Revolutionizing Digital Marketing Analytics

The digital transformation of customer-facing sales and service functions leveraging artificial intelligence and machine learning is rapidly creating winners and losers. According to Forrester Research, those that excel “will steal $1.2 trillion dollars from those that don’t by 2020*.”

In order to stay relevant and compete effectively in today’s competitive landscape, every customer interaction must be maximized via rich, highly precise insights that inform the right actions and dialogs.

Challenges with Static Segmentation

Marketers cannot afford to be irrelevant in the digital world, and inability to serve customers in the time of need augments that risk. In fact, 98% of marketers suffer from a long list of issues with static segmentation, from insufficient actionable detail to segments that don’t update based on changing customer behaviors to a lack of precision. The takeaway: static segmentation cannot keep up in the digital age.

Maximizing Customer Interactions Requires Instant & Complete Insights That Create Relevant Experiences


The amount, frequency, & velocity of customer data across channels, platforms & devices has surpassed the capacity of human driven statistical based analytics.


Most ML methods are black boxes, data goes in & predictions come out, but there is no way to know why the prediction is made; “the Why” is essential for informed actions to maximize each customer interaction.


simMachines spent 12 years developing game changing advances in similarity-based machine learning, enabling predictions with the why at speed & scale.

Machine Learning for Marketing

Today’s marketers and advertisers need the scale and speed of machine learning in order to keep pace with increased consumer expectations for relevancy.  simMachines marketing applications leverage proprietary algorithms to provide precise predictions and rich insights through transparency at speed and scale.  We enable clients to quickly and significantly upgrade insight-driven marketing capabilities.

Machine Driven Customer Lifecycle Predictions

Achieve 20% to 100% performance life across acquisition, upselling & cross selling, increased profitability, increased purchase frequency/usage, risk, expanded LTV, retention, and win back.

Dynamic Predictive Customer Segmentation

Reveal granular machine driven customer clusters instantly for greater marketing and advertising campaign precision and speed.

Contextual Customer Experience Predictions

Predictions anticipate what an individual customer will want, prefer, or need, dramatically improving the customer experience with “up to the moment” data fueling sub-second recommendations.

Customer Trending & Analysis

Reveal patterns over time for gaining insight into customer trends. Whether its channel preferences, product usage, or customer level behavior, trending enables deep understanding and new insights.

Supply/Demand Forecasting

Analyzing supply and demand forecast factors and predicting future demand curves at deep granular levels of detail can dramatically improve supply planning and sales results.

Anomalous Pattern Detection

Similarity provides the ideal tool for identifying anomalous behavior, and the why provides unmatched insight into causes of such behavior revealing emerging trends and opportunities.

Call Center/Social Media Analysis

Cluster and analyze the actual conversation and comment content vs. simply sentiment and type to understand with much greater depth what customers really think and say.

“Dynamic predictive segmentation (DPS) is the future. Marketers require analytics-driven tools and it’s no surprise that dynamic predictive segmentation is the fastest growing segmentation method. Perceived benefits of adopting DPS include discovery of new opportunities, ability to react more quickly to competitors, increased customer engagement, and improved customer experience.”

Capture The Customer Moment With Dynamic Predictive Segmentation, a January 2018 commissioned study conducted by Forrester Consulting on behalf of simMachines.

Use cases

simMachines supports use cases for marketing spanning customer lifecycle predictions, dynamic predictive customer segmentation, customer experience management, sales forecasting, trending and analysis.

Churn Prevention

Large international telecommunications provider needed to reduce churn for pre-paid phone cards.

Sales Forecasting and Customer Lifetime Value

Specialty retailer needed to calculate the future sales and lifetime value of customers.

Machine Learning Fraud Prevention

Top 3 financial institution wanted to speed up ability to implement ML fraud detection solutions for e-commerce clients, enable continuous learning, and expose the factors driving the fraud.

Recent news in marketingALL NEWS ON OUR BLOG

Dynamic Predictive Segmentation Will Upgrade Retailers Relevancy with Shoppers
Dave Irwin | 30, November
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Machine Learning with Transparency Changes the Art of the Possible in Marketing
Dave Irwin | 20, October
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Marketers Need Granular Transparency Behind Machine Learning Predictions
Dave Irwin | 26, September
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*The Insights-Driven Business, July 2016, Forrester Research

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