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How Stradem turns customer data into revenue
Stradem is a platform for customer decisions, used with the Stradem team. Together they find the customer groups worth activating first, design an action your team can deliver and test, and measure what the action added. Three Twins support the work. A Twin is a Stradem model of your customers, journeys or decisions.
Where Stradem fits
Compare investments across marketing, product and sales
Your customer data platform keeps customer profiles. Your journey and campaign platforms choose and send the messages. Your analytics tools report what happened. Stradem adds the comparison across them: which initiatives deserve the next dollar and the next sprint. The platform and the Stradem team prepare each recommendation together, and your team makes the decision.
| The question | What your platforms do | What Stradem adds |
|---|---|---|
| Which customer groups have room to grow? | Customer data platform, warehouse, CRM and your existing models hold the profiles and any propensity scores | Groups customers from agreed aggregate data, uses the results of your scores and shows which groups are worth investing in |
| What should each customer see next? | Journey and decisioning platforms pick and send the message, and test it | Journey analysis: where a change, a pause in contact or a test is worth making, and what the team needs to deliver it |
| How did it perform? | Analytics and testing tools report the results | What each action added, valued in dollars |
| Where does the next dollar go? | Finance, analysts and leadership weigh the options | One comparison of the options, with each cost, owner and what it needs to start |
These jobs overlap in practice. Stradem adds one connected workflow for the investment decision.
Customer-level work stays in the systems built for it. Stradem works on agreed aggregate data. See how data moves between Stradem and each layer of your stack
Step 1, find the customer groups worth investing in
Segment Twin
Which customer groups should we invest in, and what should we test with them?
- Segmentation: customer groups built from agreed measures of usage, purchase, renewal and cost, sized by accounts and by what they are worth
- Your propensity scores: Stradem uses the results for each score band to help prioritize opportunities
- The first audiences, the size of each, the barrier that holds each back and the test to run
Output A prioritized list of customer groups, with the size of each, the barrier, the candidate actions and the source of the expected gain.
How customer groups become opportunities
Where AI helpsAI reads across the agreed data and explains what sets each group apart. The statistics run as repeatable models. The Stradem team checks the groups against your business, and your team approves the list.
Step 2, design an action your team can deliver and test
Journey Twin
Where in the journey does a change belong, and what does the team need to deliver and test it?
- Journey analysis: how customer groups move through the stages of a journey across channels, and where they stall, move up or drop off
- Where the change belongs: the stage where a message, an offer or a product fix is most likely to help
- Exclusions: the customers who already hear enough or are better left alone
- A test plan for the changes that matter most, with the delivery requirements and the owners
Output An approved brief: where the change belongs, who is excluded, what delivery needs, the owners and the measurement plan.
How this works with your journey platforms
Where AI helpsAI summarizes the patterns across journeys and drafts test ideas. The Stradem team judges which ideas your teams can deliver, and your team picks which to run.
Step 3, measure the value and guide the next investment
Growth Twin
What did each action add, and what should we do next?
- Valuation: what each action added in dollars, read against a comparison group where one is feasible
- Stack view: where your stack performs best, what needs to change and how to lean into what works
- A clear decision to scale, refine, stop or hold
- A decision log for every decision: what we expected, what happened, what the action added and the revised economics
Output A decision log with the forecast, the reported outcome, the tested gain and the revised economics, plus where to optimize your stack.
How expected value differs from evidence of impact
Where AI helpsThe measurement engine does the calculation. AI drafts the results summary in plain language, and a person reviews it before it is shared.
Who does what
The platform and the team, working with yours
Your platforms run the approved actions. The Stradem team sets up the workspace, works through each decision with your team and hands over more of the work as your team chooses.
| Twin | You provide | The platform does | The Stradem team does | You decide |
|---|---|---|---|---|
| Segment Twin | Aggregate data from your customer data platform or data lake on customers, costs and outcomes, and your goals | Groups customers from the aggregate data and sizes each group | Proposes the customer groups and ideas worth testing, checks the evidence and runs the working sessions with your sponsor | Which customer groups to prioritize first |
| Journey Twin | Journey and channel data, and what your platforms can run | Maps the stages and shows where a change, a pause or a test is worth making | Designs the tests with your marketing and platform leads and supports the launch | Which tests to run |
| Growth Twin | Results once each test closes | Measures what each action added and values it | Interprets the result with your team, recommends the next investment and records the agreed decision | Whether to scale, refine, stop or hold |
The workspace
Each decision builds on the last
Every engagement adds segments, assumptions, tests and results to your workspace. Your team can access and export them.
Responsible AI
AI that covers more of your options
Stradem uses AI to compare far more segments, journeys and channels than a team could by hand and to draft briefs and results summaries. Every analysis runs on an agreed model, and the Stradem team reviews each output against your business before it informs a decision. Customer-level records stay in your systems.
- A named person on the Stradem team and one on yours review each list, plan and results summary
- Every number shows its method
- Customer-level records stay in your systems
Who it is for
What each leader gets
Stradem serves the people who lead customer revenue and the people who run the systems behind it.
- MarketingThe segments, journeys and tests to start first, each with its expected return.
- FinanceEvery option valued on one basis, with the target return stated.
- ProductWhat a fix needs to start: the team, the capacity and an owner.
- SalesA way for added coverage to compete for budget on the same basis as a campaign.
- DataModels built on agreed aggregate data, with every number showing its method.
- ITRuns above your existing platforms on agreed files. Customer-level records stay in your systems.
Questions leaders ask
Does Stradem use propensity models?
Stradem's standard approach uses aggregate measures and the results of propensity models your team already operates. It uses those results to prioritize opportunities and design tests. Segment Twin groups customers or accounts from agreed measures of usage, purchase, renewal and cost, sizes each group and shows the barrier and the candidate actions. A customer who is likely to buy may buy without an offer, so Stradem values an action on its tested gain. Your team approves the list. See how customer groups become opportunities.
Does Stradem support omnichannel marketing and personalization?
Journey Twin studies journeys across email, web, app, ads, sales and service. It shows where personalization helps, where to reduce contact and what to test. Your own platforms deliver the experience, and the results return to Stradem.
How does Stradem value customers and opportunities?
Growth Twin puts a dollar value on each segment, journey and action. It reports what each action added against a comparison group where one is feasible, so the next investment starts from evidence. Read how the measures differ.
Does Stradem replace our customer data platform or journey platform?
Your customer data platform keeps customer profiles, and your journey platform keeps delivery. Stradem receives agreed aggregate data and does the analysis across them. The approved plan goes to your platform owners as a brief. See how Stradem works with your customer data platform.
How does Stradem relate to next-best-action?
Customer decisioning platforms choose the next message or offer for each customer. Stradem works one level up: it compares initiatives that compete for budget and delivery capacity across teams. Results from decisioning programs inform the next investment. Read the comparison.
What data does Stradem use?
Stradem works with aggregate data: agreed counts, rates and totals on customer groups, costs and outcomes, usually from your customer data platform or data lake. A small or partial data set is enough to start. Customer-level targeting and assignment stay in your existing systems, and your platforms run the approved action.
How is impact measured?
Each test states its expected result and the rule for its decision before launch. Your platform runs the agreed random assignment. Stradem designs the test with your team and evaluates the results. Where random assignment is unavailable, we assess whether the available data supports a credible comparison, use an appropriate design where one is feasible and state its assumptions. Test results show an uncertainty interval where the design and data support one. Forecasts and reported outcomes are labeled separately with their assumptions and limitations. Read how the measures differ.
Can we keep the decision log?
Your team can access and export the decision logs, assumptions and results in your workspace. Your agreement sets out the details.