Increase Marketing Team Productivity - A Case Study

A new Marketing Department model is needed, designed with Generative AI and Machine Learning at the centre of all thinking, processes, and outcomes. Today’s technology solutions quickly become yesterday’s solutions. Still, by introducing and adopting early-stage AI development programs during CV19, and subsequently expanding them, it was possible to transform the marketing function of a global B2B business in its pivot to become a B2B2C business. This drove commercial success contributing to an estimated US$ 3.7M additional revenue in the new B2C Division, a +12% increase in Leads for the Enterprise Division, and an overall increase in marketing assets for two business divisions by more than 30% - out-indexing the forecast productivity gain.

Legacy Operating Models Challenged by Diversification

Marketing Departments have many different structures; global, regional, and local. In-house outsourced, and hybrid models with freelance or specialist skills on a case-by-case basis. Market expansion can normally be addressed by adding headcount or selecting new suppliers provided the commercial numbers add up.

However, in this case study the In-house Marketing Department had very limited internal resources, and a supplier roster poorly matched to the expanded business requirement of launching into a new marketplace simultaneously across multiple geographies. Without a headcount increase, a fresh approach was required to concurrently support the existing B2B business and launch the new B2C one.

Design Principles for an AI-centric Marketing Department

Starting with a capability and capacity audit to identify requirements critical to business success, and extending this to a supplier audit produced a SWOT analysis of what the business required to succeed. Re-imagining the marketing function with curiosity and an open mind led to stimulating discussions with major and emerging players in the market.

Capacity & Capability

Two clear design principles informed the design of the new operating model for the Marketing Department model. The first, improve the capability to plan strategic activities such as product launches; the second, increase the capacity to manage the very different cadence and volume of assets for B2B and B2C marketplaces. From an internal Department perspective, there was a clear requirement to remove systemic friction caused by legacy IT systems, outmoded workflow management software compounded by an ambiguous approval process, and inconsistent ownership of delivery

More Reach, More Effectiveness

Harmonised and automated workflows replaced manual ones optimising the consistency of messaging, and a range of new content creation tools generated a wider variety of assets in more formats than had previously been feasible. SEO, SEM, CRM, and Chat were managed via Machine-Learning workflows and rigorous cohort analysis ensuring marketing communication assets became more relevant and impactful in line with improved speed to market. A new distribution-led content development framework guided the strategic planning process, realigned criteria for the allocation of creative and production resources, and sharpened measurement of commercial outcomes.

Thought Leadership Through Innovation

The Marketing Department gained prominence as a strategic thought leader in the business elevating the function from a service department to a strategic driver of business growth. Finance, Sales, Operations, and Customer Service functions all benefitted. As the migration to a data-led culture began to flow through the business, the highly siloed operating mentality across internal departments was replaced by more informed decision-making and improved allocation of resources. The business became more forward-thinking, tech-savvy, and open to change. Brand equity scores improved, market penetration expanded and as an employer brand, the company's reputation improved helping to attract top talent, better partners, and customers who value innovation.

Closing Thoughts

Generative AI and Machine Learning topics inspired a lot of media coverage in 2024 yet companies still seem undecided where the remit for AI lies. Is it the CTO, CFO, or the CMO or a.n.other functional role? The reality is that the topic should be in every C-Suite remit, regularly assessed and its adoption constantly monitored and if necessary re-prioritised. If not, too much time can be spent lobbying for its integration. Big trends to watch for in 2025 will be how AI could dramatically reshape the cost base for the US federal government, its expanding role for media owners/distributors such as the BBC, and how listed companies will continue to look to make 30% productivity savings from their marketing and advertising agencies.

Across all sectors, CEOs will without doubt be alert to the productivity gains offered by AI given turbulence in many global markets and the increased employer costs due to tax changes.

Image credit: EMP Monitor