AI in Marketing Analytics
Hype vs Reality
Subhash Madireddy
About Me : 12 Years in Data Analytics
2012-19
2019-21
2021-23
2023 -
Change is Constant - Rate of Change is NOT
2025
2023
2012
More change in the last 2 years than in previous 10 years
Relevant Skills in Marketing Analytics have changed
Interview Question I used for 10 years
Week
Marketing Spend
Price
Sales
–
–
–
–
–
–
–
–
Write Python or R script to run regression : Sales as a function of Price & Marketing Spend
Is AI replacing marketing analysts ?
● Large task-oriented teams → Lean and strategically focussed teams
● Organizations with limited budgets can build great data science teams
● Roles focused solely on execution and simple tasks should diminish
Changing Expectations from data science teams
● Bring structure to abstract and vague business problems
● Communication and influencing skills
● Appropriate use of AI tools
Who is at risk?
Marketing Budget Allocation Problem
Distribute Facebook marketing budget among these segments optimally
City - 1
Men
City - 2
Men
City - 3
Men
City - 4
Men
City - 1
Women
City - 2
Women
City - 3
Women
City - 4
Women
AI Hype and reasonable expectations
Gen-AI tools help here
Analytical
Capabilities
More widely available
and becoming cheaper
Compute Power
Gen-AI has limited role here
Quality &
Quantity of Data
Actionable
Insights
Marketing operates with weak and in-complete data
Big Data vs Small Data
Customer Id
Age
Sex
Number of
Visits
Purchases
Returns
Customer Id
Age
Sex
Number of
Visits
Purchases
Returns
1
1
2
2
3
3
--
--
--
--
10,000
10 Million
Gen-AI democratizes analytics capabilities
Not much change in what can be done
New possibilities emerge with novel AI
algorithms and availability of compute power
Thank You