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Metrics can tell you if youre going the right direction or not. They can also be a waste of time if the metrics are noise instead of strong signals. There is no one right answer to which metrics to use, but understanding how others use them can turn on a light bulb for new ideas. We asked our Fast Company Impact Council members what metrics they track obsessivelyand why and the answers we share may have you rethinking your own tracking. 1. CONVERSION AND RETENTION I track a lot of metrics and it’s easy to get lost in the minutiae of the business, but as a subscription business the metrics of conversion and retention are my twin North Stars. What percentage of visitors in trial are going to become paid subscribers, and what percentage of them will remain paid subscribers in three months? Really these metrics are a reflection of the benefit customers get from our products showing they are valuable enough for someone to pay us and that they are valuable enough for them to stick around. Nearly all of the other metrics that I obsessively check flow from these two. Tony Grimminck, Scribd, Inc. 2. ORGANIC GOOGLE SEARCH I track organic Google search above almost everything. You can buy impressions, but you cant buy someone typing your brand name unprompted. Its the cleanest signal of real demand. I also monitor inbound pullwhich partners, retailers, or creators are reaching out to us. When serious brands want proximity, it means youre culturally relevant. If search and inbound drop when spend drops, youre renting attention, not building equity. And then theres the quiet test: What happens when we ease off spend? Do we disappear or are we building something worthy of the space weve been given? Emily Kortlang, Yerba Madre 3. EBITDA I track EBITDA because it tells me, without any spin, whether our core business is creating the level of profitability that powers reinvestment and growth for our employee owners. I track labor as a percentage of net revenue, staff churn, and our employee culture index scores because they tell me how efficiently were deploying our talent and how engaged our people are in building a career here. Steven McKay, DLR Group 4. HOW CLIENTS RANK IN AI PROMPTS Right now, were obsessively tracking how our clients rank in prompts across ChatGPT, Gemini, and Claude. Its a new metric for us, but an important one. We want to see how clients show up next to competitors and what narratives or keywords are driving visibility. We layer that with media coverage and domain authority to understand how those stories are performing in the real world. Kalie Moore, High Vibe PR 5. CONTENT AND PRODUCTS We measure content and products to see how they drive behavior change, build confidence, and turn users into advocates for themselves. Engagement matters, but for us the real signal of success is when people feel empowered to act. As we build for people with real, timely needs, we track both quantitative and qualitative insights to ensure were solving the right problems, not guessing. That requires constant testing, learning, and refining. Across industries, leaders have to stay close to the people they serve to ensure theyre truly advancing the mission they set out to achieve. Nathan Friedman, Understood.org 6. INTERNAL ALIGNMENT AND EXTERNAL TRACTION I track two buckets: internal alignment and external traction. Internally, we run on objectives and key results because it forces clarity. Everyone knows what they’re responsible for and how it ties to business impact. When that breaks, you feel it. When it works, things move fast. Externally, I watch streaming and radio. Streaming shows what’s happening right now, which cities are reacting, whether a record is moving culturally. Radio signals longevity. It’s slower, but it shows real staying power. Together, they tell me if we’re seeing noise or building something durable. You need both. Logan Mulvey, GoDigital Music 7. CUSTOMER METRICS As CEO, I obsess over daily and weekly metrics like monthly recurring revenue growth, subscription churn, data-plan attach rate, NPS, transmission success rate, and early field reliability (battery life, zero-transmission failures), because recurring revenue powers the business. Any drop in trust kills referrals fast. If customer metrics are healthy so is our business. Jeff Peel, Tactacam 8. RETENTION AND SAVINGS We track retention of our members, as we offer a lifelong commitment to our C-suite women leaders to provide them with one-on-one peer mentoring for life. This commitment increases our retention to 99%. We also track the mentor/mentee relationship. Lastly, we track our savings, which annually exceed $500,000. Larraine Segil, Exceptional Women Alliance 9. ENGAGEMENT AND CUSTOMER SATISFACTION We track engagement and customer satisfaction obsessively. For us, engagement isnt just a usage metric, its a signal of trust. When someone actively redeems and returns to our platform, that tells us the experience is resonating. Customer satisfaction is even more important. If people feel valued rather than marketed to, long-term relationships followand so does durable revenue for our partners. Elery Pfeffer, Nift 10. WHERE OUR BUSINESS IS GOING When reviewing metrics, Im looking for information about where our business is going, not lagging indicators of where weve been, and early warning signs of issues that may be developing. For growth, I look at pipeline coverage and conversion. For execution, I review forecast accuracy and time to revenue. For customer value, its our net retention rate and advocacy score. Looking at these numbers gives me a good idea of not only how were performing, but how efficiently were executing and what areas need extra attention. Steve Holdridge, Dayforce 11. JOBS AND ECONOMICS REPORTS I obsessively track LinkedIns Jobs on the Rise reports and LinkedIs Economic Graph workforce data and