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case studies

18 | 12 | 2024

How Liberty identified 15% optimization with MMM

Context A team designed to deliver solutions. Liberty Latin America, the leading telecommunications and technology company in Central America and the Caribbean, has an internal team dedicated to developing tools and solutions to support their marketing teams. These include forecasting tools, dashboards, predictive models, statistical robustness, and more. In a typical sales process, Liberty generates online leads and activates users through their call center. However, they faced increasing challenges in accurately calibrating digital attribution with activated users, highlighting a clear need to fine-tune their media performance. From spending more to spending smarter. While Liberty’s team was already implementing advanced optimizations across their digital channels, they chose to further enhance their advertising investment through Marketing Mix Modeling (MMM). This approach enabled them to identify the optimal media mix based on their sales data and reallocate their budget to maximize results. Challenge Comparing apples to oranges. The first major challenge in this project was normalizing data across online and offline channels to make meaningful comparisons—especially when trying to align daily metrics (online) with weekly metrics (TV, radio). Understanding impacts beyond marketing. The second challenge was incorporating variables outside the marketing area to explain final activations. For instance, analyzing how many days passed between a lead registration and user activation. Solutions in stages Before working with us, Liberty’s marketing mix model had a statistical confidence level of an R² Adjusted of 0.39. To build a complete and statistically reliable marketing mix model capable of identifying where to optimize media investment, our Marketing Science team provided several recommendations to Liberty Latin America's data insights team. The suggested optimizations were implemented in stages: STAGE 1: Interpolation → Data collection and normalization Weekly data gaps in offline media were resolved by simulating normal distributions of the missing data. This allowed the standardization of data within those gaps, converting weekly groupings into daily distributions. STAGE 2: Share of voice → Liberty vs. competitors We modeled the effect of share of voice in the market by analyzing Liberty’s keyword bidding data and their search impression share to estimate their market presence. STAGE 3: Delayed Index → From order variable to activation variable The model initially struggled because it used conversions, whereas Liberty’s business hinges on product activations. To address this, we developed a Delayed Index, which integrated the average number of days it takes to transition from an order to an activation into the model. STAGE 4: Back-casting → Simulating the future to complete the past To address missing clean activation data for historical accuracy, we applied a back-casting approach. This method projected the data distribution forward and used the same pattern to simulate the missing data retrospectively. Featured products Marketing Science Consulting. Integrate science into your marketing approach and transition to a data-driven culture. Our multidisciplinary team provides a consultative approach to data science, following industry best practices. Markting Mix Modeling. Design your ideal marketing mix and quantify the incremental impact on ROI and sales from all your marketing activities. This enables you to reallocate your media budget for better results. slice1 Results slice2 In the customer's voice slice3 Next steps A definitive optimization agenda. With Liberty and Bunker DB working side by side, we developed a highly reliable model to create an optimization agenda aimed at improving the efficiency of the marketing budget. The next steps will involve a mix of budget reallocation and incremental studies, turning off channels in specific regions or moments to continue refining the model. Intra-digital reallocation. The first step involves reallocating the budget across online channels (Google, Meta, etc.). Calibration with lift studies. Next, incremental studies like Geo Lift and Conversion Lift will be conducted to adjust and fine-tune the MMM. Reallocation from offline to online. Lastly, investments in TV, radio, and other offline media will be shifted to online channels.

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case-studies

08 | 04 | 2024

How NUC University Increased Enrollment Value with Leads Performance

Context Years of data history. NUC University, Puerto Rico’s leading university with over 40 years of experience, has had Bunker DB as part of its team for more than six years, consistently collecting data from all their marketing actions year after year. From the beginning, we have helped them audit their brand investments, maintain transparency among collaborators, and analyze their strategies. Challenge The Pandemic as a catalyst for change. When the pandemic hit, NUC University’s experience with online course offerings allowed them to adapt quickly and make a seamless, strategic leap into the digital ecosystem. This shift, combined with their position as a major brand in a small country where many people were already enrolled, brought a significant transformation to their strategy. They transitioned from focusing on high enrollment volumes to: Adding value to each new and existing enrollment. Measuring custom metrics, such as click-to-lead and cost per enrollment (CPE). Solution The more you use Bunker, the better. With years of accumulated information, we leveraged this historical data to support NUC’s new full-funnel strategy—and got to work. We created a custom solution that connected to NUC’s database to identify whether leads were new or duplicates. This allowed NUC to develop personalized programs to determine which campaigns to target, making better use of their efforts and driving greater efficiency. Featured products Thanks to the Consumers module, NUC was able to centralize its leads and manage its database securely to create, segment, and enrich its audience. They could visualize how their conversions and sales were performing through a centralized dashboard. Additionally, with the Lead Performance module, NUC gained visibility into their conversion funnel to identify which channels, campaigns, and content generated the most leads and sales, while distinguishing between new and duplicate prospects. slice1 Results slice2 In the customer's voice slice3 Next steps The next goal for NUC will be to bring the offline and online worlds together to create a strategy focused 100% on the consumer journey.