Latest news with #RobSanchez
Forbes
23-06-2025
- Business
- Forbes
Leveraging Data-Driven Marketing In A Shifting Economy
Rob Sanchez is CEO of Anteriad, a leading provider of B2B marketing solutions. Data-Driven. Tech-Enabled. Growth-Obsessed. Business-to-business (B2B) marketers are under added scrutiny when operating in an economy undergoing major change. They might be dealing with a freeze on new tech implementations or resistance from leadership to try new innovations. At the same time, goals are ever higher, creating tension when budgets are being scrutinized. The good news is that today, more than ever, B2B marketers can succeed and even grow in these changing times with an approach that is focused on scaling data-driven marketing strategies. They should have robust data programs that underpin everything from analytics to identifying opportunities and activating campaigns with AI technology. The most valuable ways for B2B marketers to scale their data-driven approach include: • Diversifying the kind of data used, including intent data • Improving the accuracy and scale of data used • Better combining data and technology, especially AI The Value Of More, Better Data Marketers today have access to better data at scale than any time in the past, which can help them deliver more accurate targeting and analysis. They have better measurement practices in place to more effectively measure return on investment, lift, lifetime customer value and margin—metrics that can create confidence in a tough time. And they have new tools that can save time and money, including AI, so they can focus on the elements of their jobs that deliver the highest return. However, not all marketers are reaching the full potential of these opportunities. In fact, despite gains, many are under-performing because they are still limited by their data. One key limitation is a lack of data diversity. We are working with global marketers who are not tapping into the diversity and scale of data that is available to them. I see a few reasons that are holding them back. Many marketers start with a limited budget and feel that they must make choices. Many are unsure how to test the value of different forms of data against one another, such as comparing intent data to firmographic data. Or they are stuck with certain technology limitations that hinder their ability to scale up with additional partners. Marketers are often uncertain about the data they do have, and that stalls their ability to choose the right incremental data sources. Solving these sticking points is critical, mostly because proving the value of data often unlocks additional spending and scale. Marketers need to build a testing model that can prove to stakeholders—and themselves—the true contribution of different data sources. Secondly, marketers who do the work to increase data quality and accuracy often see data scale as well. As they become more confident in the data they do have, they can see more accurately what additional data they can add, what new prospects they can target and what new markets they can enter. Setting Yourself Up For Success With Data And AI Technology Marketers who move ahead with confidence and remain nimble when their competitors hit 'pause' can come out ahead, and this time is no different. Marketers can lean into data and AI to push ahead and create a path to improved performance in the long term. When marketers have accurate data at scale, they can get significantly more value from their technology, especially AI. AI outputs, including models, forecasts and even marketing content, are reliant on the inputs—and that often comes in the form of data. I see the power of data and technology at work in real time with our customers. When customers start to see the value of better data, they begin to increase their data flow, buying and testing new forms of data, which increases their customer and business intelligence and supports further scaling. However, to most effectively scale data-driven strategies, marketing leaders need to assess the health and accessibility of their data. Data hygiene and accessibility are the two critical pillars of success. Marketers must ensure company stakeholders are on board to invest in quality data, which means having recent, complete and accurate data as an ongoing priority. Of course, data is only valuable if it can be used, which means companies also need to audit their data storage, data flow and integrations to ensure all channels have access to it. Many companies have moved their data to the cloud to enable better data maintenance and scale. This move also helps marketers more easily feed their data into AI models for analysis and decision-making. Keep in mind that having easily accessible, quality data requires commitment and, sometimes, investment. Many companies have issues with incomplete, old, inaccurate data or technology that is not well-integrated, which makes it difficult or impossible to build multichannel marketing programs that use the data for targeting, personalization or optimization. These logistical issues must be addressed. Companies can invest in internal upgrades or consider working with third-party partners that can provide an alternative approach. Conclusion In today's shifting economy, the B2B marketers who act decisively and scale their data-driven strategies, embrace data diversity and power their technology with stronger insights can position themselves to not only survive but also win. While competitors hesitate and are held back by outdated data, rigid processes and fear of change, the most successful marketers will move ahead with speed and confidence. Scaling better data practices and fully leveraging AI isn't just about optimizing campaigns or saving costs. It's about competing in a high-stakes marketplace. In a volatile environment, there is a real temptation to play it safe. Instead, playing it smart—by building a foundation of better data and technology—positions B2B marketers to capture opportunities others might not see coming. B2B marketers who choose to lead now can emerge stronger, faster and ahead of the competition. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
Yahoo
26-05-2025
- Sport
- Yahoo
(Video): Chelsea match winner names are he's improved most in this season
