The consumer goods and retail landscape is evolving rapidly, driven by new and emerging technology like AI, machine learning, and VR.  Customers today expect not just convenience, but seamless, engaging digital experiences that rival the best in the tech industry. Launching an app is no longer enough. To build brand loyalty and increase customer engagement, companies need to craft an unforgettable digital journey and release products that hit the mark with consumers—or risk losing them to another brand.

Yet, in today’s hypercompetitive market, the research firm IRI reports that 90% of the nearly 10,000 new retail products released each year fail to meet their sales goals. Read on to explore how consumer goods companies can ride the wave of transformation by strategically embracing emerging technologies like AI, mixed reality, and advanced robotics to win consumers’ loyalty and increase revenue.

Why New Technology Is Increasing Consumer Expectations

The more data CGCs collect, the more customers expect. Today, AI is being used to create highly personalized customer experiences to guide each shopper through a buyer’s journey that feels unique based on their interests and behaviors. From creating in-depth customer segments and retargeting ad campaigns to customizing dynamic content in real-time based on an individual’s engagement, the technology we have access to is raising consumer expectations and changing the game for everyone.

The good news? AI can help CGCs reach unparalleled heights and generate more revenue by providing sophisticated and accurate forecasting, enabling hyper-personalization down to each individual customer, and offering predictive customer service models. According to Forbes Advisor, over 60% of business owners believe AI will improve customer relationships.

By weaving software into the fabric of their operations, from customer touchpoints to internal processes, companies can elevate their offerings, meet heightened expectations, and stand out in a competitive market.

How CGCs Can Leverage AI, Machine Learning, and New Technologies

AI and machine learning can provide a substantial boost to revenue through predictive analytics, automation, and personalization, but it’s important to understand where these tools are best utilized and how to implement them.

Forbes Advisor shares that 64% of business owners claim AI will enhance business productivity, and 43% believe it will streamline job processes. So, what tasks should leaders delegate to AI to create more effective workplaces? Here are a few key areas you can implement this new technology to give your organization a boost and achieve sustainable growth:

1. Repetitive Tasks and Workflows

Thanks to their iterative learning capabilities, machine learning and AI tools are excellent at automating mundane tasks and routine workflows. According to McKinsey & Company, 66% of businesses are taking steps to automate processes.

This can save your team valuable time and free up their ability to focus on more important strategic initiatives, like developing a robust rewards program to increase brand loyalty. McKinsey & Company predicts that generative AI alone could lead to “productivity growth of 0.1 to 0.6 percent annually through 2040” depending on how worker time is reallocated.  Instead of replacing your team members with AI, consider how else they might work alongside it and where they could spend the increased time they have available.

For example, online retailers might choose to implement AI chatbots to provide 24/7 support to customers who have simple questions. By analyzing previous customer interactions and company data, these AI chatbots can provide accurate information to help most customers overcome their issues swiftly. It also reduces the number of calls and messages customer support representatives receive, freeing up more of their time to work with challenging customers or develop a positive customer outreach program that nurtures relationships and create a better overall experience. By using AI in this way, CGCs can become more proactive to their customers’ needs versus reactive.  

Related: The Defensive Consumer Mindset: Prioritizing Health and Sustainability

2. Data Analysis

CGCs with vast amounts of historical data and customer touchpoints can extract meaningful insights from the information they already have on hand using AI to identify patterns. Surprisingly, Forbes reports that only 40% of companies are using AI for data aggregation in 2023, which means there’s still plenty of time for companies to adopt this strategy to get ahead of their competition.  Sales and marketing data can be a gold mine when paired with the right AI software, uncovering customer preferences, consumer trends, and new market opportunities. CGC leaders can also use these tools to optimize their pricing strategies, identify challenges, and optimize processes.

For example, AI might be used at the customer service level to decrease churn rates by flagging consumers who have reduced how often they make purchases, expressed their dissatisfaction with a certain product, or decreased their engagement with a brand. By analyzing past consumer behaviors, AI can quickly determine when a current customer is at risk.

At this point, the AI program might notify customer service to reach out to the flagged customer manually, but it could also take things a step further. Depending on the situation, the AI could trigger an automated email sequence designed to re-engage the consumer. Imagine if you knew one of your customers was considering switching brands and you could send a coupon code to their inbox in real-time. With predictive analytics and advanced automations, it’s possible to identify these behavior patterns and act swiftly to increase customer retention.

Related: Navigating the De-Influencing Movement: Ensuring Brand Relevance Amidst Changing Consumer Dynamics

3. Forecasting Trends

Predictive analytics map out the most likely future trends based on historical data, like past purchases and browsing behavior. While AI might seem like a flashy new tool, an impressive 95% of businesses are already incorporating predictive analytics software into their marketing initiatives because it gives them such clear insight into how their customers will behave. By examining shopping behaviors and data patterns, AI can help CGCs identify shifts in consumer preferences, purchasing habits, and even potential churn well before these changes take place. This gives CGC executives and leaders more time to adjust their marketing, sales, customer support, and product development strategies to better suit their customers’ needs.

