The client is a large mobile wallet organization having millions of transactions every month. They started executing several marketing campaigns to increase their reach and brand awareness. However, the success rate was very low compared to the industry benchmarks. The client has over 80 million records of unstructured data and the entire campaign was being run without proper buyer persona identification. The campaign costs were escalated with no returns.
Exponentia identified the big challenge- unstructured data. The solution was in the data too. An analytics engine was used to identify and extract customer segments from the underlying unstructured data defining buyer persona.
The super segmented data had:
- Buying behaviour of the customer
- Buying habits
- Likes dislikes
- Spending capacity
In addition to these insights 7 primary customer segments were recommended which could be sliced into over 50+ distinct customer sub-segments. This helped the client to execute high-touch and highly personalized campaigns which saw a significant increase in the response rates.
Increase in campaign hit rate
Million transaction rows converted into structured data