Levi Colwill had an excellent game yesterday not only defensively, but also in scoring perhaps the most important goal of Chelsea's season. It earned them 3 points today and got them into the Champions League, ultimately. Speaking to Chelsea TV after the game, he didn't hide his joy at having got the goal. 'It was a tough game. We always knew it was going to be a tough atmosphere and a tough place to play, but we showed the maturity about us and we got the win,' the defender said. 'We didn't play the football that we like to, that we usually do, but we got the win, and we knew that coming in [that's what we needed] and that's what we did, simple as.' 'We were mature, and we got the job done. We got a clean sheet in a game like this, where they hit you on the hard counter attacks, and they're very good at that. For us to stop them and nullify them, I think we did a really good job defensively. But that starts with Pedro [Neto] as a nine, all the way back to Rob [Sanchez] in goal. He said his goal had felt like it was in 'slow motion,' and having gambled at the far post, he got his reward. 'I've matured a lot, I'm playing for the team a lot more now. If we win and get a clean sheet, I'm happy,' the academy defender concluded. We've already made it clear how much we like Levi, and we can't wait to see him continue to develop in this team. His ceiling is so high, and he took another step towards it with his performance today. You can see the defender speaking in the clip embedded here:
Forbes
09-04-2025
- Business
- Forbes
Why Competitive Data Is The CEO's Secret Weapon In The Age Of AI
Rob Sanchez is CEO of Anteriad, a leading provider of B2B marketing solutions. Data-Driven. Tech-Enabled. Growth-Obsessed. Many CEOs I speak with are thinking about how AI can be woven into their business processes to increase efficiency, reduce costs and gain strategic insight. Unlike many technological advances in the past, AI is available to everyone. Foundational AI models like Chat GPT can be accessed by any company and major tech providers are building AI into their platforms so that all of their customers can use it. Because of this commoditization, competitive AI strategies are only as good as the data that drives the AI decision-making. Therefore, a competitive AI strategy requires a competitive data strategy. Data needs to be accurate, representative, recent, comprehensive and comply with privacy best practices. It also must be unique. While it takes work, CEOs who build differentiated, high-quality data assets can build a competitive moat that differentiates them from the competition. To achieve this—and ensure that data is being used effectively across the company—CEOs need a top-down strategy with clear goals and KPIs. The work is a two-step process, starting with a foundation of data best practices. From there, the company can build the data assets that differentiate it and hopefully deliver exponential returns. Many companies struggle with data quality issues (paywall), yet they are already leaping to employ AI-driven models and processes. This can be dangerous for many reasons. Companies with low-quality data could end up with AI outputs that are inaccurate and biased, which could send the company's strategy in the wrong direction, frustrate customers or worse. Conversely, companies with high-quality data usually end up with AI outputs that can deliver incremental increases in efficiency, insight and performance. Thus, it pays to educate the entire company about the value of prioritizing high-quality data and put data best practices into place. IBM has a checklist of actions every company should take to improve data governance, create data feedback loops, update data regularly and train employees. If you haven't already, work to ensure you have the basic elements in place so you won't be hamstrung as AI infiltrates more and more business processes. Creating a culture of data excellence not only helps data analysts, but everyone in the company that's considering using data. For example, marketing and sales require high-quality data at scale to understand customers through AI analysis or personalization and business intelligence needs comprehensive metrics across departments to measure contribution and lift of different activities using AI. As you work to educate teams, share how these practices can benefit each team in their work—this will help with adoption and compliance. With data best practices in place, your company is now ready to utilize AI. As a CEO, you can begin thinking about how to use the tool to create a competitive advantage. One strategy is to aim for superior data. This can be done by gathering data that is 100% compliant and cleansing data regularly. With pristine data, companies can get better insights and better outcomes than their competition that may be less diligent. CEOs can work with their teams to build out more complete data, data that's more scaled and create data sets with the most recent data possible. Data can be obtained via first-party data collection and/or partnerships with specific data providers. The right approach depends on what the data will be used for. For example, a company with a lot of self-service customers who buy online frequently could use AI for better on-site personalization. This requires comprehensive recent data that can be collected from the website, as well as online data partners that provide recent intent data. Another approach is to consider the first-party data that can drive specific business practices and focus on collecting the exact insights needed to drive lift. A manufacturing company that sells to large construction companies may want to use predictive models to forecast future demand. They might determine that the more they understand about the very specific types of projects each individual client has, the smarter their AI-based forecasts will be, and in turn, collect more insight about their customers' projects. This can not only help the company's financial outlook but also inform sales, marketing and customer strategies that are more relevant than those of competitors. Finding the right competitive data to deliver the highest performance gains is an ongoing process. You can help your company achieve continuous growth by encouraging a culture that focuses on creating a hypothesis, testing and improving—and accepting that some tests will fall flat while others will be great successes. AI is a complex process and data strategies need to be tested, updated and improved over time. I believe CEOs who embrace the journey will experience the greatest advantage. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
