Planning strategies for managers in an AI-powered world.
Mary looked at the calendar as she started her workday. It was already the second week of January, signaling that she and her team only had ten weeks to go until the end of their fiscal year. It was planning time.
What could she do with her team in the next fiscal that would help her company overcome the slump in revenues they had experienced in the previous three quarters? It had to be different. She couldn’t keep spending money on search words, emails, and sales events that didn’t produce revenue. The content for the new product line needed revamping, and sales were carping about the lack of leads. She also knew her management wanted to reduce her staff by 20%. That would mean taking her team down to the bare bones.
What could she do with the tools she had and the AI capabilities that were cropping up in new versions of those tools? What kind of team did she need to ensure that AI was managed effectively, efficiently, and ethically?
Prompt: What are the challenges for marketing ops in 2024?
She started by looking at what her favorite generative AI tool said about the challenges she and other marketing managers faced. She entered the query: “What are the challenges for marketing operations in 2024? Out came a long list. On that list were two challenges that she was very familiar with — data quality and organizational silos. Those, coupled with AI, formed a powerful triad.
These three challenges complicated her options for building, developing, and managing her team. Together with AI advances and a marketing landscape of rapidly changing technology and consumer buying behaviors, they produced a “perfect storm” that could destroy the best of her efforts, even with the most competent support.
Mary began to tackle this new marketing landscape with the end in mind. Her goal for the year was to execute efficiently with a smaller team while generating the MROI she knew the business needed. First, she needed to ensure that her team had the skills and attributes required for this task.
Look for your Tweeners
Having recently attended a conference where she heard data guru Tom Redman talk about “People and Data,” his latest book, she turned to its pages for inspiration. Tom pointed out that this new marketing environment requires a new kind of person. Tom had called the new person a “Tweener,” someone who can make sense of one area’s outputs so that those outputs can be understood and used as inputs for another area. Marketing and sales were two good examples. She already knew she wasn’t doing an excellent job making that connection.
Redman’s words resonated with her: “The problems we have today are not scientific. As far as skills go,” he said, “we need more poets than AI experts.” He went on to explain that poets have a broader view of concepts. “They look at things in many dimensions.” This ability to absorb the bigger picture and make connections is best done by someone Redman called a “Tweener.” Although he sees this person as a connector of business functions and datasets, this “connector” role is also essential for the new marketing operations environment.
But where does Mary start?
Evaluate skills needed
Mary created a list of skills needed to execute next year’s strategy. Here’s a list of those skills in priority order:
- Data Analysis. Knowing how to use data to identify and manage an audience through marketing is vital. This includes knowing the tools, such as Google Analytics and Adobe Analytics, and having skills in using business intelligence tools, such as MS Excel or Power BI, for creating reports and visualizing data.
- Digital Marketing Knowledge. Having individuals on your staff who are familiar with digital marketing trends and platforms, including social media, SEO (search engine optimization), SEM (search engine marketing), PPC (pay-per-click), email marketing, and content marketing is an essential team component.
- Sales and Marketing Automation. Because sales and marketing operate from the same customer data set, marketing operations individuals should be familiar with sales force platforms such as HubSpot, Marketo, and Salesforce. Customer Relationship Management (CRM) tools should also help marketing ops teams track and manage customer information throughout the customer journey.
- Content Creation and Management: Having proficiency in managing content systems such as WordPress, Squarespace, or Drupal is essential for some positions in marketing operations. Basic content creation, graphic design, and video editing skills may also be required.
- Project Management. Skills in project management and the tools that support it can significantly contribute to the team. Understanding not only the tools but also the methodologies, Scrum and Agile, help in efficiently managing marketing campaigns.
- Measurement management. Because marketing must prove itself as a contributor to the business daily, knowledge of marketing measurement is a must. Individuals on the marketing ops team should know A/B testing principles and how they are applied to improve conversion rates, have knowledge of the budgeting process, and know measures associated with MROI (Marketing Return on Investment).
