Integrating Impact: Learnings from Analytics Unite 2025

Analytics Unite 2025, held April 28–30 in Chicago, brought together more than 200 senior leaders, innovators and data experts from across the consumer goods and retail industries. Over three content-packed days, attendees from iconic brands shared how they’re using advanced analytics to scale innovation, overcome challenges and shape the future of their businesses.

With keynotes, interactive workshops, collaborative discussions, and plenty of opportunities to network and socialize, Analytics Unite served as as a powerful destination to share strategies that are making a real impact.

Here’s a look at the key takeaways from this year’s sessions.

Opening Presentation: The New Retail Imperative

Brendan Witcher, VP and principal analyst at Forrester, kicked off the event with a presentation on preparing for an unstructured, digitized and individualized future. 

He delivered a clear message: The future of digital transformation lies in deeply understanding the individual consumer and not just innovating for innovation’s sake. Witcher emphasized that while retailers and CPGs claim to know their consumers, many still treat them like a Rubik’s Cube, trying out random tactics until something clicks. 

The key problem isn’t a lack of innovation, but a failure to collect and act on reliable, actionable consumer data. Without this foundation, tools like AI to reach their potential. Generalized experiences must give way to personalized ones, he said. 

“We talk about ‘the customer.’ … But we can’t aggregate them; we have to think of them as individuals.” 

Successful brands are those that solve real consumer pain points. For example, Sephora’s strategy turns anonymous shoppers into known users by offering value in exchange for email addresses, transforming interactions into ongoing relationships.

Looking ahead, he stressed that other technologies like computer vision, natural language processing and biometrics are set to overhaul the industry. These tools will enable brands to gather improved insights across both digital and physical environments, the latter of which still accounts for over 70% of U.S. retail sales.

Witcher concluded with three key priorities for 2025: 

• Unify internal teams around consumer understanding

• Use AI to fix pain points before working on delighting consumers 

• Focus on collecting high-quality, actionable data

In essence, businesses need to once again stop making consumers shop and instead make it easy for them to buy.

Workshop: Harnessing Agentic AI: Real-Time, Context-Driven Solutions for Retail & CPG 

The workshop, led by Sangeetha Chandru, SVP of diversified industries group, analytics and AI solutions and services for EXL, explored how agentic AI can drive transformative change by combining data, domain expertise and outcome-driven intelligence to adapt in real time. 

The session began with interactive polls that gauged how participants are currently exploring agentic AI and what barriers or opportunities exist for applying it within their organizations. Attendees then broke into groups for hands-on exercises focused on practical applications in marketing and supply chain — two areas where agentic AI can significantly optimize decision-making and operational efficiency.

Chandru emphasized that while agentic AI has significant transformative potential, it’s important to assess where autonomous agents can realistically integrate into existing workflows. Not all processes are suited for full autonomy, raising concerns about human roles, oversight and ethical considerations.

The workshop provided a platform for sharing ideas, evaluating readiness for adoption and envisioning how agentic AI could shape the future of retail and CPG.

Share Group: Decision Intelligence – Enterprise Decision AI Agents for Growth 

In this share group, attendees grappled with how to best adapt their decision making for today’s marketplace uncertainty.

The Cloverpop team — led by Lanny Roytburg, co-founder and chief commercial officer; Eugene Roytburg, co-founder and CEO; and Lana Klein, chief operating officer — ushered attendees through an interactive presentation that provided an education on decision intelligence and explored how the use of data within enterprise decision-making is evolving.

Attendees then broke into groups to share off-the-record insights and reflect on the experiences within their own organizations. 

Among the determinations of the group was a need to establish a common language between cross-functional groups. Business-oriented teams communicate impact through different approaches than technology teams, and bridging the two languages is essential.

Also, organizations have strategic leadership for a reason, and these leaders have (ideally) developed strategic acumen over their careers. Although their determinations should be predicated on data from the rank-and-file, these leaders remain the best positioned to make game-changing decisions.

