425 purchases — roughly +9.4k extra B’s per 100 with A.
Chance of finishing on B when A happened100%
Chance of finishing on B when A did NOT happen6.5%
Per 100 with A: +542.80Purchases with A: 39,837A & finished on B: 5,205B base rate: 9.8%
216.2k
estimated incremental B’s
1.71
5,205
When A is present, shoppers are 1.71× more likely to finish on B (≈ 13.1% vs 7.6%), seen in 5,205 purchases — roughly +542.80 extra B’s per 100 with A.
Chance of finishing on B when A happened13.1%
Chance of finishing on B when A did NOT happen7.6%
Per 100 with A: +2.2kPurchases with A: 9,856A & finished on B: 4,110B base rate: 22.2%
213.6k
estimated incremental B’s
2.08
4,110
When A is present, shoppers are 2.08× more likely to finish on B (≈ 41.7% vs 20%), seen in 4,110 purchases — roughly +2.2k extra B’s per 100 with A.
Chance of finishing on B when A happened41.7%
Chance of finishing on B when A did NOT happen20%
Per 100 with A: +814.40Purchases with A: 19,335A & finished on B: 2,222B base rate: 4.9%
157.5k
estimated incremental B’s
3.43
2,222
When A is present, shoppers are 3.43× more likely to finish on B (≈ 11.5% vs 3.3%), seen in 2,222 purchases — roughly +814.40 extra B’s per 100 with A.
Chance of finishing on B when A happened11.5%
Chance of finishing on B when A did NOT happen3.3%
Per 100 with A: +1.4kPurchases with A: 8,140A & finished on B: 1,898B base rate: 10.7%
112.1k
estimated incremental B’s
2.44
1,898
When A is present, shoppers are 2.44× more likely to finish on B (≈ 23.3% vs 9.5%), seen in 1,898 purchases — roughly +1.4k extra B’s per 100 with A.
Chance of finishing on B when A happened23.3%
Chance of finishing on B when A did NOT happen9.5%
Per 100 with A: +296.10Purchases with A: 37,343A & finished on B: 4,461B base rate: 10.1%
110.6k
estimated incremental B’s
1.33
4,461
When A is present, shoppers are 1.33× more likely to finish on B (≈ 11.9% vs 9%), seen in 4,461 purchases — roughly +296.10 extra B’s per 100 with A.
Chance of finishing on B when A happened11.9%
Chance of finishing on B when A did NOT happen9%
Per 100 with A: +611.70Purchases with A: 17,491A & finished on B: 2,448B base rate: 8.9%
107.0k
estimated incremental B’s
1.78
2,448
When A is present, shoppers are 1.78× more likely to finish on B (≈ 14% vs 7.9%), seen in 2,448 purchases — roughly +611.70 extra B’s per 100 with A.
Chance of finishing on B when A happened14%
Chance of finishing on B when A did NOT happen7.9%
Per 100 with A: +159.00Purchases with A: 11,363A & finished on B: 1,544B base rate: 12.2%
18.1k
estimated incremental B’s
1.13
1,544
When A is present, shoppers are 1.13× more likely to finish on B (≈ 13.6% vs 12%), seen in 1,544 purchases — roughly +159.00 extra B’s per 100 with A.
Chance of finishing on B when A happened13.6%
Chance of finishing on B when A did NOT happen12%
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Track which campaigns drive leads, calls, demo, or donations. Our technology is agnostic on what you sell and want to track, unlocking possibilities that has benefited e-commerce for years.
Brands
Solve omnichannel.
Even Attribution — Platforms
Equal credit per touch event between previous and current purchase. “Direct” only when no eligible touches exist.
Platform
Orders
Revenue
Order %
Revenue %
Orders
34.7%
Revenue
36.5%
Orders
20.5%
Revenue
20.7%
Orders
14.5%
Revenue
13.8%
Orders
12%
Revenue
9.6%
Orders
6%
Revenue
6.4%
Orders
3.5%
Revenue
3.7%
Orders
1.9%
Revenue
2%
Orders
1.9%
Revenue
1.9%
Orders
1.2%
Revenue
1.3%
Orders
1.1%
Revenue
1.1%
Orders
0.6%
Revenue
0.7%
Orders
0.6%
Revenue
0.6%
Orders
0.5%
Revenue
0.5%
Orders
0.4%
Revenue
0.4%
Orders
0.3%
Revenue
0.3%
Orders
0.3%
Revenue
0.3%
Total Orders Credit:3,171.200
Total Revenue Credit:$355,055.00
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What are insights?
