Chief Marketing Officers (CMOs) hold a unique position in the modern digital landscape. Businesses now have access to unprecedented volumes of consumer data. But what sets a successful CMO apart isn't just the ability to gather this data, but the skill to interpret it, thereby making informed decisions that guide their marketing strategy toward success. Harnessing the power of data is no longer optional - it’s imperative.
However, this newfound responsibility doesn’t come without its challenges. As CMOs face the growing complexity of data, they often find themselves drowned in a sea of numbers, struggling to transform them into meaningful and actionable insights. A significant 67% of B2B CMOs report feeling overwhelmed by the volume of marketing data and are unsure of how to process it effectively, according to Adverity.
This article aims to guide CMOs through these complexities by harnessing the power of revenue intelligence capabilities. Known as an advanced form of data analytics, revenue intelligence provides CMOs with a holistic view of business performance, customer behavior, and market trends. It equips CMOs with the right tools to make informed decisions that align with their business goals and drive growth and profitability.
The importance of data-driven decision-making for CMOs
Data-driven decision-making refers to the practice of making informed and strategic choices by analyzing relevant data and deriving actionable insights. It’s a shift in mindset from opinion-based decision-making to a more objective, data-oriented approach.
For a CMO, data-driven decision-making provides a powerful tool for understanding consumer behavior, enhancing customer experience, improving business performance, and predicting future trends. In today’s increasingly competitive business landscape, the ability to make data-driven decisions can be the difference between success and failure, as confirmed by Forrester researchers:
“[Today] B2B CMOs cannot rely on replicating the marketing investment strategies from previous years and expect the same or improved outcomes. B2B marketing executives must commit to [data-driven] decision-making that focuses on long-term, profitable growth and resists reactive, short-term, cost-cutting decisions.”
There are three key areas that data-driven decision making can benefit CMOs in all industries:
First, it gives CMOs the ability to dive deeper into customer insights. By analyzing data on customer interactions, purchase histories, social media behavior, and more, CMOs can create personalized marketing strategies that resonate with their target audiences on a deeper level.
With data at their fingertips, CMOs can predict what customers need before they know it themselves. This approach not only enhances customer satisfaction and loyalty but also provides a significant competitive edge.
Second, it plays a crucial role in optimizing return on investment (ROI). By harnessing the power of data analytics, CMOs can measure the effectiveness of marketing campaigns, identify high-performing activities, and make necessary adjustments in real-time.
Hence, they can reduce operational costs and ensure that every marketing dollar is put to the best possible use. McKinsey reported that companies using data-driven B2B sales-growth engines could achieve above-market growth and increase EBITDA by 15% to 25%.
Additionally, data-driven strategies streamline marketing operations. By automating repetitive tasks and using data to inform strategic decisions, CMOs can achieve greater efficiency, allowing their teams to focus on creative and strategic endeavors rather than time-consuming administrative tasks.
Third, as the massive shift to digital-first buying continues to evolve, data-driven decision-making will only grow in importance. According to Gartner, "83% of B2B buyers prefer ordering or paying through digital commerce," and "almost 50% of B2B decision-makers avoid interacting with a sales representative."
To adapt to this change, CMOs have to deepen their understanding of customers’ needs and equip their sales force with enhanced tools for selling. This can only be achieved by integrating digital and human-led channels and then leveraging customer data to its fullest potential.
The challenges of implementing data-driven decision-making
Data-driven decision-making has the potential to become a game-changer for businesses, promising a world where precise, reliable, and timely data inform strategic decisions. That said, implementing it comes with its own set of challenges.
1. Data silos
Data silos occur when data is stored separately across different departments or systems within an organization, making it difficult to consolidate for comprehensive analysis.
In a survey conducted in 2022, Gartner found that the challenges of “data are inconsistent across sources” and “data are difficult to access” are the top reasons why analytics are not used when making decisions. This fragmentation often leads to inconsistent conclusions, as different teams might have access to different data sets.
2. Lack of tools and resources
Even when data is available, CMOs might need more tools and resources to analyze and interpret it. Adverity’s survey revealed that "with finances already a significant concern, many companies may be under strain, leading them to tighten purse strings and cap their spending on data ops." Also, "an overwhelming 70% of CMOs name money, not time, as their most stretched resource."
As the world of data analysis changes and grows, teams that don’t keep up risk not getting the most from their marketing budgets. They might not gather all the data from every source and understand what it’s telling them.
This could lead to mistakes in data analysis, which can cause poor decisions and plans. Also, data analysis processes can take a lot of time without the right tools and be less productive.