Share Group: AI Impact Model – A Leader’s Guide to Driving Impact from AI Investments

This share group focused on a science-based approach to measuring and predicting the business impact of AI using the AI Impact Model developed by C5i. Attendees learned how organizations can use the model to assess and guide AI initiatives before launching them.

Ashwin Mittal, executive chairman for C5i, emphasized that AI success depends on more than just technology — it requires strong data governance, cultural readiness and effective change management. 

He introduced a formula for success: Business Impact = Problem × Data + Tech × Talent ^ Execution, with each variable broken down into specific attributes like data quality, talent-business alignment and execution support.

Mohanbir Sawhney, professor at Northwestern University, stressed that clearly defining the problem and scope is crucial. While data quality is essential, trying to perfect it can lead to diminishing returns. Cultural factors like leadership, analytics maturity and change readiness are just as important as tech and data.

During the closed-door session, participants used the model within a simulated use case to explore how to align scattered AI goals, measure ROI and plan investment timing to assess expected outcomes.

Keynote: Ahold Delhaize’s Karin Chu Talks Moving From AI Possibility To Impact

At Ahold Delhaize USA, artificial intelligence is helping to optimize inventory management, elevating consumer experiences through increased accuracy in e-commerce and buy-online, pickup-in-store transactions. 

During the keynote presentation, Karin Chu, VP of AI and data science for the company, said that investing millions of dollars to run promotions to bring more consumers in may be worthwhile, but not if the store runs out of stock. By using AI, Ahold has enabled new warehouse efficiencies, ensuring that products are delivered at the right time and shelves stay full.  

Its success has been driven by an in-house platform that drives AI insights through two families of algorithms: hourly item-level forecasts by store and hourly order-level data by store. It’s an effort that has required cross-functional collaboration with the consumer experience at the core.

“Transformational solutions are never built in silos,” said Chu.

Read the extended coverage here.

How to Drive Sustainable, Enterprise-Wide AI Impact 

ROI is the big goal — and the big question — when weighing investments in data and AI. Technologies can feature all of the proverbial bells and whistles, but business value is the ultimate driver, panelists at Analytics Unite agreed.

In one session on “ROI of Data and AI: Turning Investments Into Business Value,” speakers representing the retail and CPG sectors shared how formal processes help gauge true impact. 

“There are more algorithms and more open sourcing that make it easier to harvest the value and power of data. But, ultimately, what I think really matters most is to stay true to the core vision of the company,” said Harish Rao, VP, global data and analytics, at Costco Wholesale Corp.

Rao shared that Costco has a relatively formal structure to measure the value of data, including a top-line perspective that assesses demand, forecasting and price, as well as a bottom-line perspective related to efficiencies, labor savings and time. The warehouse operator also collects feedback from members to evaluate its data-driven decisions.

The human role is, of course, important when integrating capabilities. “AI is obviously learning fast, but it’s still in its teenage years. As humans, we are the core drivers for AI to be successful, and we are the ones who are going to make sure the algorithms are trained well,” pointed out Anand Shenoy, chief data officer at Mars Snacking.

As tech advances, establishing trust is pivotal. “Whatever mechanism it is, data has to be certified,” said Rao, noting that Costco also conducts rigorous testing and validation processes. Additionally, companies should sharpen their ongoing communications around the business value of AI and data, the panelists told moderator Mrunali Majmudar, chief practice officer at Fractal Analytics. 

Stakeholders can focus on both long-term success and short-term wins as they measure AI and data effectiveness. 

“You can look at it almost like a physician’s thought process: ‘What problems are we trying to solve, and am I fixing something as a preventative or a treatment?’” Shenoy said. “Obviously, there has to be a balance of both. You can't just do tactical work without thinking about the long-term lens.”

Elevating Value Creation in CPG Through Consumer and Customer Data Analytics Strategies

Bhaumik Sharma, North America CDTO at Haleon, shared how the company is using data to tackle a key business challenge: Of 1.4 billion Haleon consumers worldwide, 59% have only used one brand in the past year. As a result, Haleon focused on transforming its data infrastructure and decision-making processes to improve cross-brand engagement.

