Marketing

Using artificial intelligence in marketing

From campaign automation and strategy optimization to data analysis and personalization — how AI makes marketing more efficient.

27.03.2024 · Sergey Kozlov
Using artificial intelligence in marketing

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Campaign automation Strategy optimization Data analysis Personalization

Modern marketing is being reshaped by technology — and artificial intelligence (AI) plays a particularly visible role. AI doesn’t just make a marketer’s job easier; it unlocks new ways to create, manage and scale marketing strategies. From deep analytics to individualized experiences for each customer, AI is becoming a real competitive advantage.

1. Marketing campaign automation

With AI, companies can significantly reduce the time and resources spent on repetitive marketing tasks. Common areas include:

  • Email marketing: AI analyzes recipient behavior, chooses optimal send times, and adapts subject lines and copy to each user.
  • Campaign management: algorithms optimize targeting, adjust bids and forecast outcomes before launch.
  • Content creation: generative models (e.g., ChatGPT) help quickly produce brand‑adapted drafts.
  • Publishing schedules: AI optimizes timing and content plans for social media.
  • Performance monitoring: AI monitors KPIs and suggests real‑time adjustments.

This lets marketers focus on strategic work — brand building and scenarios that require creativity and judgment.

2. Strategy optimization

AI doesn’t just analyze large amounts of data — it changes how decisions are made. Machine‑learning models process signals from many channels: web analytics, CRM, social media, on‑site behavior and even external sources. AI finds patterns that are easy to miss with manual analysis, enabling not only reaction but prediction — decisions based on data rather than intuition.

Example: when planning a campaign, AI can identify the most promising segments, recommend formats and propose A/B testing ideas — helping you adapt faster to changing markets and customer behavior.

3. Data analysis

In digital marketing, data is a strategic asset. With AI, marketers get deep behavior analysis: from visited pages to paths to purchase. AI combines signals from multiple sources into a unified view of the customer. This enables forecasting as well — for example, predicting churn and identifying the most valuable segments for retention strategies.

4. Customer personalization

AI has become a key tool for personalization. It analyzes interaction history, preferences and real‑time behavior to generate relevant offers.

Example 1: ecommerce recommendations based on unfinished actions (views, carts).

Example 2: email systems that automatically select subject lines, visuals and CTAs based on behavior.

Example 3: a blog that suggests articles aligned with the reader’s interests and history.

Example 4: ads that adapt creatives to location, time of day and previous interactions.

This level of personalization builds trust and increases the likelihood of repeat engagement.

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