research; they are great reads and provide ongoing snapshots on where the labor market, productivity and future of work are moving broadly. I also track the U.S. Bureau of Labor Statistics Productivity and Costs report, to understand where workplace productivity is heading. Its an excellent dashboard across key indicators and in recent years can be a strong signal on how technology, automation, and operatingmodel changes are actually changing worker productivity at scale. Alice Mann, Mann Partners 12. PROGRESS Progress against the big rocks we established. Setting broad, strategic yet outcome-based goals align the entire organization and drive results. Michael Tannenbaum, Figure 13. ENGAGEMENT, FRICTION, AND CLIENT IMPACT I think about performance in three pillars: people, process, and product. Some of it is measurable. Some of it you feel. Both matter. On people, I track engagement, retention of top talent, and how often we promote from within. If the bench isn’t deep, nothing scales. On process, I look at friction. How fast do we decide? Is delivery predictable? The best strategy collapses without operational clarity. On product, I focus on client impact, repeat business, and quality. We have a Slack channel devoted to verbatim client praise. Data matters. But when you’re the first call a client makes on their hardest day, that’s the clearest signal of all. Peter Smart, Fantasy 14. THE FUNNEL For Scribbly, my D2C business, I use every tiny tracking pixel in my funnel. I built a custom dashboard for myself and trained an AI agent to analyze the data just the way I want itway better than those messy SaaS analytics dashboards that are impossible to decipher. Lindsey Witmer Collins, WLCM Studio 15. NON-CUMULATIVE DATA Cumulative data is meaningful, but only non-cumulative data holds you accountable. For us, one such metric is how many of the Solvers selected over the past five years are still operational. Were at 96%. That tells me our selection methods and support programs have a real impact, given that industry averages hover around 70-80%. Something else a company can track is instead of asking where are you now? ask how far have you come? That’s harder to quantify than dollars raised or media hits, but it’s the only number that tells me whether we’re doing our job. Revenue, employees, money raisedthose keep the lights on. But the distance traveled keeps us honest about the mission. Hala Hanna, MIT Solve 16. BOOMERANGS AND EMPLOYEE DEPARTURES Weve been focused on people-centric workplace data since we started building a center of gravity for brilliant minds almost three decades ago. We regard the percentage of boomerangs in a company as a leading indicator of having a positive, thriving culture that people value and want to be part of. At the other end of the spectrum, the rate of regrettable departures usually signals when there are culture issues that must be addressed. Leerom Segal, Klick Health 17. ENGAGEMENT QUALITY, AUDIENCE SENTIMENT, AND BRAND LIFT We prioritize engagement quality, audience sentiment, and brand lift because they tie directly to real business outcomes, not vanity metrics. We trademarked true human influence to make influencer marketing more measurable, backing it with proprietary technology and trusted measurement partners to ensure we deliver against brand KPIs. And with AI driving the convergence of creator and affiliate marketing, we can now connect authentic storytelling to commerce at scale. Ben Jeffries, Influencer
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Agricultural data is fragmented, distributed, heterogeneous, and incompatible. Thats the verdict from a major Council for Agricultural Science and Technology report published barely a year ago, and it helps explain why AI has struggled to gain traction on farms. Other data-heavy industries, like healthcare or financial services, have established data standards, but agriculture has no universal framework for translating between the dozens of systems that generate field-level information. This isnt a new observation, but its persistence is noteworthy. While consumer tech and enterprise software largely solved their interoperability challenges years ago, agriculture still generates enormous volumes of information trapped in incompatible silos. Research institutions publish trial results in inconsistent formats, product manufacturers use proprietary naming systems, farmers record observations with local terminology and retailers track sales without connecting them to agronomic outcomes. The result is an industry sitting on massive amounts of information it can barely use. Agriculture doesnt have a data problemit has an intelligence problem, notes Ron Baruchi, CEO of Agmatix, a company building domain-specific AI for the sector. The data exists. Whats missing is infrastructure that understands what it means. According to a McKinsey report, implementing data integration, and connectivity in agriculture could add $500 billion in value to global GDPa 7 to 9% improvement over current projections. But capturing that value requires solving a problem that general-purpose AI platforms have consistently struggled with. WHY HORIZONTAL AI KEEPS FAILING IN FARMS The appeal of applying large language models to agriculture is obvious: A farmer could describe whats happening in their field and get instant advice on what to do about it, without hiring a consultant or having to wait for a lab. But agricultures complexity breaks the approach. While an LLM trained on internet text might know that nitrogen helps plants grow, it cant tell you that the right amount changes depending on the growth stage, the soil and what was planted in the same field the previous year. Similarly, computer vision can identify crop stress, but without contextual knowledge of weather, soil and product applications, that insight doesnt mean much. You can ask ChatGPT about nitrogen fertilization and