在过去的 18 个多月里，大多数品牌都很难想象还有比这更具破坏性的时期。从向数字化转型到广告削减、供应链挑战、隐私和数据安全需求上升--所有这一切都发生在全球大流行的背景下--广告主的境遇并非一帆风顺。
Given the environment, which remains very much in flux, the focus on efficient marketing and tangible returns on investment (ROI) remain elevated, especially in industries where the ad recovery has been slower than others. With so much at stake, it’s not surprising that many brands have started exploring the prospect of bringing their marketing analytics in-house. In the face of all that’s happening in the world, it’s not an irrational notion. But it needs to be executed in the right way.
Importantly, the world of marketing technology has matured significantly in recent years, offering brands an array of solutions to help with everything from promotion to social media engagement to commerce. According to the Chief Marketing Technologist’s Marketing Technology Landscape report, the landscape was rife with 8,000 different martech solutions last year—up more than 13% from 2019. That’s a lot to navigate—and well before any actual analytic work comes into play.
As vast as the growing sea of available solutions is, marketing mix modeling (MMM) is the most critical solution for advertisers to understand and optimize their marketing dollars holistically. MMM can be leveraged globally, whereas certain data-needy solutions only provide coverage in top markets. Amid a rapidly fragmenting media landscape, in-market MMM expertise is a foundational need for brands looking to ensure that they’re spending their marketing dollars in the most effective channels.
While MMM is invaluable, it requires experience and accuracy to be truly effective. For example, Nielsen’s MMM studies have found that marketers waste between 25% and 50% of their spend because they aren’t able to determine the impact on ROI. In order to narrow that waste, brands need robust and time-tested MMM to successfully determine the qualitative results of each marketing activity.
MMM 的核心是利用统计分析来了解以往营销活动对销售的影响，并预测未来活动的影响。对于营销人员来说，MMM 的考虑因素应包括四个要点：
- 全面了解营销业绩
- 能够影响营销预算的规划和优化
- 可比测量指标
- 着眼未来（隐私考虑、消费者同意等）
MMM--只是一些品牌正在考虑引入内部的一种分析能力--非常复杂。从各种意图和目的来看，创建一个内部分析机构并非易事。技术、人员需求和专业知识要求都很广泛，而且很可能成本很高。要想做好，这些成本是常年的。尽管如此，如果广告商有一个可靠的计划，并与合适的分析提供商合作，还是可以适当地在内部建立分析框架。
每个广告客户需要做的第一件事就是协调他们的数据并制定数据战略。获得准确的数据并制定如何使用数据的战略，是可靠、快速地实现 MMM 效果的基石。可靠的内部数据可减轻 MMM 在隐私和安全方面的压力。得到适当保护的数据可以让广告商放心，因为他们知道数据共享受到控制，隐私得到维护，数据可以以正确的粒度自动提供。
成功的关键之二是定期更新分析结果，使其与每个品牌的决策和业务规划期保持一致。技术发展到今天，通过自动数据交付，可以随时随地更新和交付模型结果。这就省去了组建内部分析团队负责开发和维护技术以及实际运行分析所需的大量工作。这也使广告商能够继续利用专注的分析机构提供的卓越分析和行业领先的解决方案。
Advertisers should also look for an MMM partner that can provide expert consulting when needed, as well as one that provides results and simulation/optimization capabilities in an easy-to-use interface. Partners should also have an understanding of different markets and maintain benchmarks in order to gut check MMM findings. Generating MMM results is part of the battle, but ensuring you’re able to understand and apply the results is another challenge entirely, which is a skill that MMM analytics companies have developed after years of working in the industry. This affords advertisers the flexibility to in-house none, part or all of the actual interpretation and strategic consulting that is required to take advantage of MMM results.
一旦广告客户实现了数据收集自动化，能够访问可定期更新的用户界面，并制定了基于 MMM 结果的战略咨询计划，就能满足所需的内部要求，而无需承担分析维护和建模方面的繁重工作，从而有助于确保营销资金的有效使用。
