In this article, we discuss how predictive analytics helps identify market shifts, how to use data to align with future trends, and how scenario planning can prepare organizations for emerging opportunities or threats.

As marketing becomes more data-driven, collaboration between marketing and data teams becomes more and more essential for building effective strategies. Yet, a gap often exists: marketers may lack the data literacy needed to fully engage with their data-focused colleagues. Thus, by embracing data literacy, marketers can bridge this gap, align on shared goals, and improve team impact—the trifecta of data-driven collaboration. Let’s explore how a solid understanding of data allows marketers to actively contribute to data goals, enhance cross-functional teamwork, and maximize overall impact.

With increasing talk about artificial intelligence (AI) in all corners of the business, including marketing, data is on everyone’s mind. Yet customer data has always been important for businesses to prioritize. The move away from third-party cookies and an all-too-heavy reliance on third parties in general has accelerated this. So, too, has AI and the promise of using approaches such as generative AI and predictive analytics to give customers a better experience that is more tailored.

In this article, we will discuss the top strategies for cultivating a predictive mindset across your organization. We’ll cover three main points: fostering a culture of continuous learning, conducting effective environmental scanning, and implementing scenario planning to stay ahead of industry shifts.

In any organization, clarity of roles and responsibilities is paramount to fostering a productive and harmonious work environment. When roles are ambiguous, conflict and friction are likely to arise. Let’s explore how clearly defined roles can significantly reduce conflict, enhance collaboration, and ultimately drive organizational success.

This was written by Greg Kihlström for the Medallia Blog. I recently had the pleasure of hosting Medallia’s virtual event to celebrate CX Day. This year’s theme was all about deepening our understanding of customer experience through insights and actionable strategies. 

This article was written by Greg Kihlström for CustomerThink. Customer lifetime value (CLV) is a crucial metric that businesses should prioritize in order to drive sustainable growth and profitability. CLV refers to the total value a customer brings to a business over the course of their relationship. It takes into account not just the initial transaction, but also the potential for repeat purchases and long-term loyalty.

This article was written by Greg Kihlström for MarTech. In the era of big data, businesses have recognized the value of collecting vast amounts of information about their customers, operations and market trends. But, many still struggle to transform this data into actionable insights. This is where predictive analytics comes into play.

The future of manufacturing lies in agility, responsiveness, and a commitment to innovation—principles that are at the heart of effective change management. By leveraging data for operational improvement, organizations can not only enhance their internal processes but also position themselves as leaders in their respective industries. As they navigate this transformative journey, companies must remain focused on engaging their stakeholders, fostering a culture of continuous improvement, and embracing the wealth of insights that data has to offer.

Organizations are inundated with vast amounts of data generated from various customer interactions across multiple channels. While the abundance of data presents a significant opportunity for businesses to enhance customer experience (CX) and drive customer loyalty, it also poses challenges, particularly in terms of alignment within the organization. The need for a cohesive strategy that leverages this data to break down silos and foster collaboration among internal teams has never been more critical.

In order to effectively prioritize and adapt to the ever-changing landscape of business, organizations must understand the significance of differential adaptability. This capability allows them to identify and allocate resources based on the relative importance and urgency of threats and opportunities they face.

The concept of a priority mindset in organizational culture revolves around a collective belief and approach that hones in on strategic importance, rather than getting caught up in trivial tasks or distractions. This powerful mindset empowers individuals to prioritize their work and resources based on the greater purpose and mission of the organization, rather than simply reacting to urgent demands.

The ability to remain agile in marketing strategies is more crucial than ever, including the importance of adaptability and responsiveness to consumer needs and market dynamics. As brands strive to connect with their audiences, they must embrace an agile mindset that prioritizes ongoing learning, flexibility, and a deep understanding of their target demographics. Let’s explore the significance of agility in marketing strategies and how it can drive brand success in a competitive landscape.

With the pressures that most brands face to show wins against the competition and gaining access to new markets, businesses are increasingly focused on short-term gains, often prioritizing immediate profitability over long-term success. However, sustainable growth and enduring success require a more holistic approach, one that considers the total value a business can generate throughout its entire operational lifespan. This is where Business Lifetime Value (BLV) comes into play.

This article was written for CMSWire by Greg Kihlström. Does your organization think of website experience optimization as something that needs to get revisited every couple of years at most? When you want to make revisions to the experience and test new changes, are you met with resistance, and a “didn’t we just redesign the website?” If so, you aren’t alone, but you are right if you are thinking there is a better way to approach digital experiences.

The sixth principle of priorities that I explore in my book, Priority is Action is that the methods, tools, and other approaches used to achieve our initial success will almost never work to get us to further and greater success in the future. Thus, we need to have the humility to admit we don’t have all the answers, and the curiosity to try new things.

Real-time data plays a crucial role in driving customer experience in today's digital age. The ability to access and analyze data instantly allows businesses to deliver personalized and timely interactions with their customers, ultimately enhancing customer satisfaction and loyalty. Let’s explore how real-time data drives customer experience and why it is essential for businesses to prioritize real-time data handling in order to stay competitive in the market.

There has been a lot going on in the news cycle of late, but one thing you surely caught was Google’s announcement that it is abandoning its plans to fully deprecate third-party cookies, though the company claims to remain committed to its Privacy Sandbox project that has been exploring alternatives to using cookies to track users to enable digital advertising. The headlines, however have been spelling it out pretty clearly: Google has abandoned its plan to kill the cookie.

The sixth principle of priorities that I explore in my book, Priority is Action is that the methods, tools, and other approaches used to achieve our initial success will almost never work to get us to further and greater success in the future. Thus, we need to have the humility to admit we don’t have all the answers, and the curiosity to try new things.

This article was written for MarTech by Greg Kihlström. The ability to have the tools and information to make data-driven decisions is no longer a “nice to have” but a necessity. Teams relying on gut instincts and anecdotal evidence for planning are falling behind more sophisticated brands using predictive analytics and data insights.