Northbeam analytics is the cohort, channel, and creative reporting layer that sits on top of the attribution and MMM engines - the surface that DTC analytics teams actually live in day-to-day.
Northbeam analytics is the reporting + cohort + creative analysis surface on top of Northbeam's attribution and media-mix engines - aimed at $5M+ DTC brands with dedicated analytics teams who need defensible, warehouse-exportable measurement.
What Northbeam analytics is, in one paragraph
Northbeam analytics is the dashboarding, cohort-analysis, and reporting layer of the broader Northbeam platform. It sits on top of three lower layers: the attribution engine (cross-device journey stitching), the incrementality testing engine (geo-holdouts), and the media-mix modeling engine (channel spend-curve estimation). The analytics surface is what the team actually opens every day - the place where the underlying methodological work becomes operational decisions.
The reporting is opinionated. Northbeam's dashboards are organized around the questions DTC operators actually need to answer: 'what's my new-customer CAC this week and how does it trend', 'which creative archetypes are driving acquisition vs retention', 'which channels are healthy and which are showing degradation', 'what does my repeat-purchase cohort curve look like by acquisition source'. Each of those questions has a dedicated dashboard with the right defaults pre-configured.
The analytics surface is also warehouse-exportable. Brands with in-house analytics teams typically run Northbeam dashboards as the operational reporting layer and pipe the underlying data to Snowflake / BigQuery / Redshift for custom analysis. The warehouse layer is where the deepest LTV modeling, custom MMM extensions, and bespoke financial reporting happen.
Signature features
What stands out
Cohort LTV analytics by acquisition channel
Segments customers by acquisition channel, cohort week/month, and creative, then tracks LTV / retention / repeat-purchase per segment. Lets you optimize CAC against LTV instead of against CAC alone - which is the actually-correct DTC objective.
Creative analytics with attribution at the ad level
Ad-level dashboards that surface which specific creatives drove acquisition, retention, and LTV per cohort. Most attribution tools stop at campaign level; Northbeam goes down to the ad / creative level for cross-platform comparison.
Channel health monitoring with automatic anomaly detection
Daily channel-level reporting with anomaly flags when CAC, CTR, conversion rate, or LTV trends move outside historical bands. Pushed to Slack so the analytics team sees the flag without opening the dashboard.
Custom-segment cohort builder
Define cohorts by any combination of acquisition channel, creative, geography, first-product purchased, or custom attribute. Run LTV / retention analysis on the custom segment. Powerful for DTC brands with product-line-specific cohort behavior.
Warehouse export to Snowflake / BigQuery / Redshift
First-class warehouse export with documented schemas. Brands with in-house analytics teams treat this as a primary product surface, not an afterthought - the warehouse layer is where bespoke analysis happens on top of Northbeam's measurement baseline.
Slack-integrated automated reporting
Scheduled daily/weekly/monthly reports pushed to Slack channels. Highly configurable per stakeholder group. Designed for teams that report to leadership weekly and want consistent, defensible numbers in the right inboxes.
Pricing snapshot
Plans at a glance
Growth
From ~$1,000/mo
$2-5M brands with strong analytics
Scale
From ~$2,500/mo
$5-20M brands, primary use case
Enterprise
Custom
$20M+ brands and multi-brand groups
Shuttergen
Northbeam reports the past. Shuttergen ships the next ad.
Northbeam analytics tells you which cohorts and creatives are winning. Shuttergen takes that signal and generates 10 new variants of your winners tuned to your brand and category competitors.
Fit
Who this is - and isn't - for
Best for
- · DTC brands $5M-100M+ with dedicated analytics resourcing
- · Brands that optimize against LTV-relative CAC rather than CAC alone
- · Multi-brand groups needing consolidated cohort reporting across portfolio
- · Teams that pipe analytics output to a data warehouse for custom analysis
Skip if
- · Sub-$2M DTC brands - the analytics depth requires scale to justify the cost
- · Info-product / coaching businesses - cohort model assumes repeat-purchase DTC behavior
- · Teams looking for turnkey dashboards with no analytics setup
- · Brands without a dedicated analytics owner - the depth doesn't extract itself
How the cohort analytics actually works
Northbeam's cohort layer segments customers along three primary dimensions: acquisition channel (Meta / Google / TikTok / etc.), acquisition cohort (week or month of first purchase), and creative (which specific ad drove the acquisition). Each customer gets tagged with the full triplet at first purchase, then tracked across subsequent purchases for LTV, retention, repeat-purchase rate, and average order value.
The output is a cohort curve per segment. The Meta-cohort-week-of-2026-03-04 driven by creative ID #4827 has a 60-day retention rate of X%, a 180-day LTV of $Y, and a repeat-purchase rate of Z%. Stacked across cohorts and channels, the curves reveal patterns the per-ad attribution dashboard can't see: which channels acquire customers with the best LTV, which creatives acquire repeat-buyers vs one-time bargain-hunters, which cohort weeks were anomalously good or bad and why.