Staff or buy the skills
Mary knows that should she reduce her staff. She will face choices about what skills are essential to her marketing efforts. Some of the skills she may find missing can be bought from outside agencies, but which one should she buy versus grow inside her organization? She lists the pros and cons of maintaining an inside team versus outsourcing each skill required. She does not consider costs but knows that buying some capabilities can be expensive.
Mary evaluates the skills she needs on staff versus those she can buy from outside the organization or transfer to other internal organizations. For example, it could be beneficial to hire an outside agency to do the first follow-up on all inquiries received from online marketing efforts or bring in a company that can quickly apply AI to the marketing data set to improve its quality — dedupe, correct names, email addresses, etc. And what if she could convince finance’s group of analysts to provide her with marketing reports that are only slightly different from those provided to department managers, reports that show what she is spending and where? All these actions would help her.
Here’s her analysis of whether she should keep skills in-house.
| Skill | Pros | Cons |
| Data analysis | Marketing data is clean and connected to sales from a company/customer perspective.Data understanding is complete across the organization; data governance addresses privacy considerations and helps control data usage. Data science and AI skills exist in 10%+ of the marketing organization. Marketing values data as an asset | Marketing data is not as complete as teams need; data is missing some components necessary for selling new products. Understanding of the data process is spotty across marketing teams. Data science and AI skills are dedicated to specific sub-teams and often don’t share data or outputs of data models. Enterprise wants to deploy AI algorithms but doesn’t completely understand the ramifications of AI deployments |
| Digital Marketing Knowledge | The team understands the customer journey and how digital enhances the customer experience. SEM and SEO experts have in-depth product knowledge and are dedicated to specific product lines. The team is adept at managing technical contacts and conversations on social media. | The team has limited experience with measuring customer experience. SEM and SEO experts do not apply their expertise to the overall company presence on the web. The team does not always know when to send contacts and inquiries to sales. |
| Sales and Marketing Automation | The organization has five tools managed by internal experts in each. The team uses machine learning to identify customers with the propensity to buy. | Lead handoffs to sales are messy because the sales teams are constantly changing. The team has not experimented with AI beyond propensity models and could be looking at AI for improving data quality, AI for predicting or forecasting. |
| Content Creation and Management: | Generative AI bolsters content creation and management. | Lack of product knowledge keeps content basic. |
| Project Management: | The team has three certified project managers who lead large projects and campaigns. | The project managers have not been trained to apply AI to planning and scheduling. |
| Measurement management | The team has developed a complete package of measurements that is distributed regularly.The measurement package measures MROI, lead conversations, and other basics. | The team does not help managers understand the numbers. The team does not have good data for measuring customer experience. |
With this list of skills, Mary assesses her team’s attributes. She recognizes that skills are learned and can be taught. They are capabilities that are applied to tasks daily. Attributes, however, are inherent personal qualities that can’t be taught. They make up one’s personality. Although attributes are easy to name, Mary has some issues evaluating them in her team, so she takes each attribute and identifies behaviors she would like to see for each:
Evaluate the attributes of the team
| Attribute | Descriptions | Recognizable Behaviors |
| Open-minded. | A person willing to consider new ideas, perspectives, and experiences without prejudice or bias. | Curious — ask questions. Empathetic — feel others’ pain. Non-judgmental. |
| Rapid learner | Someone who can learn new things rapidly from reading, listening, observing, experimenting, and doing. | Learns new technologies rapidly. Reads widely and often |
| Good listener and question-asker: | One of the most time-honored ways to learn is to ask questions of those who know something you don’t. This attribute combines asking a good question with listening carefully to the answer. | Actively listens. Asks questions for clarification. Questions demonstrate an understanding of the discussion topic. |
| Simplifier | Someone who takes a complex subject, breaks it into bite-sized pieces, and communicates an understandable narrative. | Often clarifies others’ comments in meetings and offers explanations. |
| Precise communicator | Someone who uses data and facts to communicate clearly and objectively. | Presents facts and data about a situation first before making recommendations. |
| Even-tempered Juggler | A person who never lets you see them frustrated keeps a cool head and listens for the compromise position. Combines an even temper with the ability to juggle several projects, programs, or things simultaneously, and everyone benefits. | Often has a crowded schedule and an extensive to-do list but seldom complains. |
With skills and attributes identified, Mary considers how to manage this new Tweener role. Was it a skill or an attribute, or both? Where exactly did the role belong? In one dedicated person or within a skillset that many jobs had? Could she hire a specialist in one area (Customer Experience, for example) but have them collaborate with other areas, such as SEM or Events? Would the work product be as effective or efficient?
