For the past few years, retail companies have been leveraging machine learning models to improve supply chain efficiency and manage inventory. More recently, they’ve been exploring generative AI to make chatbots more conversational and create content. But what about market research?
How can brands use AI to understand their buyers’ desires?
Advances in AI and data analytics, as well as platforms like Walmart Luminate, as recognized CPGs at CES 2024open up new possibilities and potential in market research. For example, brands can now uncover insights into shopper behaviors, such as how certain groups use the buy online, pick up in store system (BOPIS).
CPGs can also uncover brand-switching behaviors across their portfolios, identify effective pricing and promotions, and personalize product assortments based on store location. CPGs have a wealth of shopper data at their disposal. Now they can quickly leverage that data: AI-driven insights can tell what consumers want today and what they’ll buy tomorrow, next week, and next quarter.
Better consumer data paves the way for AI
AI is only as effective as the data that powers it. CPG has access to robust sources of consumer insights. Brands have their own consumer data, but they also have access to third-party panels, macroeconomic reports, and social listening insights. Add to that retailer purchase data and loyalty insights, and CPG can use AI to deliver highly strategic insights into consumer behavior.
It wasn’t always this way, but retailer platforms have been a catalyst for change. Brands can gain insights into millions of households. They can also mine data and feed it into AI to make immediate strategic recommendations.
Brands can study retailer dashboards and scour spreadsheets of their own data, but AI can speed up the process by examining the information and suggesting action items to increase sales or move volume.
What CPGs Can Learn from AI
Using AI to read prolific amounts of shopper data can enable brands to learn more about omnichannel shopping behaviors, innovate with new products, predict product demand, and optimize pricing, packaging, and promotions. It’s up to brand teams to chart the course forward.
Here are some ways brands can leverage AI and buyer research:
1. Advanced customer segmentation
AI analyzes vast amounts of buyer data to create detailed customer segments based on behaviors, preferences, and demographics. Segments help brands tailor their marketing strategies and new products to specific groups.
2. Predictive analysis
For consumer market research, brands can predict future purchasing behaviors to help manage inventory, manage supply chains, and optimize product assortments to meet future demands.
3. Personalized shopping experiences
Analyzing individual buyer data provides personalized recommendations, offers and promotions for each buyer, improving customer loyalty.
4. Sentiment Analysis
By studying social media activity, reviews, and other online content, brands are using AI to uncover consumer sentiment in markets. What do they think about products and brands? AI can analyze feedback from various channels—surveys, social media, call centers—to extract actionable insights.
5. Churn Rate Prediction
Brands can study shoppers with AI by identifying patterns that indicate potential customer churn, thereby triggering customer retention strategies.
6. Customer journey mapping
AI can track and analyze the entire buying journey, from awareness to purchase. This provides insights into the touchpoints that influence purchasing decisions, helping brands optimize their marketing and sales strategies.
AI improves buyer data
For decades, brand managers and analysts have toiled in spreadsheets, doing their best to predict product performance. Now, thanks to AI, that work can be reduced to minutes. CPGs that leverage AI-powered forecasting not only improve their product performance, but also become key collaborators among their retail partners.
AI is taking data analytics to new heights. This predictive technology understands shopper behavior and how it impacts a consumer product’s goals. AI can predict what shoppers will put in their cart tomorrow and beyond, and it can predict how that behavior will impact sales, revenue, and more.
