Pēq is PURE.

Precise. Uniform. Real-Time. Exact.

  1. PreciseGranular enough to act.
  2. UniformOne standard across marketing.
  3. Real-TimeInsight while it can still matter.
  4. ExactRigorous causal measurement.

P / Precise

See what worked, not just whether it worked.

Pēq measures performance at the level where decisions happen, revealing the investments that are creating incremental growth and the ones that are not.

From the portfolio view to the individual execution, Pēq gives teams the granularity to take action.

U / Uniform

Different marketing. Same standard.

Pēq applies one consistent framework across channels, retailers, partners and activations, so results can be compared without translating between different methodologies and metrics.

R / Real-Time

Know what’s working while there’s still time to act.

Pēq refreshes performance insights while marketing is live, turning measurement from a post-campaign report into information teams can use to make optimizations during the campaign.

  1. Forecast


    Know what to expect before launch.

    Use baseline sales and planned media investment to forecast incremental sales, iROAS and the expected impact of a campaign before it begins.

  2. Measure


    See the sales impact as it happens.

    Track incremental sales, lift and iROAS through independent test/control measurement, with updated reads as new sales data becomes available.

  3. Optimize


    Know where to act while media is live.

    Identify stronger and weaker markets, uncover performance opportunities and shift investment while the campaign is still running.

  4. Plan


    Turn what worked into the next allocation.

    Build on measured results and historical response curves to identify the right channel mix, investment levels and allocation for future campaigns.

Every campaign makes the next one smarter.

Illustrative example

E / Exact

Built to measure what marketing actually caused.

Pēq combines observed retailer sales data with rigorous causal measurement to estimate what would have happened without the marketing intervention and isolate true incremental impact.

Observed sales rise after marketing starts while the modeled counterfactual stays near baseline; the gap between them is the incremental impact Marketing starts Incremental impact What happened What would have happened Before During campaign
What happenedObserved sales performance
versus
What would have happenedModeled counterfactual without the marketing intervention
=
Incremental impactWhat the marketing actually caused
How the counterfactual is built
  • Observed sales come from retailer point-of-sale data, harmonized by week, UPC and store.
  • The counterfactual is modeled from comparable stores and markets that did not receive the marketing, calibrated on the period before the campaign started.
  • Incremental impact is the difference between the two, isolated with geo-based experiments and causal models, and reported as incremental sales and iROAS.

Proof · Exact

“Marketers are drowning in dashboards that confuse correlation with causation. What impressed me about Pēq is that they chose the harder path: store-level data, honest controls, and causal inference done properly. It reflects the best of what measurement science has learned in the last decade, made usable for the people who run campaigns.”

Elea FeitElea FeitPēq Academic AdvisorThe Ohio State University