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Tech trends in retail and consumer goods

Here are some of the tech trends retail and CPG organizations are investing in or exploring.

As we approach mid-year 2024, demand for tech in retail and consumer packaged goods (CPG) remains elevated and shows no sign of abatement. Driven partially by GenAI investments, but also buoyed by important events like Chrome’s third-party cookie deprecation, heightened demand is likely to persist as the year progresses.

Paradoxically, this uptick in demand traces its roots to early last year when the industry-wide tech slowdown gathered pace. This trend also persists despite continued softness across many areas of tech—in the first weeks of 2024, for example, nearly 25,000 tech workers were laid off.

Background aside, here’s a list of the top tech trends I am tracking across the industry. While not an exhaustive list, these are the main areas retail/CPG organizations are investing in or exploring.


Third-party cookie deprecation and data privacy laws are making it more difficult for CPGs—especially those building DTC strategies—to gather intelligence and market to customers with personalized content. In this environment, ownership of customer data is paramount—especially as third-party data sources disappear.

Given this paradigm, many retailers and CPGs are investing in customer data management and collaboration solutions to understand customers and better manage marketing addressability, distribution, and merchandising.

Key trends include:

  • Customer Data Platforms (CDP) are hot again. These tools seek to provide a single source for data centralization, identity resolution, audience building, and activation.

  • “Native Composable” Data Warehouses (versus packaged) CDPs are emerging as a top solution for large CPG companies that have historically stored customer data in many locations.

  • Identity Resolution (IDR) is needed whether it lives in a CDP or separately in a customer data warehouse instance with a third-party IDR provider, to tie together offline first-party and third-party data sources, not to mention activating the data across engagement channels.

  • Digital Data Tracking is being used by DTC brands to serve as a behavioral source of data critical to segmentation and audience building.

  • Data Clean Rooms are being adopted for data collaboration to act as a tool to enrich CPG customer profiles when first-party data is limited. Data clean rooms offer a secure environment to bring data together for joint analysis without revealing underlying PII or user IDs with collaborators.


Faced with budgetary constraints, many retail and CPG companies are currently experimenting with GenAI-powered content automation (with human oversight) to automate and supplement content generation, with early signs of success. Citing efficiency, productivity, and automation, brand managers are assessing how AI can automate time-consuming tasks, augment specialized skills, and funnel data to internal teams more quickly.

Some key considerations include:

  • Accuracy And Protection: Many brands are testing solutions that offer prompt engineering for brand, style, tone, and template control, operating with a retrieval augmented generation (RAG) model to reduce hallucinations. To limit liability, plagiarism, and SEO, checkers are being built into popular GenAI content production solutions. Some vendors are even offering indemnification for copyright infringement.

  • Integration And Scalability: Content production GenAI tools can save time at almost any scale, but API integrations with current content and creation tools allow for greater scalability across use cases (think automating thousands of landing page product descriptions from one SKU). Scalability leads to better personalization and localization.

  • Interoperability: Content generation GenAI tools are generally stronger if they are interoperable across different systems. This allows them to leverage the data needed to produce content in multiple use cases, addressing various business use cases.

  • Watermarking And Copyright: Content creators should be aware that GenAI-produced content must contain a digital watermark. Further, while ensuring content does not violate existing copyright laws, brands must also consider content created using GenAI may not be copyrighted—a double whammy.


Given slow growth coupled with signal loss from cookie deprecation depressing RoAS, many brands are focusing on tactics to drive top-line sales numbers and reach customers in relevant contexts. New platforms are emerging online that allow brands to merchandise in contextually relevant ways.

Following years of hype and lackluster results, social commerce is finally taking off in 2024. Social commerce refers to creating an end-to-end shopping experience—from product discovery and research to checkout—that takes place directly on social media channels. 

Some interesting stats for TikTok: 68% of GenZ and 76% of millennial CPG audiences try new products or brands more often after joining the platform, according to a study by Captiv8. Similarly for Meta, 36% of 18 to 34 year olds in the US say they engage with food-related posts on Facebook every week, reports Social Media Today.

Having built perhaps the world’s most expansive logistics and fulfillment network, the e-commerce behemoth Amazon has quietly been pivoting to power e-commerce for partner organizations with its Amazon Multichannel Fulfillment (MCF) service, which many refer to as “Powered-by-Amazon.”

Partnering with Amazon, TikTok Shop officially launched in the United States in September 2023 to offer consumers a connection with Amazon MCF for seamless shopping within a contained experience. Last Fall, Meta and Amazon announced a partnership to enable an in-app shopping feature on Facebook and Instagram. Upon linking their Meta accounts with Amazon, users can now shop selected ads and checkout using their Amazon accounts without having to change or toggle between apps.


Multi-touch attribution, or MTA, is a marketing effectiveness measurement technique that considers all marketing touchpoints across the consumer journey and assigns fractional credit to each channel. This allows marketers to understand the impact of each on the marketing program. MTA offers the promise of measurement, ROI analysis, and spend optimization. Historically, MTA has been challenging for organizations to implement.

As cookies disappear and MTA becomes more challenging, MMM, or Marketing Mix Modeling, is having a moment and interest is way up across the industry. MMM consists of collecting aggregated data (rather than customer-level data) from various sources. The goal is to determine the impact of marketing and non-marketing activities. MMM relies on regression and other econometric methods to develop a model based on historical sales movements. 

Many CPG brands are experimenting with tactics to get closer to their customers as they deal with the corrosive impacts of signal loss as third-party cookies disappear and privacy laws begin to bite. It’s a time of change and transition, bringing both challenge and opportunity.


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