get an answer that sounds authoritative. But when you dig into specificstiming for your soil type, interactions with your previous crop, and product selection based on local availabilitythe recommendations fall apart. The same CAST report reinforces this point, noting that many farmers distrust AI because of its black box naturemodels making predictions without clear explanations behind them. In farming, 90% accuracy on a fungicide recommendation means 10% of the time youre telling a grower to spray the wrong product at the wrong time. BUILDING INTELLIGENCE FROM THE GROUND UP This is where a growing number of companies are taking a different approachbuilding AI systems designed specifically for agriculture rather than retrofitting general-purpose tools. For example, India-based Cropin, backed by Google, has constructed its own crop knowledge graph spanning 500 crops across 103 countries and recently developed an agriculture-specific micro-language model. Israeli-American startup Agmatix built its own agricultural intelligence system from the ground upan approach that mirrors, in concept, what Palantir did for defense and intelligence data. The core of that system is what Agmatix calls pre-trained ontologies: Frameworks that encode agricultural relationships before customer data enters the system. Agmatixs AI engine uses a neuro-symbolic architecture, combining structured knowledge graphs with machine learning. Agricultural relationshipshow specific fertilizers interact with specific soils at specific growth stagesare encoded by agronomists, validated through field trials and refined continuously. What that means, essentially, is that the AI doesnt start from scratch. Before it touches any farms data, agronomists have already taught it how agriculture workswhich fertilizers affect which soils, how a crops needs change as it grows, and why what was planted last season matters for whats planted next. According to the company, the system has structured more than 1.5 billion field trial data points, creating what data scientists call semantic interoperability: The ability to translate between different data sources because the system understands what the data means, not just what it says. But building better technology doesnt guarantee adoption. McKinsey partner Vasanth Ganesan noted in the firms 2024 Global Farmer Insights survey that farmers are demanding clearer ROI, lower cost of implementation and maintenance and easier-to-setup technologiescomplaints shaped by years of agtech tools that overpromised and underdelivered. A separate McKinsey analysis found that poor user experiences continue to hold back adoption across the sector. Baruchi says farmers have good reason to be cautious. Farmers are CEOs operating in one of the most unpredictable industries on earth, he tells Fast Company. They balance biological systems, financial risk and environmental volatility every single season. The ROI question is only hard to answer when your platform cant connect what a grower applies to what actually happens in the field. WHERE ITS WORKING The approach is already operating across several deployments. BASF has collaborated with Agmatix on digital tools for crop disease detection, including a recently announced project targeting soybean cyst nematode. The company says growers using its prediction platform have reduced fungicide costs by 15 to 20% while maintaining disease control. Its engine is also powering predictive disease-risk modeling in large-scale row-crop systems in the United States. A national agriculture ministry uses the system to model policy impacts before implementation. On the sustainability front, Agmatixs RegenIQ platform works with major food and beverage companies to assess which regenerative practices deliver measurable results in specific field conditionsclassifying, for instance, Brazils 150 coffee-growing localities into six distinct climate clusters, each requiring different approaches. Cropin, meanwhile, partnered with Walmart in March 2025 to optimize fresh produce sourcing across U.S. ad South American markets using AI-driven yield forecasting and crop health monitoring. THE HARD PART REMAINS Agmatix represents a broader shift from horizontal AI platforms toward domain-specific solutions. But it isnt the only company betting that agriculture needs its own AI. John Deeres acquisition of aerial analytics firm Sentera in May 2025 suggests the industrys biggest players have reached the same conclusion. The AI in agriculture market is projected to grow from $2.55 billion in 2025 to over $7 billion by 2030, according to Mordor Intelligence. But adoption remains uneven, with 81% of large farms showing willingness to adopt AI, while only 36% of smaller operations plan to do the same. Agricultural AI adoption is still slow by any standard, and its not hard to see why. CASTs report catalogs the major barriers that agriculture still faces today: High costs, limited rural broadband, insufficient training and unresolved questions about data ownership. These challenges intensify in an industry previously plagued by overhyped technology promises. But the tailwinds are real. Major food companies have made commitments to decarbonize supply chains that are impossible to fulfill without field-level data. Climate volatility is making predictive tools more valuable. And a decline in U.S. public agricultural R&D spending down roughly a third from its 2002 peak, according to USDA data is creating a vacuum that private-sector platforms are positioned to fill. The question isnt whether agriculture needs better data infrastructure. Its whether the companies building it can survive farmings patient adoption timelines long enough to reach critical mass and whether the benefits will extend beyond the largest farms that can already afford to invest. For an industry responsible for feeding 8 billion people, getting that balance right matters enormously.
