MACHINE LEARNING ANALYTICS

We build better models. It’s that simple.

Direct marketers must continuously improve performance.
It’s not an option, it’s an imperative.

We combine our Big Data assets with a purpose-built Machine Learning platform optimized for direct marketing applications.

The platform optimizes your acquisition, upsell and retention campaigns, enabling you to cost-effectively obtain more customers and maximize their value. This approach generates results that are 15% – 30% greater than traditional segmentation models. Think of it as modeling on steroids.

For decades, the workhorse in statistical modeling has been regression analysis. Incremental advances have been made over time, however, the underlying structure of the approach hasn’t changed much in the last 20 years.

Unfortunately, traditional regression analysis begins with a reduction in the size, depth, and complexity of the information being analyzed. This inherent weakness creates trade-offs which negatively affect model performance. It also creates waste as valuable prospect records are discarded to reduce overall model complexity. In fact, most regression models utilize only a handful of variables in their final solution.

The volume and complexity of marketing data available today is unmanageable using traditional modeling and data mining techniques, highlighting the need for a better approach. 

Machine learning gives computers the ability to learn from data without relying on a rules-based program and is unconstrained by the limitations of scale and complexity associated with traditional modeling approaches.

Machine Learning for Direct Mail Marketing

What is it and how does it work?

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If you are struggling with disappointing results from your direct mail programs, machine learning could be your ideal solution. Learn how this type of artificial intelligence is transforming our client’s marketing programs.

How Our Platform Works

We gather thousands of pieces of data for every client project, aggregating your campaign histories and customer responses with our in-house databases which include demographic, socioeconomic, psychographic and buyer/donor behavior data on every household and firmographic details on every business in the country.

Our machine learning platform churns through the data on a massive scale, analyzing thousands of combinations of variables in sub-second intervals. It then creates highly complex algorithms to isolate high-value prospects wherever they may be found within the data set. This approach allows us to identify prospects that aren’t typically found via traditional models and produce higher overall universes of viable prospects. Moreover, the platform gets “smarter” over time as new instances of promotions and responses are analyzed, which increases response rates and helps to overcome list fatigue.

Some clients have ‘broken’ models that are no longer working. Others are seeing their results slip over time and need to address the downward trend before it’s too late. Almost all are being pressured to do more with less and to produce greater results for their companies. Regardless of your level of sophistication and wherever you’re at on the analytics spectrum, we encourage you to discover what machine learning can do for your organization.

Our Approach

Our unique approach to machine learning is based on a ground-up build out of the IT infrastructure rather than using off-the-shelf, black box solutions which have limitations in computational and parallel processing speed and, therefore, produce inferior predictive algorithms.

Our approach is a highly dynamic framework which utilizes simultaneous training of multiple algorithms for each project. Algorithms adapt to new sets of training data, allowing them to get stronger over time as the latest campaign results are analyzed and the algorithms further refined.

Once only the domain of the largest organizations and academic research facilities, the exponential increases in computing power and decreases in cost are allowing us to bring machine learning to market at price points that are comparable to traditional modeling projects.

 

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