In-flight measurement & analytics
Your performance engine making every media dollar work harder.
Your outcomes. Your controls.
Precise connects in-flight measurement with a scenario planner to:
- 01Uncover more value while campaigns are live for incremental ROAS
- 02Recommend where to move spend, predict the impact, and learn from each outcome
- 03Turn every outcome into a smarter recommendation
- 04Make your impact clear to clients
01 / Uncover more value
Uncover more value
while campaigns are live.
Precise determines the contribution value of every campaign attribute, alone and in combination.
- Data partner
- Distributor
- Frequency
- Creative
- Demographic
- Daypart
- Geography
- Bid strategy
- Audience segment
- Publisher
- Supply path
- Flight week
+ every other attribute on the buy
We recommend where the next dollar goes and the predicted gain.
02 / Make the next decision
Recommend where
to move spend.
Sample analytics. Objective: improve ROAS. Total spending to remain $1,000,000.00.
Current plan 2.07× → recommended plan 2.68×
Recommended plan
Projected return on the same $1,000,000
- Current plan
- 2.07×
- Recommended plan
- 2.68×
+29.5% higher projected return on the same budget.
Precise recommends how to divide the same budget across four combinations of creative, audience, and platform to improve the campaign outcome.
Here, it shifts spending toward two combinations on one DSP: customer story with home improvement shoppers, and product demo with kitchen and cooking enthusiasts.
It accounts for how much each combination can absorb efficiently, directing the next dollar where it is predicted to contribute most.
| Placement | Current | Recommended | Shift |
|---|---|---|---|
| Customer story×Home improvement shoppers·DSP A | $300,000.00 | $420,192.23 | +$120,192.23 |
| Customer story×Kitchen and cooking enthusiasts·DSP B | $160,000.00 | $74,126.64 | −$85,873.36 |
| Product demo×Kitchen and cooking enthusiasts·DSP A | $120,000.00 | $471,188.56 | +$351,188.56 |
| Product demo×Home improvement shoppers·Connected TV platform | $420,000.00 | $34,492.57 | −$385,507.43 |
| Total | $1,000,000.00 | $1,000,000.00 | $0.00 |
Move left to shift less budget. Placement budgets and projected return update together.
Illustrative model estimates, not demonstrated lift. ROAS includes media spend and fees.
03 / Predict the impact
Predict
the impact.
Audience, placement and frequency can change the same creative’s contribution value.
Estimated revenue contribution per $1 of media spend and fees for the selected combination.
Sample analyticsIllustrative
Contribution value
3.50×
Programmatic DSP · Home improvement shoppers · Connected TV · Smart TV · Evenings · 15-second cutdown · First-frame before/after · Top 10 DMAs · 3–5 exposures
| Added contextSelected valueValue ÷ cost |
|---|
Select a layer to explore the example; each layer includes the selections above it.
04 / Learn from each outcome
Learn from
each outcome.
Once enough data is available, we compare results with the prediction and benchmark, using controlled tests where feasible.
Our recommendation: predicted and measured returns
| morning | actual | predicted | low | high | left alone | holdout |
|---|
Illustrative schematic. The area to the right of today shows projections, not observed results. Return means revenue per $1 of media spend and fees.
01
Before the move
Record the prediction and range, with a comparison that keeps the original setting.
02
After the move
Measure improvement. Use controlled tests to assess causality where feasible.
05 / Keep improving
Compounding precision.
Turn each outcome into a smarter recommendation. Spend moves toward what drives performance while campaigns are in flight.
- 01
Run
The campaign, in flight.
- 02
Surface
Intelligence and insights.
- 03
Recommend
Shift and reinvest.
- 04
Predict
The outcome.
- 05
Prove
Actual vs predicted.
- 06
Recalibrate
Every cycle, more precise.
06 / Build your evidence
Make your impact
clear to clients.
Your team builds an in-house record of recommendations, decisions and measured outcomes. Each decision informs the next and adds to a collective view of performance.
01
Why money moved
The recommendation, supporting evidence and predicted outcome, recorded before action.