A major hurdle, Sharma noted, was data quality — a common issue in organizations with complex histories of mergers and acquisitions. 

“How do you bring in different data sources so that it's in one place, unstructured and available for the right decisions and insights for the people who are really in charge?” asked Sharma. 

Haleon consolidated various data sources — including POS and inventory data, ERP systems, influencer engagement and market research — to create data hubs focused on a single area, such as customer, consumer and marketing.

Sharma highlighted a joint initiative with a retailer that involved sharing comprehensive data across functions, with Haleon providing supply chain forecasts and demand plans, while the retailer contributed transactional, inventory, shopper behavior and advertising insights. The companies then worked off a shared KPI dashboard that could support operations, supply chain, e-commerce and marketing processes.

This collaboration led to measurable improvements: Haleon moved from being the retailer’s No. 4 supplier in 2022 to No. 2, and the company reduced its promotional inefficiencies.

“It has also helped us in our supply chain,” said Sharma. “From procurement of raw materials to packaging … we are able to plan it better because we know months in advance what the customer is looking for.”

Scaling an AI Program for Maximum Business Impact

Kraft Heinz’s head of decision intelligence, Pat Nestor, shared how the CPG giant is evolving its AI strategy by treating AI initiatives like product development, with clear life cycles, value targets and governance. “[It’s] an ingredient that enhances a broader business application or use case,” rather than a means to an end, Nestor said during the session presented by Snowflake. 

When it comes to Kraft Heinz’s portfolio priorities and product development, the company shifted from a relatively unbalanced innovation "tunnel" to a flexible "funnel" that encourages high-volume ideation and faster experimentation, ensuring only the most viable concepts scale.

A success story was the launch of "KHAI," Kraft Heinz’s enterprise-wide generative AI tool and internal assistant designed to prevent “chatbot chaos.” Nestor explained that the platform offers a single, intuitive entry point for Gen AI, streamlining internal adoption and improving employee productivity.

The session also highlighted Kraft Heinz’s AI-driven digital twin ecosystem in manufacturing — optimizing plant-level throughput, yield and waste — and the use of computer vision for real-time supply chain management and quality control. 

Critical to this success is a rigorous governance structure that includes a cross-functional AI Data and Ethics Council, business-aligned KPIs and ongoing upskilling initiatives, Nestor said. He also emphasized the importance of starting small and delivering early wins to gain executive support and reinvestment momentum.

Retail Data, Recalibrated: Getting Closer to the Truth on Shelf

In an era of skyrocketing data consumption and intensifying execution challenges, Trax and Haleon teamed up to tackle one of retail’s most persistent problems: out-of-stocks. Trax’s Matt Greene, VP of enterprise sales and account management, outlined how decades of disruption — from e-commerce to COVID-19 — have exposed systemic issues in retail execution, including poor display compliance, mispriced promotions and inaccurate on-shelf availability (OSA). Notably, Greene cited that roughly 30% of the time, products aren’t available when shoppers expect them to be.

The session highlighted a partnership aimed at identifying and fixing root causes of OSA failures and challenges. The program combined crowdsourced in-store data with real-time image recognition and flexible merchandising services. Haleon selected five high-priority SKUs (e.g., Advil), monitored across thousands of store visits. The findings confirmed widespread OSA issues and enabled targeted interactions in the stores, creating data points for Haleon. 

Becky Church, shopper and category insights manager at Haleon, shared results from the test, noting that nearly all store visits showed at least one of the core SKUs were out of stock, and that conditions like “phantom inventory” and locked cases were limiting product access. She said the pilot program drove measurable improvements in inventory accuracy, category share and out-of-stock rates. Church emphasized that persistence and data transparency — especially with supply chain partners — were key to unlocking results and retailer alignment.

How Schnucks Is Optimizing Data for Real-Team Reactions and Proactive Planning

As many retailers and CPGs can attest, there’s no shortage of data in today’s operating environment. The sheer volume of information can actually cloud what needs to be done to lift sales, boost loyalty and gain efficiencies.

