In today's competitive eCommerce landscape, optimizing profits has become a significant challenge for many brands. By employing Media Mix Modeling (MMM), businesses can effectively enhance their gross profits across different markets. Let's explore the steps to do this efficiently:
The end of the year is often considered as the most significant period for eCommerce brands. A fact evidenced by the staggering statistic that eCommerce Holiday spending exceeded $889M in 2021 in the US alone. Moreover, there is a continous growth forecasted for the following years which will manifest in 2023 as well. Such an impressive figure prompts the question: How can brands tap into this immense potential, and more importantly, do so profitably?
Welcome to Part 2 of our series on end of year marketing strategy optimization. By blending analytics with strategy, Media Mix Modeling (MMM) offers a comprehensive lens to dissect, understand, and enhance marketing endeavors. As the festive season beckons and the stakes rise, let's delve into how MMM can be the beacon guiding brands through the intricate maze of end-of-year campaign planning, ensuring that every move is calibrated for maximum impact.
TikTok has emerged as a powerhouse, captivating millions with its scroll-friendly design and bite-sized content. However, with its unique user engagement patterns, measuring the success of advertising campaigns on this platform isn't as straightforward as end-of-the-funnel digital mediums. Brands, especially those in the eCommerce and DTC sectors, find themselves grappling with traditional metrics that might not paint the full picture. In this blog post, we'll delve deep into the challenges of measuring TikTok ads and explore how Media Mix Modeling (MMM) can offer a more holistic and accurate approach to understanding your advertising impact.
In the current digital era, where data forms the backbone of successful marketing strategies, the provenance and quality of this data have taken center stage. Every decision, from content creation to ad spend, is often dictated by the insights garnered from these data sources. Among the multitude of platforms available, Shopify and Google Analytics (GA) emerge as frontrunners for companies looking to harness the power of data to optimize their digital marketing.
In the current digital era, where data forms the backbone of successful marketing strategies, the provenance and quality of this data have taken center stage. Every decision, from content creation to ad spend, is often dictated by the insights garnered from these data sources. Among the multitude of platforms available, Shopify and Google Analytics (GA) emerge as frontrunners for companies looking to harness the power of data to optimize their digital marketing.
Welcome to the fourth part of our series on eCommerce KPIs. As we delve deeper, our lens sharpens on crucial metrics that underpin every successful eCommerce venture's decision-making: Customer Acquisition Cost (CAC) and Customer Lifetime Value (LTV). In this part, we’ll deep dive into these essential metrics in order to show how they and MMM guide the trajectory of eCommerce brands aiming for sustained growth and profitability.
The rapidly changing digital commerce landscape demands a robust marketing strategy for businesses aiming for success. One of the main driving forces behind an effective strategy is understanding and utilizing your Key Performance Indicators (KPIs). But there's more to KPIs than just recognizing their definitions
For decades, Media Mix Modeling (MMM) has been seen as a luxury for large enterprise companies, focusing on measuring the effectiveness of media investments in relation to sales. While this approach and its associated KPIs might suit the corporate landscape, it often proves too abstract and slow-moving for the dynamic world of eCommerce.
In the world of marketing, understanding how different variables influence consumer behavior is key to designing effective advertising campaigns. One of the crucial concepts in this domain is the Advertising Response Curve (ARC), a function in marketing mix modeling that describes the relationship between advertising spend and the resulting consumer response. This article will delve into the intricacies of ARCs, detailing their function, significance, and how they intersect with critical elements such as saturation points. We will also investigate the impact ARCs have on Media Mix Optimization, specifically, the Return on Investment (ROI) , and shed light on the various industry-standard types of curves. Lastly, we will deep dive into the process of building an ARC.