Objective:
Our client in the insurance sector sought to understand the effectiveness of their advertising campaigns, especially on user searches. Their primary objectives included:
- Quantifying the advertising investment necessary to prompt a potential customer to initiate contact via phone, ask for a quote, or visit the brand’s website.
- Developing a reliable methodology to gauge the number of leads each televised advertisement generates.
Challenges:
The insurance sector is fiercely competitive, with multiple players vying for a share of consumer attention. Accurately gauging the efficacy of advertising campaigns, particularly regarding return on investment (ROI) and lead generation, is crucial to ensuring that marketing budgets are allocated wisely.
Solution:
To address these challenges, Sapience employed two-pronged analytical strategies:
- Econometric Models: These models were developed for every contact channel, both offline and online. The goal was to understand and quantify the impact of various advertising drivers on each track. The client could make informed decisions about future advertising investments by discerning which advertising channels yielded the most significant results.
- Application of Huff Models: The Huff models were leveraged to determine the probability that a lead generated could be attributed to one or multiple TV spots based on the time elapsed since the advertisement aired. This approach allowed for a more granulated understanding of the effectiveness of individual TV spots.
Action Taken:
A deep-dive analysis was conducted for each media channel after establishing the econometric models. This analysis was pivotal in understanding the efficacy of each channel in generating potential leads.
Furthermore, the probabilities derived from the Huff models were used to assign leads to specific TV spots. This facilitated the calculation of the cost incurred for each lead.
Results:
- Comprehensive quantification of contacts generated via different advertising strategies enabled the differentiation of results by campaign type, media, and format.
- The client could accurately assign leads to specific TV spots. This granulated insight empowered them to calculate the ROI for each advertisement, ensuring a more optimized advertising spend in future campaigns.
Conclusion:
By harnessing the power of econometric and Huff models, the insurance brand was able to transform its advertising strategy. With clear insights into each ad campaign’s cost-effectiveness and lead generation capabilities, they could make data-driven decisions that maximized their advertising ROI. This case underscores the importance of analytical methodologies in optimizing advertising investments, ensuring that brands get the most out of every advertising dollar spent.