For example, CGC companies might use predictive analytics to analyze historical sales data from previous holiday seasons to identify how many units they typically sell, what types of products are the most popular, and how much of an increase in transactions they usually see. Then they could use AI to cross-reference this data with economic and social trends to determine how many units they should order, which products they should promote, and how many employees they should staff to work the busy holiday season this year. By using predictive analytics in this way, CGCs can save money, reduce waste, and improve the overall customer experience.

3 Examples of CGCs Applying AI, Machine Learning, and New Technologies

From marketing and sales to product development and customer service, the applications for AI in the CGC space are endless. Here are three case studies that highlight how successful CGCs are incorporating AI, machine learning, and new technologies to increase customer satisfaction, build brand loyalty, and generate more revenue.

1. Nestlé Uses AI To Launch New Products

Alongside several other industry-leading CGCs, Nestlé has adapted the Tastewise platform to compile robust market research reports and determine which new product concepts have the best chance of becoming fan favorites. Earlier in 2023, Tastewise launched TasteGPT, an AI-backed platform designed specifically for the food and beverage industry. This generative AI tool draws on Tastewise’s impressive data sets to provide CGC leaders with real-time product and marketing recommendations based on consumer trends and insights. An article from Food Industry Executive explains just how much of a gamechanger this is:

“In a nation where social media trends can immediately cause nationwide retail shortages of ingredients from feta to fresh corn, and one of every eight menu items is new in the last month, consumption is changing faster than ever. Food and beverage companies responsible for what the world eats and drinks are in a race to keep up, and traditional consumer research methods provide outdated insights.

Traditional market research methods (i.e. surveys, focus groups, syndicated industry reports) for product innovation, renovation, and marketing typically report data approximately 13 months late and miss significant behavioral shifts, making them unreliable in the current fast-moving consumer world. The result? Products that don’t resonate with consumer needs, high product failure rates, and monumental waste.”

With TasteGPT, CGCs like Nestlé can gather real-time insights, allowing them to cash in on current trends by making smarter decisions about the products they produce and how they market them.

2. Mars Mitigates Risks with Predictive AI

The manufacturing powerhouse Mars is using AI in a unique way to mitigate risks in the pet food industry and keep your furry family members safe. A spokesperson from the company explains that today “AI is already helping us predict whether cats and dogs could develop chronic kidney disease; speeding up the sequencing of pet genomes to provide individualized nutrition and care; and unlocking efficiencies in our manufacturing operations through digital twin technology.”

The use of AI in this way is helping Mars develop new, research-backed products that are safe for pets to enjoy—and they’re doing it at an unprecedented speed. By partnering with the AI company PIPA, Mars can synthesize large quantities of consumer data and cross-reference this with health information to create unique formulas for new, differentiated products.

Through the Mars Advanced Research Institute (MARI), PIPA and Mars are focused on releasing new, functional products by “deriving connections between molecular and food-related entities with microbes and diseases,” explains Informa. And there’s more where that came from.

Informa goes on to highlight several other CGCs using AI for similar purposes. “IBM is working to develop a platform called Hypertaste that can improve taste. Firmenich has partnered with Microsoft to use AI to optimize flavor combinations for plant-based meat. Conagra has leveraged AI to help pinpoint consumer preferences and quickly release products that are on-trend.”

3. Coca-Cola Develops a Creative AI Community

As one of the first partners to link up with OpenAI, Coca-Cola continues to invest heavily in generative AI, machine learning, and emerging technologies. One of the ways Coca-Cola is leveraging AI is by injecting it into its marketing materials, most notably throughout the ‘Real Magic’ campaign.

In a commercial titled ‘Masterpiece,’ Coca-Cola weaves AI together with live-action shots and advanced digital effects to create a truly captivating animation style that grabs viewers’ attention.

You can watch the full video below:

To build off of their ‘Masterpiece’ video, Coca-Cola invited digital artists around the world to ‘Create Real Magic’ using their new AI platform, developed with Bain and OpenAI. This one-of-a-kind platform comes equipped with the ability to generate both text and images automatically from prompts (similar to ChatGPT and DALL-E). Artists are encouraged to use the library of iconic Coca-Cola creative imagery and assets to develop their own marketing collateral, with the opportunity to have their final designs featured on billboards throughout Times Square in New York.

Through this campaign, Coca-Cola is not only using AI to save time and produce memorable marketing materials, but they’re also using it to nurture a community for fans who enjoy their brand and want to express their creativity.

The Future of the Consumer Goods Industry

Generative AI will have a revolutionary impact across all industries, including the retail and CPG space. McKinsey & Company predicts that AI could generate an additional $400 billion to $660 billion a year in value in the CPG space alone if implemented correctly.

As technology continues to evolve, our strategies as business leaders need to continue to evolve with it. AI and machine learning tools will become more sophisticated, and so will the predictions they make about consumer trends, pricing models, and economic implications.

To meet the demands of tomorrow and ensure our organizations are growing at the same pace as the technology we need to be effective, it’s essential for us to continually educate and elevate the teams we work with. Tech-enabled learning can’t happen without the right investments, assets, and processes in place. Remember, digital upskilling is a business and people are a priority. Focus on building a growth mindset culture to set your organization up for long-term success while strategically adopting emerging technologies.


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