Your team members doubt the value of analytics in marketing. How can you convince them of its benefits?

In our agency, we always make the decisions after analyzing the data. If the data is not present with the new clients we do some campaigns by analyzing the audience and competitors. When we get the data we make suggestions as per them. Few benefits of data-driven decisions - 1) It gives better ROI 2) Better customization of the content and personalized offers can be released 3) Budgeting also becomes accurate 4) Loyalty of the customer increases for the brand 5) Better targeting of the audience 6) Reduce risk 7) Saves time for the marketing team 8) Advantage over the competition, as most small businessmen decide out of gut feeling.

Having both an extensive business and quantitative background, I’ve learned that many decisions in business are often made with limited information. In the past, managers frequently relied on 'gut feel' decisions based on limited information. Today, however, with the advent of AI and analytics tools, we can make decisions with not only more comprehensive data—what is often referred to as big data—but also with greater predictive accuracy. This progress is made possible by advancements in technology. As time goes on, management decisions will continue to improve, although this advantage will apply to every company within an industry. Therefore, the better equipped you are with analytics, the more likely your business is to succeed.

Data-driven decision-making goes beyond immediate metrics to uncover deeper insights into customer behavior. By integrating predictive analytics and machine learning, you can anticipate market trends and adapt strategies proactively. This approach ensures more strategic resource allocation and positions your brand to stay ahead of changes, reducing reliance on reactive measures. Embracing these advanced analytics fosters a culture of continuous improvement and drives long-term growth, making your marketing efforts not just effective but also resilient to evolving market dynamics

Customer data can provide insights on which marketing efforts (campaigns or tactics) are more effective. This can lead to a better allocation of marketing resources and a better ROI/ ROM (Return on Marketing). But looking back is only one part of the opportunity. You can look forward to better understand how to respond to new market dynamics. A third opportunity areas exists when you utilize marketing analytics operationally. This can include analytics to actively improve messaging, targeting, and other elements in the customer journey. My team helped a client in the Pharmaceutical industry implement this and it resulted in more relevant and differentiated interactions, higher conversations, and more sales.

In my experience, I've found that diving into customer data isn't just about tracking what's working; it's about understanding why certain strategies succeed while others fall short. This insight allows me to allocate resources more effectively, cutting unnecessary spending on underperforming campaigns and focusing more on initiatives that truly resonate with our audience. Beyond just optimizing current efforts, analytics has also enabled me to forecast trends and adapt to market changes, ensuring our marketing remains agile and impactful. It's this proactive approach, grounded in data, that helps me make decisions that are not only justifiable but also strategically sound.

Analytics and AI tools now allow us to identify patterns in customer purchase habits that would have been enormously difficult to detect just a decade ago. Companies can now examine every customer touchpoint, gauge their reactions through NPS surveys, and analyze responses to specific changes in how we engage with them. This is honestly the best thing to happen to customer experience. We no longer live in a world where everyone has to buy a car in black, as in the Henry Ford era. Customers demand more customization, and technology is enabling us to make those customizations easier to understand and implement. It’s a win-win for both the company and the customers.

Customer Insights work with marketing analytics and drive both strategic and operational decision making. Customer Insights are at the center of what I call a Customer Centric operating model. Such an operating model then has major implications for a firm. Our teams helped a couple of clients implement such a model. It started with analytical models that helped us understand how we make money via customers (customer economics) and then incorporated a schema to understand how we appeal to unique customer needs (needs analysis). Combining customer economics with customer needs can drive a segmentation model (or personas). This segmentation can then support a number of both strategic and operational marketing decisions.

With new AI advancements, we are now able to track most digital customer touchpoints and estimate with reasonable accuracy how campaigns are performing. This data is then combined with information on costs per media channel and customer type to calculate marketing return on investment (ROI). This allows us to make informed decisions on whether to allocate more budget to TV versus digital for a specific customer or segment. I am thrilled to be leading these types of projects.

To convince your team of marketing analytics' value, emphasize its ability to drive data-driven decisions and provide deep customer insights. Analytics helps identify effective marketing efforts, optimize resource allocation, and improve ROI by reducing wasted budget on underperforming campaigns. Additionally, it offers comprehensive views of customer behavior and preferences, enabling personalized marketing that boosts satisfaction, loyalty, and conversion rates. This targeted approach demonstrates the tangible benefits of using analytics in marketing, enhancing both efficiency and effectiveness.

Marketing Analytics encompasses many methodologies and disciplines: web analytics, CRM analytics, brand equity analytics, sentiment analysis, journey analytics, market share analysis, conversion rate optimization, as well as the analysis of primary research such as from surveys and interviews. All of these methods have implications for future planning. For example, brand equity and market share analytics can help you see where there is white space across your peer set of competitors to enhance your product in way that will steal market share. I've helped a SaaS based client with this, we came up with a few product modifications as a result, and the product stole competitive share in the months that followed the new product launch.