Product promotion has always been about capturing attention and turning it into action. But the way companies approach promotion today is dramatically different from even five years ago. Instead of gut instinct and generic campaigns, marketers now have tools that can process massive volumes of data, recognize patterns invisible to the human eye, and execute campaigns automatically across dozens of channels. Artificial intelligence (AI) and automation don't just make promotion faster — they make it smarter, more personalized, and more measurable.

The shift from manual grind to intelligent promotion

Traditional promotion is labor-intensive. Teams build campaign assets by hand, analyze results in spreadsheets, and rely on assumptions about what their audience wants. This approach still works in some cases, but it doesn't scale when you're trying to engage thousands (or millions) of customers across multiple channels.

AI changes the equation. By processing behavioral, transactional, and demographic data at speed, it can reveal insights no team of analysts could reasonably uncover. Automation ensures those insights don't just sit in a dashboard but are acted upon instantly. A customer abandons their cart? An automated sequence using AI for email outreach sends them a reminder with a personalized incentive. A new product launches? Ads are generated, scheduled, and optimized without waiting on manual setup.

As Concord CEO Matt Lhoumeau puts it, “Automation isn't about replacing people. It's about freeing them to focus on what really matters.” That same mindset is driving the adoption of AI across marketing, finance, and operations — just as companies are adopting automated workflows to streamline other business processes.

How AI enhances audience targeting

Knowing who to reach has always been the first step in promotion. AI takes targeting beyond demographics into intent prediction. Machine learning models can segment customers based on subtle behavioral signals — for example, distinguishing between a casual browser and a high-intent buyer based on how they navigate your site.

  • Benefit: Campaigns reach smaller but more qualified audiences, improving ROI.
  • Challenge: Predictions are only as good as the data fed into the system. Poor data hygiene can sabotage outcomes.

The smarter your targeting, the less budget you waste shouting into the void.

Personalization at scale

Customers today ignore generic campaigns. They respond to experiences that feel tailored to them. AI tools makes that personalization possible across thousands of touchpoints:

  • Emails with subject lines optimized for each user's past open behavior.
  • Product recommendations pulled from browsing and purchase history.
  • Landing pages that adjust headlines or offers depending on the visitor's industry or role.

What once required hand-crafting dozens of campaign variations is now handled dynamically. The result is higher engagement, stronger relationships, and faster conversions.

But personalization has a double edge. Done clumsily, it feels intrusive (“Why do they know I looked at this yesterday?”). Transparency and customer consent remain vital.

Automation for consistency and efficiency

AI creates the intelligence, but automation delivers the execution. Campaign automation ensures that no opportunity slips through the cracks:

  • Abandoned cart recovery workflows
  • Retargeting ads triggered by site visits
  • Loyalty program reminders sent after a repeat purchase

Instead of relying on teams to remember every follow-up, automation guarantees consistency. This not only increases revenue but also frees marketing teams to focus on strategy and creativity rather than repetitive tasks. For example, creative teams often streamline production workflows by using dedicated video editing services to maintain visual consistency and brand quality across campaigns.

Matt Lhoumeau, who leads the contract intelligence platform Concord, says he's seen the same transformation in how companies handle routine agreements: “Most contracts today don't even need negotiation. Automation just makes sure they don't get lost in someone's inbox.”

Predictive analytics for proactive promotion

One of the most powerful uses of AI is prediction. Instead of reacting to customer behavior after the fact, predictive analytics helps companies anticipate it.

For example:

  • A retail brand can forecast which products will sell out during the holidays and promote them early.
  • A SaaS provider can identify accounts at risk of churn and target them with retention campaigns.
  • A subscription business can predict when customers are most receptive to upsell offers.

This turns promotion into a proactive growth driver. The downside? Predictive models require constant monitoring. Consumer behavior shifts quickly, and what worked six months ago may no longer apply.

See Part 2 for more...