There are many solutions in the market that help with reporting, data connections and attribution. (We do it cheaper.) One thing, however, that is not as common is quality insights into a website's traffic. Take a look below to get a taste of the ever-growing library we develop with our partners.
Learn more from simple insights
Last Channel Before Abandonment
See which marketing channel users last touched before dropping off to target smarter retargeting.
Touchpoints Before Drop-Off
Measure how many interactions users have before abandoning to spot friction and fix leaks.
Average Time to Convert
Understand the typical time from first touch to purchase to set expectations and optimize funnels.
30/60/90-Day LTV by First Touch
Track cohort lifetime value at 30, 60 and 90 days, grouped by the channel that first acquired customers.
Customer Behavior Patterns
Identify the most common browsing and buying behaviors to tailor journeys and messaging.
Channel Impact by Journey Stage
Quantify each channel’s impact at every stage of the buyer journey to allocate budget effectively.
Conversion Time Distribution
Visualize how long conversions take across customers to uncover fast vs. slow-moving segments.
Conversions by Hour & Channel
Find the hours of day that drive the most conversions and the channels behind them.
Core User Metrics Overview
Monitor total, new, returning and active users for the selected date range.
Daily User Metrics Trends
Trend daily totals for new, returning and active users to spot momentum and dips.
Event Type Distribution
See which on-site events (views, carts, checkouts, purchases) occur most often.
First-Time vs. Repeat Purchases
Compare new vs. repeat order volume and revenue to gauge retention health.
New vs. Returning Users by Source
Discover the source/medium combos that attract new customers and bring users back.
Top First-Touch Sources
Identify where customers first discovered your brand to optimize acquisition.
New Customers: First vs. Last Source
Compare initial vs. closing channels for new buyers to balance prospecting and closing.
Returning Customers: First vs. Last Source
See which channels start and finish returning-buyer journeys to guide retention spend.
Funnel Step Drop-Off
Quantify how many users reach each step and where they exit to prioritize fixes.
Purchases by Hour & Referrer
See when purchases peak and which referrers dominate those hours.
Channel Lift & Assist Analysis
Measure how often channel A appears in journeys that convert on channel B to justify upper-funnel spend.
Initiating & Influencing Channels
Reveal channels that kick-off or influence converting journeys beyond last-click.
Channel Presence in Long Journeys
Find channels consistently present in complex, multi-touch paths.
Journey Length vs. Conversion Efficiency
Analyze whether longer paths correlate with higher AOV or lower conversion rates.
Journey Touchpoint Distribution
Quantify the share of short vs. long journeys to size effort to convert.
Longest Engagement Channel
See which channel holds user attention for the longest during converting paths.
Even Multi-Touch Attribution
Distribute credit evenly across all touches so fractional credits sum to 1 per journey.
New Customer Acquisition by Channel
Attribute first-ever purchases to earliest touchpoints to see where new customers come from.
Daily Platform Impact
Compare platform performance day by day across purchases, revenue and ROAS.
Platform Impact Summary
Rank platforms by total impact to guide budget allocation.
Platform Over-Reporting Audit
Compare ad platform claims (Google, Meta) to real attribution to estimate over-reporting.
Product Conversions by Channel
See which products convert from which channels to align merchandising and media.
Product: First & Last Sources
Find common first and last sources for each product’s converting journeys.
Journey Length by Product
Compare average conversion time across products to detect friction or urgency.
Daily Revenue & Orders
Track revenue and order counts by day to understand sales cadence and seasonality.
Source Performance Comparison
Benchmark sources against each other on conversions, revenue and efficiency.
Performance Spike Reasoning
Explain sales spikes by pinpointing the channels and campaigns that caused them.
Touchpoints per Journey
Count interactions per converting journey to gauge effort and attribution spread.
Vendors: Items Sold & Top Channel
Rank vendors by items sold and reveal their leading attribution channel.
Visits Before Purchase
Quantify sessions required before conversion to identify high-effort paths.
Likely Wasted Ad Spend
Estimate spend on users who would have purchased anyway to cut cannibalization.
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