If you want a snapshot of what every marketer is facing today up and down the marketing landscape, Joe Davy says you don’t have to go much further than the “Gartner 2023 CMO Spend and Strategy Survey.” Among the number of statistics that jump off the page of the report, the one that shows 75% of today’s chief marketing officers (CMOs) are facing increased pressure to “do more with less” to deliver profitable growth is an eye catcher. Because of this, 86% say they must continually make significant changes to how the marketing function works to achieve sustainable results.

Davy, co-founder and CEO of Banzai, an interactive content platform that teaches real-world finance, says the continual explosion and complexity of data and its importance on everything marketers do can be overwhelming at times. This is especially true in finding places where it can help with that whole “do more with less” mantra.

At Banzai, Davy and his team prioritize making integrations between its products and services as seamless as possible, including the investments they make in securing more platforms. “Engagement analytics are one of the biggest new advances we’re seeing. Essentially, marketers want to understand what’s happening between lead generation and conversion. The kinds of content prospects are looking at and how they’re interacting with that content are indicators of which prospects are hot, which need more attention, and what kinds of content and channels deserve more investment.”

When it comes to marketing, cutting-edge technologies like AI are making it possible for marketers to analyze the qualitative side of their events, programs and data at scale. Where traditional analytics might tell marketers how many leads were produced by each campaign, new AI libraries can lend insight into what those campaigns have in common, including which campaigns are likely to appeal to which leads, and what content is most relevant for which audiences at industry events.

A number of new AI tools are making it simpler to enhance the decision-making processes in the marketing supply chain, including things like chatbots, and leveraging data-driven insights and automation for optimization. These technological advancements can significantly contribute to cost savings in the marketing supply chain by streamlining processes, improving efficiency and reducing waste.

It is why In-Shape Family Fitness, which has 63 locations in California, relies on what the next generation of automation can do in the marketing supply chain. CMO Kris Mulkey says the benefits abound. For example, automation tools and software are able to streamline routine and repetitive tasks for data entry, email marketing and social media posting reducing the labor expense, while data analytics provides valuable insights—a scenario that enables her and her team to allocate resources more effectively, reducing wasted spending.

In addition, ecommerce and online sales platforms allow the In-Shape team to streamline the sales process and reduce overhead in its clubs and support centers. “We have a variety of tools and technologies that we use to collect data on our members and prospects to help drive acquisition and engagement,” says Mulkey, who along with the health and fitness world, has worked with marketing teams in retail, automotive, wine and spirits, grocery, restaurant chains, and home décor. “There are multiple sources that we collect data from, including websites, email campaigns, in-club check-in activities, class reservations, sales conversions, etc.”

Mulkey says the data influences new programs In-Shape develops, promos it launches and amenities it adds to its locations. “The ease and ability to A/B test campaigns and segments based on audience behavior and demographics is driving conversion optimization. For the website, for example, we have a tool that shows us the complete member journey and highlights pain points in the buying process. Without the tool and data, we wouldn’t fully understand the member journey and areas we should focus on.”

More than anything, Mulkey says that the traditional marketing supply chain continues to evolve in response to changes in technology, consumer behavior and market dynamics. “One of the biggest changes is the shift from traditional, print-based marketing to digital marketing. The evolution has led to the development of entirely new channels, i.e., social media, email, search, online, reviews, influencers, location-based maps, etc.”

Take AI-powered chatbots, which can provide immediate responses to customer inquiries, and help improve customer service efficiency and availability. The chatbots are able to handle routine queries and direct more complex issues to human agents. AI also is being used to help with supply chain optimization by helping manage inventory levels, demand forecasting and logistics. This ensures products are available when and where they are needed, which can help reduce costs and improve customer satisfaction.

Overall, AI is revolutionizing the marketing supply chain by enabling marketers to make more informed, data-driven decisions. Ultimately, marketers believe this will lead to more effective and efficient engagements. “Every step you remove in the supply chain through automation represents a reduced cost,” Banzai’s Davy says. “For example, every time a direct integration is built between two platforms, time is saved for a human to download, collate and manually transfer data.”

As marketers continue to marry what they need with what the market demands, the strategies for the marketing supply chain will continue to evolve—and the players on all sides will adapt to the changes.

Accurate Demand Forecasting
Artificial Intelligence and machine learning algorithms can analyze vast amounts of historical data, external factors and customer behavior to predict future demand with greater accuracy. This enables marketers to plan their inventory levels.

Improved Supply Chain Visibility
Machine learning algorithms can analyze data from multiple sources, including supplier performance, logistics and production processes, to identify bottlenecks and optimize supply chain efficiency.

Predictive Maintenance
Often overlooked, predictive maintenance algorithms can analyze sensor data to predict when equipment repairs and updates are needed. By identifying these before they occur, brands can reduce downtime, improve equipment reliability and reduce maintenance costs.

Source: Arkieva