The old way: launch, wait for results, learn what worked, adjust next time. The DoppelIQ way: simulate, see the reaction, adjust, then move with confidence, whatever product got you there.
Five ways to turn signals into answers. Start where your question is.
One living twin per real customer, fitted on your transaction, behavioural, conversation records and more.
Start with search, social, reviews & forums or market signals. Then bring in your 1P data to make the intelligence uniquely yours.
Explore by function. Each use case maps to a real question your team is already trying to answer.
Simulate your campaign copy, offer language, or creative concepts and know which resonates more.
See predicted reach, resonance, and response for a full campaign before committing media spend.
Different customer personas respond to different cues. Find which messaging pillars (value, convenience, quality, or occasion) resonate.
Test a new product tier or category extension and predict adoption rates by segment before committing investment.
Simulate cross-category expansion paths for your highest-value customers, with tailored offer timing and sequences.
Simulate at-risk customers and curate precisely targeted win-back messages at exactly the right moment.
DoppelIQ's ML pipeline groups customers purely by how they actually shop, as natural behavioural clusters emerge. No survey bias, no manual tagging.
Simulate variants on customer cohorts and predict the winning version. Reduce wasted test-and-learn spend.
Identify the share of your base who buy at full price anyway, and recover margin without blanket promotions.
Identify which segments are most likely to switch to a competitor or alternatives.
A general-purpose model imagines your customer. The twin is built from real signals about them, so the answer reflects how they actually behave.
Rebuilt as new signals arrive, with segment-level detail rather than one average customer.
Give us a brand name and a category and the system finds the signals itself. No data handover, no fielding, no recruitment.
Unreleased concepts, price moves and exit plans, all tested without a single real customer seeing them.