These questions led Mary to her next step.
Determine where Tweeners or connectors can best serve the team
The most obvious place to put a Tweener is between sales and marketing, but seeking out a place within marketing to start the experiment seemed more reasonable to Mary. She was looking for someone on the team who could grease the gears and glue together functions, a place to put a Tweener, but within her control.
Mary went back to the three challenges for marketing operations: data, organizational silos, and AI. How could she use AI to help her improve her data and dissolve the walls within her organization?
Mary knew that AI could and would probably take over many marketing operations. There were already bots to manage data movements between applications and tools. Her marketing team could be more efficient now that many of their marketing tools had built-in language creation and editing capabilities. With AI-developed scripts for telemarketers, leads could be generated faster and more efficiently.
Tools with built-in AI could also help manage data quality. Informatica, Ataccama, Data Ladder, Informatica, and Talend already use AI to solve data quality issues. With the improved data quality of her customer data, Mary would be more confident in using that data to build AI models for the company. Those models could help all departments answer their most perplexing questions.
Suddenly, Mary had an idea: What if she created a Tweener role that could help her various marketing operations areas use AI to improve their processes, data, and even their relationships? Her Tweener role would be someone who knew AI but could also help others apply it. She would look for someone with Tweener attributes as well as AI skills. She would assign the Tweener to her lead generation team and have a plan developed that generates a 100% increase in leads for the new year. She decided that the Tweener would work with lead generation and the inside sales teams to ensure that AI contributes to the processes in the right places.
What results to expect
Mary was excited about her possibilities for the new fiscal year. Taking the time to think through what areas of the business were most important to her operations team helped her better understand where the team had gaps. She could use this knowledge to set a training curriculum as well. Since Mary picked a challenge for the team involving AI, team members would also increase their understanding of this technology and what the company gains by applying it. She was looking forward to understanding better how the role of a Tweener could help her bring organizations together and erode silos.
Mary also understood that these changes — adding a Tweener role and tackling lead generation with AI — would create challenges for the team. Change was always hard, and having an open mind about new ideas was imperative. George Bernard Shaw’s quote rang in her ears: “Those who cannot change their minds cannot change anything.”
She knew it would be her challenge to bring change to her organization. Still, if they successfully reached their goal, they would elevate marketing capabilities within the company and begin the process of eroding the silos that had been created. As she closed the day, she thought of what Tom Redman had said about the new roles the business needed. “We need more poets,” those who can think broadly about the topics that will change our world.
The post Building a future-ready marketing operations team appeared first on MarTech.
MarTechAbout the author
Theresa Kushner is passionate about data analysis and how it gets applied to today’s business challenges. For over 25 years she has led companies – like IBM, Cisco Systems, VMware, Dell/EMC – in recognizing, managing, and using the information or data that has exploded exponentially. Using her expertise in journalism, she co-authored two books on data and its use in business: Managing Your Business Data: From Chaos to Confidence (with Maria Villar) and B2B Data-Driven Marketing: Sources, Uses, Results (with Ruth Stevens). Today, as the Data and Analytics practice lead for NTT DATA, Theresa continues to help companies – and their marketing departments — gain value from data and information.
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