According to a trio of panelists, retailers and brands can tap into data-driven market transparency to react in real time. 

“Things are being won at the local level,” pointed out Brad La Rock, SVP of marketing at Datasembly.

Taylor Espinosa, Datasembly’s director of products, said that bringing structure and organization to data through hierarchical analytics platforms can help stakeholders achieve that goal. 

“This helps you separate out the signal from the noise and figure out exactly what’s happening in your category and competitive categories as well,” she explained.

Scott Kaverman, senior director, strategic pricing at Schnuck Markets, shared how such capabilities are transforming decision making. 

“The data has allowed us to be hyper-local and react in real time,” said Kaverman. “Today, we take in over hundreds of millions of records on a weekly basis that help us delve into creating some of that strategy and driving it to provide competitive offerings to the customer.”

Insights gleaned across the regional grocer’s tech deployments have helped Schnucks get ahead of trends in store brands, track commodity pricing, optimize ad spends with CPG partners and curate pricing campaigns. 

“Having this level of data transparency helps us look at different pockets of where we can invest deeply to drive that incremental shop, grab larger portions of the basket and also level back a bit and make sure we understand price elasticity of demand and response,” Kaverman said.

Leading Data-Driven Transformations: Empowering Organizations for Strategic Decision-Making 

A panel of experts discussed the significance of aligning data-driven initiatives with business goals to navigate AI/data complexities. Andy Walter, a strategic advisor and retired executive from Procter & Gamble, highlighted the necessity of bridging the communication gap within organizations to ensure that senior leadership understands technological advancements, likening the current AI-driven transformation to previous revolutionary changes in technology.

Loretta Franks, VP, chief data and analytics officer, discussed Kellanova’s strategic evolution following its separation from The Kellogg Company, underscoring the importance of a unified organizational purpose to foster resilience amid change. She advocated for prioritizing foundational work while balancing the speed of delivering value to ensure sustainable growth.

Priya McCarthy, CIO of Ferrara, shared the challenges faced by the confectionary company as it aims to establish itself and grow in a competitive market, underscoring the need for clear data foundations. She emphasized the value of asking the right questions and advocating for a dual-focus strategy that considers foundational systems while exploring innovative technologies, as well as getting senior leadership on board.

Eric-Francis Chen, chief digital information officer, North America personal care and SVP of North America digital and technology at Unilever, echoed the importance of educating senior leadership and getting them to “fall in love with AI.” He also elaborated on the need for collaboration with partners and retailers, emphasizing that successful data strategies involve listening to and addressing the goals of stakeholders.

The panel concluded with reflections on their careers, where they shared lessons learned, including the importance of taking risks and fostering a culture of inquiry. They collectively highlighted the significance of intellectual curiosity and adaptability.

Hershey, Kellanova, Diageo & Giant Eagle Execs Strategize on How to Prove AI Value

Striking a balance with artificial intelligence continues to pose challenges for consumer goods and retail leaders. While the technology offers transformative potential, the execution roadmap is anything but linear, and proving its value is harder than ever. 

Leaders from the Hershey Co., Diageo, Kellanova and Giant Eagle recently took on the topic at CGT’s Analytics Unite event, held in Chicago. 

Among the biggest questions asked include: How can I extract value from AI? Should it begin with a canned solution that provides broad functionality, or should it start with a specific use case?

Read the extended coverage here.

Data Leadership Awards Ceremony

The 2025 Data Leadership Award winners were honored in person during a dedicated ceremony. This celebration, sponsored by Mastercard, brought together industry leaders, peers and partners to recognize the exceptional achievements of data-driven innovators across the consumer goods and retail landscape.

The ceremony offered a moment to spotlight each winner’s contributions and impact, as well as to celebrate the power of data in transforming the way businesses operate and connect with consumers. The morning was filled with meaningful conversations of shared successes and well-deserved recognition.

Stay tuned to ConsumerGoods.com to learn more about each award winner. 

