Advertising technology (ad tech platforms) help digital marketing leaders plan, buy and manage digital advertising campaigns across channels including but not limited to: display, video, streaming TV and audio, mobile, social and search. They provide functions for campaign planning, media buying, advertising analysis and optimization and automation. Ad tech platforms can be used by buy-side and sell-side agents; this definition focuses exclusively on the buy side.
Marketing analytics skills are among the most important capabilities in the marketing organization, yet it remains difficult to recruit, hire and retain people with strong skills to support in-house teams. Most marketing teams still struggle with a skills gap in this domain. As a result, marketers seek to augment internal teams by using advanced analytics service providers that offer third-party expert resources, proprietary methodologies and models, and even managed technology to help marketers tackle some of their toughest challenges. Vendors in this market specialize in advanced analytics, including sophisticated methods such as mapping the customer journey, attributing marketing spend to measured outcomes, simulating and measuring business impact of marketing and advertising campaigns, and implementing predictive models. Engagements may be project-based or part of an ongoing partnership, and may include the use of proprietary technology.
Retail assortment management applications (RAMAs) are a foundational component of modern category management solutions for long life cycle products. Using data & analytics and AI technology, RAMAs can curate targeted assortments to create compelling customer experiences, leading to an increase in sales conversion. Long life cycle products in retail include categories such as grocery, consumables and hard goods. The long life cycle retailers’ traditionally broad approach to assortments is not satisfying customers’ demands for more curated assortments to match their lifestyles. Local trends mean that even more granular store-specific assortments are necessary. Advanced analytics, algorithms, AI and automation will play pivotal roles in driving this transformation through better customer understanding and alignment.