Proliferation of Seamless, Personalized Commerce Experiences
With the advancements in generative AI production capabilities, we
are going to finally see a blurring of lines when it comes to previous limitations to shopping anywhere and everywhere commerce is possible, with the added benefit of highly-customized experiences
that negate the need for traditional DTC/brand.com mechanisms.
The ability to build unique and self-contained media placements that integrate seamlessly with personalized messaging, creative, and payment
infrastructure will become as ubiquitous as the products slipping into our feeds, our social platforms, our commutes, and our podcasts. It is already becoming more approachable and affordable to
build, maintain, and deploy flexible libraries for everything from DCO to brand experiences.
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As audience data becomes more integrated across the entire ecosystem, generative AI threads its way into
each tech stage. This enables us to cater to specific individuals with precision, such as those who have a penchant for granola bars and travel with a camera kit on vacation. We can now offer them the
ideal travel bag, coupled with a seamless payment experience, all within the confines of their social feed, ensuring a frictionless shopping experience without ever leaving the
platform.
While the road is open for tighter cohesion here, privacy laws around data-sharing could prevent overly integrated use cases, particularly where
large tech companies have faced recent regulation, like location tracking practices and preventative data leak fines, but also the concerns around quality assurance checks and legal compliance for
production built off generative AI models.
Optimizing Operations, Productivity & Activation
The coming forecast for ecommerce in 2024 may well prove that the industry is
starting to peak post-pandemic years – while share of online grocery shopping is still edging up at 9% growth from last year, total ecommerce has steadied at around 15% share of late. If
the share of activity continues to stabilize, the next great commerce initiative will be to iteratively optimize for improved operations and productivity, and we are keeping a close eye on the tech
and tools that will help our clients accomplish this.
Three key initiatives we believe will play out in significant ways next year:
Tighter control and management of commerce fulfillment: Amazon is leading the charge here but expect a plethora of
advancements in AI guidance systems and upgraded robotics for warehouse operations and retail floor management to further advance speed and safety — this could lead to order fulfillment
improvements by 25% and 75% speedier inventory identification.
Pragmatic generative AI and advanced automation: Working with practical application of
generative AI and smarter rules-based automations in production software will continue to shave off 30%+ resourced time against labor-heavy copywriting, design, filming, and animation. But never leave
home without a human editor.
Refined audience targeting: Media and creative briefs and execution are only as good as the data driving them. Further advancements in audience
data optimization (including data enrichment and reconciliation), tighter clean room partnerships, and iterative profiling with combination data sets will allow marketers to improve who and how they
address customers with messaging and experiences to meet their intentions more fully.
Analyzing Retail Media Performance
In the quickly maturing commerce media space, there is increasing
complexity in analyzing performance across the massive but fragmented reach of channels at play, notably exasperated by competing sources of data truth and ambiguity in measuring results with enough
confidence to make the next best activation and optimization decision.
By unifying the right compatible data sources, products, and platforms to better communicate, the ability to measure some of
the more incompatible datasets (like retailers’ sell out data and media performance data, or bridging marketing and identity data with commerce media campaigns) becomes more substantial, thereby
solving a number of hurdles in analyzing performance to better calibrate, optimize, and drive incremental performance – such as narrowing into incremental return on ad spend and growing revenues
across the right channel mix.
Advancing Use Cases for the Largest Retailer’s Marketing Data
We have been hearing from our clients that there is a need to utilize and
implement Amazon Marketing Cloud (AMC) data to improve how they sell on Amazon.
Amazon Marketing Cloud provides cloud-based analytics that give advertisers a deeper look into their marketing performance
across channels. AMC offers better insight into media spend and strategies, campaign measurement, and audience data.
In 2023, Amazon Ads had the largest retail media network, which captured over 75% of the US
retail media. With 200 million prime members, Brands are looking for ways to harness AMC data to measure and optimize net revenue, organic versus paid growth, and other meaningful performance metrics
for media tactics to grow their business on Amazon.com. We will continue to see innovation in how we bridge both AMC data and vendor sales and media performance data to optimize incremental ROAS,
incremental reach, better understand subscription drivers, and a myriad of other signals around revenue and profitability.