Retail & Consumer Goods Analytics Study Panel

Technology experts came together during this panel to dive into analytics trends and best practices, using CGT’s recently released Retail & Consumer Goods Analytics Study as the backdrop. 

Here’s what they had to say:

Identify Tough Issues

Dealing with myriad data silos, systems and technologies is one of the biggest obstacles organizations face. “Not having continuous end-to-end visibility across all those areas is challenge,” said Abhideep Dasgupta, manager of value engineering at Celonis.

Making sense of available data is part of that challenge. “Most companies have the right data, but who do you go to help make sense of it?” asked Chris Daniel, GM of consumer products and services and industry lead at Toptal.

Collaboration that allows organizations to be “reading off the same sheet of music with regard to the same kinds of data, same scorecard, same metrics” can help with articulating data and insights, said Ryan O'Halloran, head of pre-sales and global consulting at DemandTec. 

Improve Organizational Alignment

Bringing a vision to life requires more than an idea. 

“You have to have the team structure and funds to get the end-to-end work done — so you want to get proper promotion management and proper optimization solutions in place,” said Hariharan Margabandhu, vice president of digital CX company HGS.

Considering change management in process transformation initiatives is one of the best ways to get a project across the finish line, Dasgupta said.

Refine Talent Strategy

A change in recruiting mindset will be required to find team members with “the breadth and depth and capacity to support the customer,” Margabandhu stressed. 

Dasgupta noted that a “unicorn personality” — someone with the technical skill sets, understanding of the industry and change management skills — does not exist. Technology can fill that void by taking data from one end of the spectrum to someone at the business end of the spectrum who can use AI to make sense of the data,” he said.

O'Halloran offered this prediction: “I think we're going to continue to hear about human in the loop, about augmenting the human decision-making process and arming a person with the right data, the right insights to do something with their data.”

Mark Anthony’s Sam Wong Shares AI Blueprint: Leadership Buy-In & Collaboration

For major consumer goods and retail companies, integrating AI into company ecosystems is no longer a question of “should I?” but rather “how will I?” The landscape, however, is riddled with obstacles, requiring enterprises to build a strategic roadmap before going all-in on AI.

Sam Wong, senior director of data, analytics and AI at the Mark Anthony Group — an international drinks company with products such as White Claw Hard Seltzer —  highlighted how the company overcame challenges to create an AI incubator and offered a roadmap for successfully implementing the technology. 

“When AI first came out, everyone wondered what to do about it,” Wong said, noting that many companies took a “let’s hold on” approach. Mark Anthony’s founder, Anthony von Mandl, however, had a different take on the topic. 

Read the extended coverage here.

Mars, Five Below & Generac: Building Collaborative and Resilient Supply Chains With AI

As retailers and consumer goods companies face yet another year of supply chain disruption, whether from costly tariffs, weather uncertainty or changing consumer preferences, enterprises are increasingly looking to artificial intelligence to help navigate unpredictability and increase resiliency. 

While the question of data quality comes to the forefront when building the foundation for AI supply chain investments, Andy Fox, senior director of analytics product organization at Mars Snacking, told attendees at Analytics Unite that the first thing that needs to be recognized is that data quality will never be perfect. 

Five Below’s Kim Sussman and Generac’s Neil Bhandar spoke on two things that can significantly impact the supply chain: weather and tariffs. “Our inventory level, our supply chain preparedness and our customer service teams have to be prepared to respond,” Bhandar said.

Read the extended coverage here.

Closing Keynote: Integrating Impact to Drive the Future of Retail and Consumer Groups

In the closing keynote, Gaurav Shah, global head of data, analytics and AI at Opella — an over-the-counter, vitamins, minerals and supplements company — shared how organizations can embrace innovation, foster a data-driven culture and scale AI initiatives to drive the future of retail and consumer groups.

“The next big transformation that will change the world is going to happen through AI or data. This is going to be a change that is going to impact all of our lives,” Shah said. The question becomes, “How are we preparing ourselves to get to that transformative way of working?” 

Read the extended coverage here.