Leading US-based fashion retailer with online and brick & mortar presence.
The client had recently adopted a new omni-channel strategy without foreseeing that the new strategy would make their conventional market mix modeling algorithms obsolete. The data came in from multiple sources. 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.
SG Analytics constituted a team of data experts and modeling specialists to deliver the following solution:
By combining its in-depth understanding of various data sources along with the client’s business knowledge, SG Analytics' data scientists 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, our team had in-depth interactions with the client and decided on a distributed linear attribution model.
The team then built a model to explain the effect of channels on sales and quality of fit.
As a value-added service, our team built a simulator for “what if analysis” and added a visualization layer over the model.
Helped provide clarity on effectiveness of the current marketing spend, allocation of marketing dollars, and assessing channel efficiency and saturation.
Devised a seamless marketing mix methodology which covered both online as well as the brick & mortar business.
Ensured adoption across multiple business users by designing scenarios and visualizing the effect of changes in marketing strategy.