Mega brands need new sources of business to sustain double-digit growth on a substantial base.
As brands grow, bringing in the next wave of growth becomes increasingly difficult. Increasing consumer loyalty, retention and acquisition are required. Reaching out to untapped consumer segments and need-states can bring unexplored users and usage occasions. We also need to map out new consumer segments and their potential vis-à-vis the current target segments. The latest macro and category-related trends need to be incorporated. We must evaluate the opportunities and threats from other interacting categories from a share of wallet perspective. Identify triggers and barriers in the purchase journey. Analyze how this varies across markets and create a granular go-to-market strategy across consumer segments and brand offerings.
Data science helps integrate internal and external data sources and re-engineer business growth.
Integrating multiple data sources is essential to identify and unlock new avenues of growth. Combining brand, category, consumer, market and media insights from internal and external databases and layering them with purchase power and sales indicators; helps arrive at need-gaps along with headroom for growth; attitudes, motivations and beliefs to leverage; and the consumer touchpoints to activate. For a leading jewelry brand, we used a multi-level fusion of different data sources to derive untapped consumer segments based on life stage and mindset. Fusing this with the share of wallet indicators, we identified new geo-locations. This effort led to a comprehensive rule book and road map that helped develop new product offerings and go-to-market strategies, leading to a big jump in ROI, effectiveness and business growth.
Robust multi-variable data sources, data-mining and domain knowledge are vital to the process.
The quality and depth of both internal & external data sources influence the ability to mine and identify new avenues of growth. Data warehousing pulling in different sources of year-on-year data is needed. A deep-diving multi-variable analysis is required to decode the operating environment’s complexity correctly. Domain knowledge plays a crucial role in setting the testing hypothesis and interpreting findings. Finally, actions taken on the new results play a pivotal role in success. In the quoted example, the multi-level fusion led to new product offerings targeted at new consumer segments, new distribution channels, redeployment of media, and new communication cues to appeal to the sensibilities of the new consumer segments.