The Organisation

An up and coming Indian e-commerce organisation focused on bringing the joy of cup of Indian tea to the world over. Working directly with the tea growers  who hand select the tea ensures they have the best selection. With the latest of technology and great care taken in storing and packaging, the organisation is able to transport the freshest of teas to any part of the world. The organisation is looking to apply Analytics to further sharpen and optimise their marketing strategies. 

Analytics Goal

Identify the profile of individuals buying Premium Black Tea from a particular continent.

Success Metrics

Identified two distinct profiles of individuals who buy Premium Black Tea with data from the CRM and social data allowing for sharper targeting of marketing campaigns.

The Redwood Solution

- Built out an Analytics datamart from the customer data shared. The final datamart had over 50 data points derived from the original 6 data points that was being captured in the CRM. 

- Multivariate Cluster Analysis was applied on this datamart to segment the customer base of premium black tea based on their share of revenue. 

Impact of Analysis

Identified two distinct segments  who buy Premium Black Tea

Identified the major brands of Premium Black Tea that make a larger contribution to the overall revenue from Premium Black Tea. 

Data Augmentation

The data of the two segments was further augmented with social data to understand the digital/ social profile of these segments. 

As a result of this, a very clear understanding of the two segments  which were digitally/ socially very distinct were generated. As a result targeting and messaging of ad campaigns were built out separately for each segments, leading to a more optimised campaign strategy. 

Predictive Modeling to identify factors that influence success of Facebook Ad Campaigns

- All Facebook ad campaign details were collated and an analytics datamart of the same was built out. 

- Multivariate statistical analysis was conducted on the same to identify the factors that influenced a high degree of purchases directly from an ad campaign. 

As a result of the above analysis, a benchmark was set for future ad campaigns. This ensured the future ad campaigns were geared for higher degree of purchases/ revenue.