Optimizing your spend in marketing is critical, but hard to get right. Boltzbit’s generative AI helps companies make better investment decisions.

As your organization handles more and more data, it becomes more and more difficult to operationalize and organize that information for data-driven decision making. At the same time, there are important areas where you don’t have enough data to make sound predictions.

Our no code platform makes it easy to create AI solutions to tackle your biggest problems. Boltzbit proudly works with:

Budget Optimization: Marketing Mix Modeling

Marketing has become more and more scientific, but being able to shift to a full speed data-driven approach has been overwhelming. While you have access to more data than ever before, it’s painstakingly difficult to combine this into useful insights about where and how to invest your limited marketing budget for maximum ROI.

Our customer used their historic user acquisition data to train Boltzbit to identify patterns in user behavior, reasoning for market trends, and suggest the optimal mix of marketing actions providing the best return of investment.

This allowed the customer to make more confident decisions on how to build their marketing strategy and budget. The mix modeling process which typically takes weeks was done in a matter of hours.

Forecasting: Predicting Market Behavior

Being able to forecast demand is the strongest way to predict and therefore optimize company growth. But predicting consumer behavior often must rely on more art than science as building robust models is resource intensive, slow and requires access to well segmented data.

Boltzbit was able to ingest the complex dataset of our customer and quickly begin bi-directional deep learning. Our platform; the first to use generative AI, completed multiple tasks at the same time. This allowed them to determine the likely purchasing behavior of their existing and new users in advance to order placement.

The customer was then able to build hyper-relevant campaigns and promotions for specific consumer segments to ride existing market tailwinds.

Automation: Improving Customer Engagement

Engaging customers at scale often loses relevance and personality as the 1-to-many model favors broad communication over specific. At the same time, the number of channels for mass communication is only increasing and each still demands an authentic and cohesive brand voice at lightning speed.

Our customer used generative AI to create natural language content to be used in user communications across email, chat, ads, query responses and targeted messaging. Their AI cube understood what resonated with their users and quickly provided multiple versions of impactful, on-brand and effective communication.

This saved a huge amount of time for the marketing team in spinning up new campaigns, channels and increased the efficacy of chatbots to quickly get users to the right destination.

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