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Paper A

Role of AI in Marketing Analytics and Business Decision Making

Asst Prof. Ashwini Kende — 2026 — International Journal for Research in Applied Science and Engineering Technology (IJRASET)

peer reviewed journal article  ·   ·  test this week

Key findings

• AI tools — like machine learning and predictive analytics — let businesses predict what customers are likely to buy next, which customers might leave, and what demand will look like. This makes planning faster and less guesswork.
• Companies that use AI for customer segmentation (sorting customers into groups based on behavior) can send more targeted messages, which tends to improve how many people actually respond or buy.
• AI-powered personalization — like Amazon's product suggestions or Netflix's recommendations — increases customer satisfaction and loyalty by showing people things they're actually interested in.
• Automating marketing tasks with AI (such as sending emails, running chatbots, or adjusting ad bids) reduces manual work and human mistakes, freeing up staff time and cutting costs.

Marketing implications

• If you're still manually segmenting your email list by hand (or not segmenting at all), try a basic ML-based segmentation tool — even free or low-cost options can group customers by past behavior and help you send more relevant messages.
• If you run an e-commerce store, add a recommendation widget that shows related products based on what customers have viewed or bought. This is one of the most documented ways AI increases average order value.
• If your team spends time on repetitive tasks like scheduling emails or responding to the same customer questions, try one AI automation tool this month — even a simple chatbot or automated email sequence — and measure how much time it saves.

Paper B

AI-Driven Marketing vs Traditional Marketing: A Strategic Shift

Sanjay Kumar Padhy, (Dr) G. Mahesh — 2026 — International Journal of Versatile Research and Analysis

peer reviewed journal article  ·   ·  watchlist

Key findings

• AI marketing lets businesses show each customer different content based on what that person has already browsed, bought, or clicked — unlike traditional ads that send the same message to everyone.
• Traditional marketing (TV, radio, print) is expensive and hard to measure — you often can't tell exactly how many sales came from a billboard. AI marketing tracks results in real time so you know what's working and what isn't.
• AI can handle repetitive tasks automatically — like sending follow-up emails or answering customer questions via chatbot — which saves staff time and keeps responses consistent around the clock.
• The authors argue that the best strategy today is a hybrid: use AI tools for targeting and automation, but keep traditional methods for brand storytelling and reaching audiences who aren't highly connected digitally.

Marketing implications

• If your team is still doing batch-and-blast email campaigns, this paper confirms the direction the field is moving: swap to triggered, behavior-based emails (e.g., send a follow-up only to people who clicked but didn't buy).
• Don't abandon traditional channels entirely — if your audience includes older or less tech-connected customers, a TV spot or direct mail piece can still build trust in ways an Instagram ad won't.
• Start measuring everything you can digitally. The core advantage AI tools offer over traditional ads is that you actually know what worked — so even before adopting AI, get your analytics baseline set up.

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