Wiland has introduced two new predictive models, WAIfarer and WAIfinder, adding neural network modeling to its predictive audience intelligence solutions. The technology is designed to help brands and nonprofits identify high-value prospects, improve customer retention, and support long-term revenue growth.

Introducing WAIfarer and WAIfinder

The new models use neural network techniques to analyze complex relationships across multiple layers of variables. Wiland says this approach can identify patterns and audience opportunities that may not be captured by conventional machine learning methods.

Early prototyping reportedly showed stronger performance than standard modeling approaches, including improvements in prospect discovery and merge survival rates.

Predictive Intelligence for Audience Discovery

Rather than focusing on generative AI or large language models, Wiland is applying AI specifically to predictive marketing use cases.

The neural network models are intended to help organizations:

• Find new audiences with a higher likelihood of responding.

• Identify additional high-performing prospect segments.

• Improve engagement with valuable existing customers.

• Discover incremental growth opportunities.

• Generate forward-looking insights from consumer spending signals.

Wiland says the capabilities can be particularly useful in non-cooperative data environments, where organizations have limited access to external or shared customer data and therefore depend more heavily on sophisticated modeling.

Integrated With Existing Data and Workflows

WAIfarer and WAIfinder are designed to work alongside Wiland's existing data assets and predictive frameworks. Clients can therefore adopt the new modeling capabilities without making major changes to their existing systems or workflows.

The company says the expansion strengthens its broader predictive analytics offering by combining consumer spending signals with more advanced modeling techniques.

Moving From Insights to Predictions

The launch reflects Wiland's focus on using AI to move beyond descriptive audience analysis toward predictive intelligence. By applying neural network modeling to consumer and audience data, the company aims to help marketers identify potential customer behavior and opportunities before they occur, supporting more targeted and data-driven marketing decisions.