Direct Mail Optimization

Improve Campaign Performance and Reduce Costs with Predictive Modeling.

Modern Direct Mail Shouldn’t Exist Without Optimization

Whether direct mail is a “new” channel to your business, or one that has been leveraged for years, optimization will enable you to deliver more effective and profitable campaigns.

Save Money

Predictive models will rank prospects based on projected performance, so you can focus on consumers who are most likely to generate a profitable return. Save on printing, postage and fulfillment and redirect your marketing investment to deliver greater ROI! Need help justifying an additional program cost? We’ve got you covered.

Deliver on Your KPIs

Focus on top-ranking prospects or customers who are most likely to take a preferred action. On-demand models can be quickly tested to improve response or payment rates, or use your 1st party data in combination with the Alliant DataHub to build a model that is tailored to your definition of success.

Keep the Audience in Focus

For many consumers, behavior changes depending on the channel. Alliant’s predictive models helps multichannel marketers forecast how someone will respond to direct mail specifically, allowing them to make the most of the channel.

Don’t Sacrifice Volume

Dropping segments of your audience does not have to mean smaller campaigns. A robust optimization program empowers you to identify other qualified sources with the same model. Find hidden pockets of potential high-value customers in your own data, or backfill with proven audiences that match your needs.

Direct Mail for All

Alliant has a rich history supporting direct mail marketers across industries and business models. Let our experts contribute to your next great campaign.

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Machine Learning Works for Direct Mail, Too

Machine learning is not just for digital campaigns – Alliant uses a suite of ML algorithms to build marketers innovative solutions for acquisition, retention and reactivation efforts. Each algorithm has different strengths. Using them together produces stronger results than any single one on its own.