How GenAI Bridges the Data Gap Between CMOs and CFOs

Marketing budgets are never entirely safe. While it may seem like pressure is easing as global economic estimates turn slightly sunnier, consumer demand is still getting more expensive to capture and close – which means scrutiny from finance chiefs is as tough as ever.

To keep investment flowing, CMOs need to get better at not only boosting and showing short-term impact, but also illustrating how their efforts create long-term brand interest, in a way that makes sense to CFOs. Or put simply: using the right kind of data to prove real value.

Fortunately, this doesn’t mean highly pressured CMOs must now task themselves with becoming fully fledged data scientists. Thanks to innovations in generative artificial intelligence (GenAI), there is potential for self-serve tools to help them start driving data analysis and reporting that delivers the insights CFOs want to see, and effectively track their ongoing business contribution — without requiring in-depth expertise.

A Rocky Relationship: What’s Behind the Rift?

Rising CFO expectations of marketing effectiveness and accountability aren’t news to CMOs. Amid endlessly turbulent business conditions, they’ve faced an ever-more intense need for in-depth reporting, detailing how each cent is spent and what results activities drive.

But despite this enhanced flow of regular and transparent communications, relations still need work. While recent studies show most CMOs think they’re strongly aligned with finance teams on overarching strategy, over half (52%) now feel increasingly pressured by CFOs to prove their value — up from 45% two years ago.

Looking closer at their biggest reporting challenges, it’s not hard to pinpoint where this disparity stems from: not only are six in 10 (61%) CMOs finding it difficult to demonstrate how they fuel financial outcomes, but just under 30% are also struggling to link their efforts with key business objectives. Clearly, singing from the same strategic song sheet isn’t enough to compensate for the lack of hard data connecting marketing initiatives to the factors finance chiefs (and CEOs) truly care about.

Closing this gap will partly involve closer collaboration on setting performance tracking parameters from the get-go; including dialing down focus on impressive-looking yet empty vanity metrics – such as delivered impressions and ad views – and enhancing emphasis on measures that track bottom-line effects. 

Equally essential, however, will be honing the ability of CMOs to improve data integrity by playing a more active part in leading and generating granular analysis. This is where GenAI can help.

Feeding Ruthless Demand for Short-Term Wins

With growth always vital for CFOs, it’s not necessarily surprising to see it once again topping their priority list for the rest of this year and beyond. What’s interesting, however, is the way finance decision-makers are being encouraged to realize their growth ambitions.

To balance continued investment and cost cutting, industry pundits such as Gartner’s VP of financial research, Marko Horvat, are advising a more “ruthless” approach to resource allocation, with quick and significant capital shifts towards projects that are bolstering business development – and away from those that aren’t. From the CMO perspective, this makes it vital to ensure campaigns avoid the chop by evidencing tangible performance against finance-friendly short-term goals, from online sales to store visits.  

Requesting reports from analysts is the obvious standard route, but there is a real risk that uncompromising CFOs may have switched gear (and spend allocation) before monthly or weekly insights roll in. 

Adding GenAI capabilities to the mix provides a faster and easier option. Built to create new outputs from a host of diverse inputs, advanced deep learning models are taking their next natural step into the world of analytics – powering smart self-service tools that make it simple for users to get the information they need, when they need it, without requiring extensive data expertise.

For instance, innovative GenAI analytics tools are able to work from users’ natural language prompts, run instant SQL queries, pinpoint the most useful data, and share it through accessible visualizations. Moreover, sophisticated tools can also enable users to run broad analysis, with automated data evaluation extracting and summarizing key insights. The core benefits both of these capabilities bring aren’t just about boosting efficiency and saving time for already-pressed analysts; they offer a friction-free way for all users to produce their own top-level reports and start activating data as part of their standard everyday activities. For CMOs, this means they can directly obtain the insights needed to illustrate their impact on current demand capture, instead of waiting on analysts, and use this data to enhance their budget, as well as protect it.

Giving Brand Building Better Data-Powered Clout

Persistently illustrating value, of course, calls for more long-term thinking and justification of the benefits good branding delivers. Many CMOs will be familiar with the often-painful experience of trying to explain how brand building, demand creation, and sustainable business growth are connected. This is especially true of conversations with CFOs, who would rather hear that marketing activities have maximized profits than earned the company a place in consumers’ memory structures. As once quipped by Rory Sutherland, vice chairman at Ogilvy, when trying to explain the importance of brand to leaders outside of the marketing space, “you may as well be talking about the healing power of crystals.” 

Data, and specifically management assisted by GenAI, has the capacity to offer an effective answer to this language problem. At the general reporting level, automated summaries can enable CMOs to act as pattern detectors: reviewing past and present data to identify correlations between brand interactions that simulate high awareness and positive longer-range outcomes such as frequent purchases and brand preference. Or in other words, collecting data that shows the power of keeping their brand front of mind to influence consumer decisions, consistently.

This ability is further heightened by tools that come with flexible transformation options, so that users can define the configuration of whole data sets and procure code to order. Supplying both custom code and instructions for how to use it, such transformation solutions can help users shape, formulate, and apply the right data in whichever way works for them and aligns with their requirements, even without expert skills. 

With near-unlimited scope to speedily shape data in any way they like, CMOs will not only have the ability to determine what does generate demand and what doesn’t, but also spot opportunities to experiment with strategies that no one else is leveraging and potentially gain a distinct competitive advantage.

As ever, technology can’t eradicate CMO problems – but it does set them on the path to being able to solve their issues for themselves.

Stepping out of transactional relationships with CFOs to engage in setting united objectives is a good start. To maintain productive connections, however, marketing leaders need the means to translate what they’re aiming to achieve and the outcomes they fuel into terms finance teams can grasp, and embrace. Improving their data management capabilities is therefore a crucial element of bridging the marketing to finance gap, as well as proving once and for all why branding matters.