The Intelligent Investing winback and cross-sell

Leadership wanted investing activations out of a dormant base of roughly 900,000 people. The first thing that mattered was that it wasn’t one audience: some had gone quiet on Intelligent Investing, but a large part of the pool were lending customers who had never invested with us at all, which is a cross-sell rather than a winback.

The two products needed different pitches on top of that. Manage is automated weekly investing into an S&P 500 strategy. Self-directed is manual trading with research alongside it. One list, four different conversations.

And I genuinely didn’t know what the list quality was. Pruning it on guesswork would have thrown away contacts that were still worth something, so that question had to be answered under real campaign conditions rather than assumed.

Build it as a multi-iteration program rather than a campaign. Iteration 1 would do two jobs at once: give a real read on conversion, and act as the list clean-up, since engagement under live conditions is the only honest signal of who is still reachable.

Two behavioural hooks anchored the whole thing. For the Manage path, an investment calculator where someone could model what a small weekly contribution grows into by 75. For Self-directed, Fiscal.ai — a research tool already included in every Mogo membership, so the pitch was about something they already had.

Messaging split by relationship rather than by segment name. Lending customers got progression: you have borrowed with us, here is how to start building. Dormant investors got resumption without judgment: you paused, and you are still an investor as far as we are concerned.

Conversion rate, with one condition attached: Iteration 1 was also the decision gate for how to treat the list afterwards — who to keep, who to cull, and what to do with the segment that never engaged at all.

Iteration 1 ran February to June 2025 across the full pool. Re-introduction in month one with a subject-line resend to non-openers, product-specific tracks through months two and three, then objection handling in months three and four using a one-click survey where people named their own barrier — too risky, cash flow, confused about the products, or already investing somewhere else. Each answer got its own response: risk mapped to long-term dollar-cost-averaging education and the calculator, cash flow to micro-contribution framing at ten or twenty dollars a week, confusion to plain product explainers, and other platforms repositioned as complementary rather than competitive. Months four and five tapered off for the coldest segments.

That round converted about 2.7%. Afterwards I culled hard bounces, spam complaints, and anything with three or more soft bounces, which brought the reachable audience to roughly 600,000.

Iteration 2 ran July 2025 to January 2026 on the cleaned list and converted about 5% — around 30,000 people who either activated for the first time or came back to real activity. The structural call in that round was what to do with people who had never interacted at all. Going dark on them risks a reputation spike whenever you eventually return, and normal cadence just burns them, so I ran a low-frequency monthly drip instead: one educational email a month, alternating between calculator content and Fiscal.ai research concepts.