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E-Commerce
Hello and welcome to Modern CEO! Im Stephanie Mehta, CEO and chief content officer of Mansueto Ventures. Each week this newsletter explores inclusive approaches to leadership drawn from conversations with executives and entrepreneurs, and from the pages of Inc. and Fast Company. If you received this newsletter from a friend, you can sign up to get it yourself every Monday morning. Last weeks Modern CEO made the case that boards and recruiters should stop focusing on CEO candidates résumés and start evaluating their potential for agility. That said, one aspect of work history can serve as a good proxy for the ability to manage uncertainty and change: international experience. Leaders who have global exposure tend to develop sharper instincts for adapting in different contexts, taking in information effectively, and making business decisions based on these different inputs, says Jeff Sanders, vice chair and co-managing partner of the global CEO & Board of Directors Practice for Heidrick & Struggles. New research from the executive search firm shows that one in five Fortune 500 companiesthe largest enterprises in the U.S. by revenueappointed CEOs with cross-border experience in 2025. More than a third of external candidates named to the top job last year worked internationally. Theyve already had to respond to complexity in real timeand that kind of experience becomes increasingly valuable as global conditions continue to evolve and shift, Sanders adds. Charting new territory Ariane Gorin, CEO of Expedia Group, credits her global experience with helping to shape her leadership style. Gorin spent 23 years in Europe: 13 years in Paris and 10 years in London, where she held several senior positions at Expedia before becoming CEO of the Seattle-based travel technology company in May 2024. The biggest thing is youre out of your comfort zone, she says of working abroad. Gorin, who is fluent in French, notes that speaking a language is different than doing business with others in that language. Youre just always a little bit uncomfortable, she says, adding: It also forces you to listen more. Working abroad also fosters empathy, another quality recruiters call out as a trait they seek in future CEOs: I spent my first 11 years at Expedia in Europe [working with colleagues in America], and I will never forget what it feels like to be the only one whos on the late-night calls, Gorin recalls. Perhaps not surprising for a CEO whose company facilitates travel, Gorin also believes in the importance of geographic diversity in her leadership team. The president of Expedia Group B2B is based in Madrid, and the chief commercial officer is in London. I think if your leadership team is all in the same place, it certainly makes it easier to get things done, but you can start to have a myopic view, she says. Expanding horizons As technological and geopolitical complexities become the norm in business, leaders with international experience often have real-world experience managing disruptions to supply chains, strategy, and talent, says Heidrick & Struggless Sanders. Gorins agility is getting put to the test as the travel industry is feeling the impact of the U.S.Israel attacks on Iran launched last month, and artificial intelligence continues to transform tech companies. During Gorins time as CEO, the company has expanded its use of artificial intelligence (AI) to assist travelers and featured partners like hotels, airlines, and car rental companies. (It was early to embed the Expedia app into OpenAIs ChatGPT chatbot.) The Expedia Group, whose flagship brands include Expedia, Vrbo, and Hotels.com, last year posted revenue of $14.7 billion, up 8% from 2024. Regardless of whether an executive secures an international posting, Gorin believes travel to other countries is critical to understanding global business. When she stepped into her previous role running Expedias business-to-business (B2B) unit, she embarked on a two-week trip around the world, meeting clients in Japan, Korea, Australia, and the U.S.a journey that helped her appreciate the business and cultural nuances of each market. Gorin also makes a case that travel can open the mind. She says: Getting out of your day-to-day into a new environment jogs a lot of creativity. Working a world away Are you an executive who has worked internationally, and if so, how did that experience shape the way you lead and think? Did it make you more agile? How? Send your stories to me at stephaniemehta@mansueto.com. Ill publish the best examples in a future newsletter. Read more: global business Honeywell CEOs leadership style is shaped by his time in the field The Most Innovative Companies in Asia-Pacific When Starwoods CEO moved his leadership team to China
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E-Commerce
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