Snipp Blog

2024 AI In Shopper Marketing Technology Landscape

Written by Snipp | Jul 29, 2024 3:22:25 PM

Artificial Intelligence (AI) is making waves across almost every industry and shopper marketing is no exception. Capable of creating personalized shopping lists, optimizing ad creative, and even bringing more relevant products to market at a quickened pace, AI is poised to drive marketing efficiencies, customer experiences, and innovation for brands and retailers looking to stay competitive and relevant with their shoppers in-store and online.  

In a recent study conducted by Deloitte, 40% of grocery executives surveyed think their company will be using AI for a business application in 2024. So, is there a single killer app, or will its impact be broader reaching? AI has its tentacles in almost every aspect of shopper marketing. This year, both the front and back office are represented; for example, 31% of the grocery execs surveyed stated that AI could be used as a customer assistant, while 22% looked to manage supply chain logistics. Of course, there are many other ways that AI can impact shopping.  

To help you keep ahead of the fast pace of innovation, we’ve created the AI Shopper Marketing Technology Landscape. Even though AI is being employed in-house by both brands and retailers, this landscape is designed to help you identify up-and-coming AI innovators in their respective categories. This follows from our Shopper Marketing Technology Landscape released in 2023. 

Artificial Intelligence In Shopper Marketing Technology Landscape 2023

Without further ado, here is the 2024 AI In Shopper Marketing Technology Landscape. Click on the image for a larger version (or here for a PDF Version). See below the graphic for details about each category included in the landscape.

Resources:

AI In Shopper Marketing Technology Categories

Predictive Analytics 

Uses Ai for real-time forecasting  of demand to manage inventory, analyze customer behavior for personalized marketing, and track market and competitor data.

Creative Optimization

Analyzes consumer data to generate and refine ad content. Tests various creative elements ensuring that the most compelling creative is used for each target audience.

Advertising Optimization

AI analyzes consumer data for precise targeting and personalization, to optimize budget allocations across channels, and monitor performance in real-time.

Price Optimization

Uses real-time data for AI-generated dynamic pricing, analyzing promotions, and tailoring market strategies to quickly adapt to market changes.

Promotions Fraud Management

Uses AI to detect fraudulent activities, optimize promotional strategies, and ensure the integrity of discount offers, promotions and loyalty programs.

Product Innovation

Analyzes market trends and consumer preferences, generates and refines product ideas, and forecasts market demand, supporting product innovation to stay competitive and develop personalized products.

Customer Engagement

Analyzes consumer data to create AI-derived personalized interactions, automating customer service with chatbots, and anticipating customer needs.

Customer Support Tools

Automates responses, personalizes interactions, and analyzes feedback, enhancing efficiency, resolving issues quickly, and improving customer satisfaction.

Measurement

AI provides data-driven insights on campaign performance, customer behavior, and ROI, optimizing marketing strategies and improving decision-making.

Retail Merchandising Services

Optimizes inventory, ensures planogram compliance, analyzes sales data, manages promotions, and enhances in-store execution for increased sales and efficiency.

Personalization

Analyzes consumer data to deliver tailored marketing and product recommendations. Optimizes customer interactions by personalizing content, offers, and experiences based on individual preferences.

Dynamic Pricing

Software that automatically adjusts prices in real-time based on market demand, competitor pricing, and other factors to optimize revenue.

Demand Forecasting

Use data analysis and predictive models to estimate future consumer demand, helping businesses optimize inventory, pricing, and supply chain decisions.

Path to Purchase Analysis

Track and analyze consumer behavior across channels, identifying touchpoints and influences to optimize marketing strategies and enhance the buying journey.

Video Personalization

Creates tailored video content enhancing engagement and customer experience by customizing messages and visuals based on individual viewer preferences and behaviors.

Voice of the Customer

Analyzes customer feedback, identifies trends, and provides actionable insights to improve products, enhance customer satisfaction and better meet consumer needs.

Supply Chain Optimization

Streamlines logistics, forecasts demand, manages inventory, and reduces costs, enhancing overall efficiency, responsiveness, and profitability for CPG clients.

Customer Segmentation

Uses data analytics to divide customers into distinct groups based on behaviors, demographics, and preferences, enabling targeted marketing and personalized experiences.

Retail Media Platforms

Enables brands to advertise directly on retailer websites, targeting shoppers with personalized ads based on browsing and purchasing behavior.

Ecommerce + Digital Shelf

Enhances product visibility and sales by optimizing listings, keywords, images, and descriptions across online retail platforms.

Social Commerce + Shoppable Media

Third party technology solutions for retailers to enable brand advertising and promotions on their owned digital media assets. Retail media was once reserved for brick-and-mortar titans like Walmart and Kroger but is now a growing opportunity for regional grocery and drug retailers. Tech providers like Kevel, and CitrusAd have made it easier for these smaller players to monetize their digital assets, allowing their brand partners to market directly to their digitally engaged shoppers.

The First AI In Shopper Marketing Landscape 

We hope you received value from this Shopper Marketing Technology Landscape. Feel free to contact us if you see other categories of AI innovation or if we’re missing key innovators or examples! Feel free to drop us a line with any feedback, additions or changes for us to consider in upcoming versions of the landscape. We’d love to hear from you!