Client
A leading US-based fashion retailer with online and brick & mortar presence.
Opportunity
The client’s omni-channel strategy had made their conventional market mix modeling algorithms/ strategies obsolete. The data came in from multiple sources and each source had a different format ranging from TRPs, GRPs, Impressions, Likes, Views, App Downloads, etc. Moreover, there was no mechanism to attribute the returning revenue to all the touch points in the buying journey.
Value Delivered
- Helped provide clarity on the effectiveness of the current marketing spend, allocation of marketing dollars, and assessing channel efficiency and saturation.
- Devised a seamless marketing mix methodology that covered both online and the brick & mortar business.
- Ensured adoption across multiple business users by designing scenarios and visualizing the effect of changes in marketing strategy.
Solution
SG Analytics constituted a team of data experts and modeling specialists to deliver the following solution:
- By combining the in-depth understanding of various data sources along with the client’s business knowledge, the SGA team defined business rules to standardize the data and brought all data sources at the same level for primary EDA and ease in modeling.
- To decide sales attribution, the SGA team had in-depth interactions with the client, and decided on a distributed linear attribution model.
- The SGA team then built a model to explain the effect of channels on sales and quality of fit. • As a value-added service, the SGA team built a simulator for “what if analysis” and added a visualization layer over the model.
Value Delivered
- Helped provide clarity on the effectiveness of the current marketing spend, allocation of marketing dollars, and assessing channel efficiency and saturation.
- Devised a seamless marketing mix methodology that covered both online and the brick & mortar business.
- Ensured adoption across multiple business users by designing scenarios and visualizing the effect of changes in marketing strategy.