Kuwalyst Media Planner
Build a plan from your data or audited benchmarks, monitor it against your goals and work through recommendations as new evidence becomes available. The source behind each number remains visible throughout.
Follow the planning process from what is working this week and what to do next, through to your commitments, the portfolio they belong to and the data and models that support them.
Review each channel's committed spend against plan, marginal incremental ROAS and current status. Goals sit alongside the channel view, identified as projected or measured and shown with their target and trend. Weekly and monthly reports explain what changed and where attention is needed.
Each recommendation explains its hypothesis, proposed action, expected impact and confidence rating. You can accept, defer or reject it, and the planner records the decision. Where evidence is limited, measurement recommendations propose an experiment that can replace a modelled figure with a measured one.
Compare allocations side by side, with each option showing its projected blended return, uncertainty range, trade-offs and the guardrails it does or does not meet. Once you commit to a scenario, the planner prepares the plan document, rationale and presentation export.
Designed for teams managing more than one brand, the portfolio shows the evidence available for each one: a calibrated MMM, platform synchronisation or an active A/B test. Plans that need attention are easy to identify.
The planner connects to your data, audited benchmarks, documents and models across online and offline channels. Its connectors cover warehouses, ad platforms, analytics, CRM, e-commerce and flat files, and it can also connect to MCP servers and agent skills developed by your team.
You decide which actions the planner can take. Each level of autonomy operates within the guardrails and limits you set.
The planner can take low-risk actions within limits you set, such as spend caps and reversal windows, while keeping you informed.
ExamplePausing a keyword with zero conversions.
Medium-risk actions are presented for review and can be approved in one click, with thresholds you control for each channel.
ExampleA budget reallocation the MMM recommends.
High-risk actions come with a full briefing before you decide. On higher plans, a Kuwalyst marketing scientist can join the review.
ExampleStopping a campaign or changing a bidding strategy.
If first-party data is not yet available, the plan can be based on your brief and the audited benchmark registry. Each figure is identified clearly, along with the most useful tests to run first.
With a data warehouse and an MMM, allocations can follow the marginal incremental ROAS shown by the model's response curves, rather than relying on an average return.
Your AI analyst inside Shopify admin: what changed in sales, products, inventory and customers, where it came from, and what to check next. In early access, free.
The planner uses Scaleway Generative APIs, hosted in the EU (France). Privately hosted models are available on request, including on-premise and VPC deployments.
License the platform for your own team, or work with our marketing scientists on optimisation and execution. Agencies can license a single workspace for their client portfolio.
See pricing“TikTok isn't a channel in your warehouse — you don't have TikTok spend or revenue tracked. There's nothing in the warehouse to calculate a ROAS from right now.”
Begin with audited benchmarks when data is not yet available, then move to a data-backed plan as evidence builds.
Each traced to its primary publisher. The sourcing policy is part of the registry.
Figures are identified as measured, projected or benchmarked on every screen and in every export.
Bring a brief, spreadsheet or data warehouse, and we will show you what a first plan could look like within an hour.
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