Applied AI · Marketing Operations · SMS · Decision Support · Cost Optimization
Building an AI-Enabled SMS Optimization Tool
The challenge
SMS creates an unusual optimization problem: marketers need to balance the quality of the message with character limits, message segmentation, cost, timing, and campaign planning.
Those decisions are interconnected.
A small copy change can affect the number of SMS segments required. That can change campaign cost. Meanwhile, the least expensive message isn’t necessarily the most effective one.
I saw an opportunity to bring those decisions together into one workflow.
The solution
I designed and built an AI-enabled SMS optimization workspace that brings planning, cost estimation, technical SMS analysis, campaign management, and copy optimization into one experience.
Sanitized view of the SMS optimization workspace, combining message planning, credit estimation, SMS encoding and segmentation analysis, campaign management, and copy guidance.
Recreated with representative data. Proprietary company information, internal cost structures, and campaign data have been removed.
Credit and cost estimation
Estimates the messaging credits required for a proposed send so marketers can understand cost implications earlier in the planning process.
Cost optimization recommendations
Identifies opportunities to reduce unnecessary message length or segmentation while preserving the intent of the communication.
Copy optimization
Analyzes proposed SMS copy and recommends improvements for clarity, concision, and effectiveness.
Campaign calendar
Provides a consolidated view of planned SMS activity, helping teams understand messaging volume and timing across campaigns.
Rather than requiring marketers to separately calculate cost, edit copy, and evaluate timing, the tool makes those considerations part of the same decision-making process.
Building toward a smarter system
The initial tool solves immediate operational problems, but I designed it with a broader optimization model in mind. The next stage incorporates:
- –plannedHistorical campaign performance — using previous sends to inform recommendations around copy, timing, and other campaign decisions.
- –plannedGenerative SMS copy — creating draft copy based on campaign objectives and requirements, building on prior work developing AI-powered email copy generation.
- –plannedIntegrated UTM creation — connecting the tool with a separate UTM/link builder so campaign setup becomes more streamlined and consistent.
Over time, the goal is to move from a collection of utilities toward a connected system that can help marketers plan, create, evaluate, optimize, and learn from SMS campaigns.
My role
I identified the operational opportunity, designed the product and workflow, and used AI-assisted development to build the working application and its optimization capabilities. I am also defining its evolution from a practical operational utility into a more data-informed decision-support system.
Why it matters
This project represents the kind of applied AI work I’m most interested in: starting with a real business problem and using AI to create something people can actually use.
The technology is valuable because it can reduce manual work, surface decisions earlier, control costs, improve consistency, and eventually turn historical marketing performance into actionable recommendations at the moment marketers need them.