soclar · for CMOs

watching q2

Every touch.Every channel.Credited.

Soclar credits every touch on every deal. LinkedIn, events, partnerships, the dinner that actually closed it. We watch the journey in real time and tell you on Slack the moment a channel pulls more weight than your CRM thinks. Up or down.

Book a 15-min call See it without us

No credit card. No setup. Bring a number you want to hit.

q2 attribution · recomputed

2m ago

last-touch · your crm

5 channels

+312%

Events

+420%

Partnerships

+540%

Direct

−68%

Paid Search

−22%

last-touch undercounted LinkedIn by 3.1×

soclar

· every quarter ·

You set the budget in January.
By March you're guessing.

Spreadsheets lag a week. Dashboards show what already happened. By the time you spot the channel that's burning cash, the quarter is gone.

01 · the inputs you control

Tell it what winning looks like.

Quarterly revenue target. CAC ceiling. Pipeline floor. Blended ROAS. The numbers your board already asks about. Captured once, then watched continuously.

Set once. Re-asked only when the quarter closes.
Read by every layer. Attribution, pacing, forecast all watch the same numbers.
Versioned.Last quarter's plan is still there when the board asks.

q2 2026 · plan

editing

Revenue target: $4.2M↑ 18% vs Q1
CAC ceiling: $1,800per closed-won
Pipeline target: $12.6M3× revenue
Blended ROAS floor: 2.4×minimum

total budget · q2

$840,000

$0$1.2M

saved · 2 min ago · elena.m

02 · the companion

A teammate in your Slack.
One that reads the data.

Ask it anything in #marketing-ops. It pulls from every connected source, answers in plain English, cites the numbers, links the dashboard. And when something diverges from plan, it speaks first. You don't have to ask.

What’s pacing on Q2 pipeline?
Why did our blended ROAS drop last Tuesday?
Should I shift $20k from Meta to LinkedIn?

marketing-ops· 14 members

today

Soclarapp9:14 AM

LinkedIn Ads is pacing 23% below plan this week. Two campaigns paused on Tuesday: Enterprise-Q2-ABM and MidMarket-Retarget. At this rate you'll miss the channel's pipeline target by ~$340k. I'd shift $18k from Meta Retargeting (running 41% above plan) to keep pace.

linkedin · 14d pacing

−23%

View in dashboardApply reallocation

Elena M.10:02 AM

@Soclar how are we tracking on Q2 pipeline?

Soclarapp10:02 AM

$8.9M generated · $12.6M target · 71% with 38 days left.

Pacing 6% ahead of plan. Three channels carrying it: LinkedIn ABM, Events (RSA recap), and outbound. Risk to watch: Google Search CPCs up 14% week-over-week.

View dashboard

soclar · connected to Slack · read-only outside threads

03 · the watch

Every channel, against the plan.
In real time.

The line you drew in January is still on the chart. So is what's actually happening. When they part, the AI explains the gap before it widens.

Total budget pacing · Q2 2026 · model: Bayesian

spend vs plan

planactualai forecast coneupdated · 2 min ago

04 · the horizon

Plan four quarters.
Watch all four.

Budget for Q3, Q4, even next year, and see them all narrow as new data arrives. The further out, the wider the cone. The closer in, the more you can trust the line.

q2 2026
in progress
$8.9M
71% to plan · 38d left
q3 2026
forecast
$13.4M
±$1.1M · 82% confidence
q4 2026
forecast
$15.2M
±$1.8M · 71% confidence
q1 2027
directional
$16.8M
±$2.6M · 58% confidence

how it works

From a number on a whiteboard to a calm Monday morning.

01
Set the goals
Revenue target. CAC ceiling. Pipeline. ROAS. We capture the numbers your board already asks about. Once.
02
Set the budget
Allocate by channel, or let the AI propose an allocation grounded in the last four quarters of what actually worked.
03
We watch
Every channel, every day, against the plan you drew. The math we'd hire a McKinsey shop for, automated and never asleep.
04
We tell you on Slack
When something strays, the bot speaks first. Under-pacing, over-pacing, an early-warning trend. Plain English. Specific numbers. A recommendation.

· why you can trust the alerts ·

The AI doesn't guess.
It checks three readings of the same revenue.

Most attribution tools give you a number. We give you a number you can defend, because three independent layers read the same revenue, and the bot tells you when they disagree.

01 · classical
Multi-touch, every variant
the math your finance team already trusts.
First-touch, last-touch, Data-Driven, time-decay. Computed every variant, every day. Not because they're all right. Because their disagreement is information.
02 · bayesian
A probabilistic core
that holds uncertainty.
Updates as new data arrives. Holds uncertainty instead of pretending it isn't there. This is the layer the rest of the market hasn't shipped.
03 · verifier
AI as the check, not the engine
claude reads, then disagrees.
Claude reads both layers, walks back through the underlying paths, and flags channels where the layers diverge. The math gives the answer. The AI checks it. Hallucinations have nowhere to land.

When all three agree, the bot speaks with certainty. When they don't, it tells you it isn't sure, and why.

That ambiguity is usually where 15–30% of the budget has been mis-credited. We'll walk you through the layers on a 15-minute call.

we connect to

We pull from where your data already lives.

Read-only OAuth into your CRM, ad platforms, analytics, and warehouse. Nothing leaves your tenant unencrypted; every connector ships with a sub-processor entry on our security page.

CRM

Salesforce
Pipeline + deals
HubSpot
Pipeline + deals

Ad platforms

Meta Ads
Spend + creatives
Google Ads
Spend + creatives
LinkedIn Ads
Spend + creatives
TikTok Ads
Spend + creatives
Reddit Ads
Spend + creatives

Analytics

Google Analytics
Web events
Mixpanel
Product events

Warehouse

Snowflake
Data warehouse
BigQuery
Data warehouse

Comms

Slack
Daily reports + alerts

Need a connector we don't list? Tell us on the call.

twelve places your customers come from.
you only see four of them.

Where the credit actually goes.

The same alerts and forecasts run on top of this. Last-touch said Direct closed 31% of revenue. Data-Driven found it was riding on LinkedIn, Events, and Partnerships that had been working for months.

Open the demo

Attribution · last 30 days · model: Data-Driven

cadence audio · seeded

Channel	Last-touch	Data-Driven	Δ
LinkedIn Ads	12%	21%	↑ 9pp
Events	4%	16%	↑ 12pp
Partnerships	6%	14%	↑ 8pp
Google · YouTube	7%	10%	↑ 3pp
Google · Search	18%	13%	↓ 5pp
Meta Ads	16%	9%	↓ 7pp
Direct	31%	11%	↓ 20pp

questions, asked quietly

who's building this

Two of us. So far.

Co-founder

Rasmus

Built TrueROAS. Solved cookie-loss attribution before most people noticed it was broken.

Co-founder

Victor

Founded and sold Alba Cross at 51 people. Doing it again, with Rasmus.

Read the longer story

· then ·

Bring a number you want to hit.
We'll show you how close you are.

Fifteen minutes. Your real data on the screen. We don't ship a pilot until we've answered a question you already have.

Book a 15-min call

Every touch.Every channel.Credited.

Tell it what winning looks like.

A teammate in your Slack.One that reads the data.

Every channel, against the plan.In real time.

Plan four quarters.Watch all four.

From a number on a whiteboard to a calm Monday morning.

Set the goals

Set the budget

We watch

We tell you on Slack

The AI doesn't guess.It checks three readings of the same revenue.

Multi-touch, every variantthe math your finance team already trusts.

A probabilistic corethat holds uncertainty.

AI as the check, not the engineclaude reads, then disagrees.