MTA Case study
Identifying key campaigns that led to conversion using Multi Touch Attribution (MTA).
Problem:
The client (in B2B space), wanted to understand which campaigns were driving no. of orders on their website. They were running social media campaigns on LinkedIn, Google, Bing and Twitter.
The client wanted to get an idea of how their customers interacted with different touchpoints and which customer journeys were leading to conversions.
Solution:
- We implemented MTA algorithm using Markov chains to attribute conversions to various campaigns the client ran in 1 year.
- The Markov chain algorithm was compared with other heuristic approaches like First-Touch, Last-touch, and Linear-Touch conversions.
- Top customer journeys which were leading to conversions were identified
- Cost per order was computed and compared for all campaigns to analyse which campaigns generated higher ROI.
Impact
Identified top campaigns driving conversions.
The cost per conversion metric helped in classifying campaigns into higher CAC and lower CAC.
10% more marketing spends were spent on campaigns with higher CAC.
6 % more lead conversions were observed.
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