This is the analytics layer that justifies Northbeam's enterprise pricing for the right buyer. A DTC brand at $10M+ where ad budget allocation directly determines the next quarter's revenue trajectory needs cohort-LTV-informed decisions; a CAC-only optimization will systematically over-spend on channels that acquire low-LTV customers and under-spend on channels that acquire high-LTV ones. Northbeam's cohort layer is the most operationalized version of LTV-aware acquisition reporting in the category.
Creative analytics at the ad level
Most attribution tools stop reporting at the campaign or ad-set level because the data resolution at the individual-creative level is noisy. Northbeam goes one level deeper - ad-level attribution stitched across platforms, with creative-specific cohort LTV tracking.
The use case: you've got 40 creatives running across Meta and TikTok. The campaign-level dashboard tells you Meta is at $X CAC, TikTok at $Y CAC. The ad-set-level dashboard tells you which ad sets within each channel are working. The Northbeam creative-level layer tells you which specific creatives are driving acquisition, which are driving repeat-purchase among existing customers, and which are acquiring high-LTV customers vs low-LTV ones.
That depth changes the creative production workflow. Instead of 'TikTok is working, double the budget', you get 'TikTok creative archetype A is acquiring high-LTV customers at acceptable CAC; archetype B is acquiring low-LTV bargain-hunters at the same CAC; ship more of archetype A and kill archetype B'. The signal is what creative teams actually need to make good production decisions.
Caveat: the ad-level resolution is only useful at scale. Brands with under ~$30k/mo total ad spend won't have enough conversions per creative to read meaningful cohort patterns. Below that scale you're reading noise. This is one of the reasons Northbeam's effective floor is around $5M ARR - the analytics depth needs ad-spend scale to surface signal.
Northbeam reports the past. Shuttergen ships the next ad. Northbeam analytics tells you which cohorts and creatives are winning. Shuttergen takes that signal and generates 10 new variants of your winners tuned to your brand and category competitors.
Channel health monitoring and anomaly detection
Northbeam runs daily statistical checks on every channel and creative against historical baseline. When CAC, CTR, conversion rate, or LTV moves outside a configurable confidence band, the platform flags the anomaly and pushes it to Slack with context.
The value isn't the flagging - any analytics tool can flag anomalies. The value is the context. Northbeam's flag includes the cohort-LTV impact estimate, the projected revenue effect if the anomaly persists, and links to the underlying creative-level data that explains the move. The analytics team gets a Slack message they can act on rather than a generic 'CAC spiked, please investigate'.
Operational impact: brands using anomaly detection well typically catch budget-allocation problems 2-4 weeks earlier than they would by reading the dashboard manually each week. At $10M+ ad spend, 2-4 weeks of avoided over-spend on a degrading channel pays for the Northbeam subscription many times over.
Warehouse export and the analytics-team workflow
Northbeam's warehouse export is structured as a first-class product surface, not a side feature. The schema is documented, the data refresh is scheduled, and the export covers the attribution, cohort, and creative-analytics layers. Brands with in-house analytics teams treat Northbeam as the measurement engine and the warehouse as the bespoke analysis layer.
Typical pattern: Northbeam dashboards run the operational reporting for the marketing team. The warehouse export feeds custom Looker / Mode / Hex dashboards that the analytics team builds for finance, leadership, and product. Both layers stay in sync because they share the same upstream data. The arrangement scales cleanly as the analytics function grows.
Comparison: Triple Whale also offers warehouse export, but the schema is shallower and less methodologically rigorous. For brands with serious in-house analytics, Northbeam's warehouse layer is closer to what they actually need to build defensible custom reporting on top. For brands without in-house analytics, neither warehouse export gets used and the comparison doesn't matter.
Internal: northbeam for the full product deep dive; northbeam-attribution for the attribution methodology; northbeam-pricing for the tier breakdown.
FAQ
Frequently asked
What does Northbeam analytics actually report on?
How is Northbeam analytics different from Triple Whale's analytics?
Do I need a data warehouse to use Northbeam analytics?
Does the cohort analytics work for one-time-purchase brands?
How long does it take to get value from Northbeam analytics?
Can I use Northbeam analytics without the rest of the Northbeam platform?
Does Northbeam analytics replace Looker or Mode?
Related
Keep reading
Resource
Northbeam
Full Northbeam product deep dive.
Resource
Northbeam attribution
The attribution methodology layer.
Resource
Northbeam pricing
Tier-by-tier pricing breakdown.
Research
Triplewhale Vs Northbeam
Head-to-head with the DTC alternative.
Research
Triplewhale Deep Dive
Triple Whale - the lower-tier DTC alternative.
Sources
Northbeam reports the past. Shuttergen ships the next ad.
Northbeam analytics tells you which cohorts and creatives are winning. Shuttergen takes that signal and generates 10 new variants of your winners tuned to your brand and category competitors.