model-driven planning™
An incrementality testing program to scale your performance.
Optimize spend across channels
Perfect attribution is hard. And with the combination of shifting consumer demands, and the difficulty to accurately attribute media spend, marketers are challenged to make decisions around channel and media mixes without quality data.
Model-Driven Planning™ helps you:
- Determine the right channel and media mix
- Invest your marketing budget efficiently
- Save time and money on other complex measurement solutions
$4B+
direct commerce sales attributed
$10B+
offline sales influenced
HOW IT WORKS
Pairing human insight + proprietary tech to crush our shared performance marketing goals.
A roadmap for growth
We develop a strategy for testing optimal spend across channels, using your first party business data. This begins with identifying your key objectives, mapping business goals to scaling benchmarks over a pre-determined time period of work, and setting up data ingestion.
Suite of testing
Our tri-test approach measures the impact of media with little disruption on overall account performance. We analyze and split spend in the desired testing channel into three groups, performing hold-back and scale-up testing at the same time. It’s a win-win: you understand incrementality, with low opportunity cost.
Measure + scale
Get results, analyze and tweak — with our help — on an ongoing basis. Adlucent data scientists detail out where to make spend adjustments and how to optimize your media for maximum efficacy.
Scale your marketing, efficiently
We tailor our tech-centered approach to your exact goals and needs, every time.
CLIENT SPOTLIGHT
A global ecommerce marketplace client builds a program of experimentation
01
CHALLENGE
Our global ecommerce marketplace client wanted to understand whether spending more on Google Shopping would increase incremental topline revenue.
02
SOLUTION
Using the brand’s internal revenue data combined with their paid search spend from Google, tests were executed to gauge incremental top-line revenue lift.
03
RESULTS
By spending 3x more in the experiment groups vs control groups, a 3x incremental lift in top-line revenue was observed versus the last click attribution the brand was originally reliant upon.
04
Actions taken
Since Google Shopping drove more revenue than was previously being attributed for this brand, budget investment was increased, and additional experimentation continued to test more facets of the company’s paid media.
LEARN ALONGSIDE US
Check out resources created for your campaign growth.
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GOT QUESTIONS?
Here’s the answers to some of the most frequently-asked Adlucent queries. Don’t see yours here? Reach out to our team.
What’s cool about our approach is we use your source of truth to create geo splits for the test and evaluate performance, versus vague proxy metrics or network metrics that can cause more questions than clarity. We can test in any channel with sufficient spend that can be reported on daily by either DMA, city/state, or ZIP code, and evaluate any response metric that matters to you. So whether it’s ecommerce orders, store revenue, or something else, we help you make a data-driven decision to quantify the optimal investments across channels for your business.
Our scientific approach at Adlucent involves creating experimentation to scale performance, and as such we recommend performing incrementality testing regularly to help make spend decisions in an increasingly complex digital marketing landscape. First, we work with you to identify and prioritize the right set of tests needed to provide statistically significant answers to media mix models. Then, we analyze and split test spend into three groups of 33%: one control, one with a higher spend, and one with a lower spend. We partner closely with you to do a combination of hold-back and scale-up testing at the same time to measure the impact of media with less disruption on overall account performance.
Yes! It is not a requirement to have Adlucent managing your marketing campaigns. We will work with your in-house team or agency closely to provide the appropriate geo-split and ensure the appropriate adjustments are made in the testing channel, and share the results with full transparency.