3. Skill gaps
Data literacy isn’t a skill that comes naturally to everyone. In the latest survey of 1,015 Swiss CMOs, Deloitte found that “making sense of data, using it across the entire organization/functions, generating a 360-degree/single-customer view (as a prerequisite for personalization), showing ROI and getting executive sponsorship for digital projects are the implementation challenges facing CMOs.”
To fully benefit from data-driven decision-making, Deloitte researchers emphasized that “CMOs must now combine a full suite of cross-discipline skills—marketing, analytics and creative—to deliver the customer insights that influence decision making and shape corporate strategy.”
They also “need to establish a team that includes individuals with “blue skills” (e.g., business acumen, communication skills, persuasion, and negotiation) as well as those with “red skills” (e.g., data, analytics, information design, sophisticated analysis).”
How revenue intelligence capabilities can help CMOs
Revenue intelligence is an advanced data analysis method that uses artificial intelligence (AI) and machine learning (ML) to process vast amounts of data from diverse sources. It aims to provide real-time, actionable insights about business performance, customer behavior, sales trends, and more.
For CMOs, revenue intelligence capabilities present a transformative approach to understanding business data. It presents an opportunity to pivot from decisions based on intuition or past experiences to data-driven choices that are more accurate and reliable. Specifically, it helps:
- Identify and prioritize high-value opportunities: Revenue intelligence enables CMOs to determine the most lucrative opportunities, providing a significant competitive advantage. For example, by analyzing past sales, customer engagement, and market trends, revenue intelligence can track patterns and predict which product lines or geographical areas will likely deliver the highest revenue. This allows CMOs to focus their marketing efforts where they’re most likely to yield strong returns, thus maximizing ROI.
- Track marketing performance: A CMO is responsible for the performance of marketing initiatives. Revenue intelligence provides a real-time, comprehensive overview of marketing performance, tracking metrics like customer acquisition cost (CAC), customer lifetime value (CLV), and the effectiveness of various marketing channels. With such insights, CMOs can adjust strategies promptly, allocate resources more effectively, and identify successful marketing tactics to replicate for future campaigns.
- Improve lead generation and conversion rates: Revenue intelligence can help CMOs analyze data points such as customer behavior, engagement levels, and buying patterns. Then, identify what triggers interest in prospects and what persuades them to purchase. With those insights, CMOs can craft highly targeted marketing campaigns that resonate with their audience, leading to increased lead generation and higher conversion rates.
- Reduce skills gaps: Revenue intelligence can provide insights into where the deficits lie and help CMOs devise targeted upskilling programs. By building personas that detail how different teams need to use data in their roles, CMOs can prioritize training sessions that best enable each team to learn the skills they need to perform their job. This targeted approach to upskilling can help fill the talent gaps in critical areas like revenue operations and account-based selling.
Best practices for implementing revenue intelligence capabilities
1. Develop a data strategy
A robust data strategy is fundamental to harnessing revenue intelligence capabilities. CMOs should define a clear vision and roadmap for data collection, analysis, and utilization.
This strategy should consider data sources such as customer relationship management (CRM), marketing automation, web analytics tools, and external data providers.
2. Build a data-driven culture
A data-driven culture empowers employees at all levels to make informed decisions based on data-driven insights. CMOs should foster a culture that encourages data literacy, curiosity, and experimentation.
Think about how your organizational structure should change to meet new challenges in making data-driven decisions. How should you help current teams keep up with the changes? What new roles are needed — and what new kinds of talents do you need to hire to fill those roles?
3. Build an analytics infrastructure
CMOs must invest in developing a robust analytics infrastructure to extract actionable insights from data. This infrastructure includes tools, technologies, and processes that enable data collection, analysis, visualization, and reporting.
Forrester discovered that 87% of “customer-obsessed” B2B firms would prioritize accelerating their move to digital and analytics infrastructure — and they are backing that commitment up with a budget.
Time to harness the power of data-driven decision-making
The role of the CMO is rapidly evolving and has become increasingly crucial to the success of businesses. As advocates for customers, CMOs must now leverage data analytics to craft effective marketing strategies and deliver measurable ROI. Those who succeed in doing that will gain a competitive edge in today’s complex marketing landscape.
By taking advantage of data-driven decision-making, CMOs can make more informed decisions, prioritize high-value opportunities, track marketing performance with precision, and ultimately drive business growth.
To that end, CMOs should deploy revenue intelligence capabilities within their organizations to truly unlock the full potential of data-driven decision-making. Only by adopting this approach can CMOs assert their roles as strategic leaders and equip their teams with the tools for confident selling.