- Recommendation
- Reallocate spend
- Predicted outcome
- Recorded with a range
02
What changed
The allocation decision, when it happened and how much moved, within your agreed limits.
- Decision
- Reviewed by your team
- Allocation change
- Recorded when implemented
03
What it returned
The measured outcome against the prediction and agreed benchmark, informing the next decision.
- Measurement
- Prediction vs. outcome
- Next recommendation
- Refined with the evidence
Our collaboration arms your team for conversations with your client CMOs.
07 / Built around you
In-flight measurement with a scenario planner,
built into your tech stack.
An authorized subprocessor and building block inside your tech stack. We enhance your platform’s performance.
Interoperable with any
- Data sources & storage
- Snowflake, Optable, DSPs
- Reporting
- Tableau, Datorama, Power BI
- Workflow
- Internal systems, Mediaocean, AI agents
What makes Precise different.
01
Contribution math
Multi-patented methodology calculates contribution value relative to cost. Scores individual attributes and their combined effects.
02
Depth + speed
Evaluates hundreds of attributes, individually and in combination, in near real time. Recalculates contribution as new campaign data arrives for immediate recursive learning.
03
Traceable outputs
Preserves the data and logic behind every result. Produces structured decision records for agents to act on and people to audit.
Where your delivery and outcome data lives.
Precise connects what ran to what it returned, using data you already have.
Delivery data
What ran, where and what it cost
- DSP logs
- DV360, Amazon DSP, The Trade Desk
- Social
- Meta, TikTok
- Search and video
- Google, YouTube
- Retail media
- Amazon, Walmart and other retailers
- Reporting tools
- Domo, Power BI, Snowflake
Outcomes data
What the business got back
- First party data
- Orders by market, time and value
- CRM and sales
- Client sales and customer records
- Conversions
- Already joined to DSP logs
- Visits
- Site and store visits
- Retail sales
- Amazon AMC and other retailers
- Data clouds
- Snowflake, LiveRamp, Optable
Agree on success, establish the baseline and identify what to predict. You define the objective, eligible inventory, budget movement limits and approval requirements.
The team
Built by people
who know media.
Our founders helped build and scale Madhive and created the AdLedger transparency consortium.
Precise brings that operating experience to a focused task: understanding what contributes to campaign outcomes and using that evidence to improve spending decisions.
- Spencer PottsCo-founder & Chief Executive OfficerFormer CEO of Madhive
- Adam HelfgottCo-founder & Chief Technology OfficerCo-founder of Madhive · Founder of Valence Labs
- Matt BarlinChief Science Officer
- Dave AntonelliChief Revenue Officer
Backed by
Blockchange Ventures · Lasagna · Click Ventures · 3C Ventures
08 / Next step
Getting started.
We analyze 30 days of historical data to define a baseline, followed by a 60-day engagement aligned with mutually agreed success metrics.
01
The starting input
30 days of historical portfolio data. Agree on success, establish the baseline and identify what to predict.
02
The 60-day engagement
Predict the outcome. Act on recommendations and measure results. Refine the models as we learn.
03
Build on the evidence
Extend the approach as value is established, with the record of predictions and measured outcomes carried forward.
A few practical questions.
How will we know whether performance is improving?
We agree on the business outcome, included costs, comparison and evaluation window upfront. Measured outcomes are compared with recorded predictions and the agreed benchmark. Controlled tests assess causality where feasible; a prediction alone is not proof of improvement.
How does Precise fit our existing setup?
We work with your campaign data and existing workflows, bringing recommendations to your team or AI agents. The data available and its level of detail determine what we can evaluate. Integration and deployment are agreed with your team. Read about security and data.
Who decides whether to move spend?
Your team defines the objectives, operating limits and approvals. On the standard path, Precise recommends and your team makes the change in the platform. The implemented change is recorded so it can be measured.
What becomes part of our record?
The recommendation, its supporting evidence and predicted outcome, the decision taken, the implemented change and the measured outcome. This builds an in-house evidence base your team can use to inform future decisions.
Let’s talk
Make your next
media decision
more precise.
Tell us the outcome you want to improve. Let’s find where your budget can do more.