The design of MarketingOps teams
by Jan Hendrik Fleury on Mar 25, 2022 8:54:48 AM
Marketing is currently undergoing a transformation to put the customer first at scale. This is necessary because the processes run 24/7. Operational, creative, brand, analytics, and data engineering teams work together to develop and maintain all processes and tasks.
With MarketingOps you have the opportunity to make marketing and support functions more effective by setting performance expectations and measuring and analyzing results. To get that marketing machine up and running, you need a MarketingOps roadmap so that you implement MarketingOps in your organization in the right way. You can read how the MarketingOps team is part of the roadmap and how you can implement this team in the third part of this series.
The third part is about setting up MarketingOps teams.
Connection to the strategic goals
The strategic MarketingOps roadmap focuses on long-term results that are in line with the overall mission and vision of the organization. First of all, you define in the MarketingOps roadmap what you want the MarketingOps function to achieve for the Marketing Department and the stakeholders of the organization. In addition, you outline the current situation and the desired situation, and how you will achieve it.
The following steps will help you shape your MarketingOps roadmap:
- Draw up requirements that are necessary to realize the desired situation. Focus on the processes, data, systems, and people that are required for this.
- Establish the time frame within which the result must be achieved. Divide the time frame into individual milestones in chronological order.
- Determine how the performance resulting from the implementation of the roadmap will be reported and communicated.
- Create a business case and determine the business outcomes that will impact Marketing.
You then use the roadmap to determine which infrastructure, data, analytics, performance indicators, data collection, and analysis and reporting processes are required.
Develop a data strategy
Ask any MarketingOps professional what the biggest problem they encounter in their job is and they'll tell you it's "bad and missing data". Poor quality data is the source of problems. From embarrassing email blunders to campaign reporting no one seems to agree on. Still, it's not crazy. Most companies use a variety of SaaS applications, and that number is expected to continue to grow. Solving data problems ad hoc by quickly putting a plaster on it is no longer sufficient.
During Emerce Digital Marketing Live on June 2, I will present DDMA about the organizational and technical elements of a first-party data strategy from my role at the Data-Driven Marketing Association.
In the second article, we saw that data can provide insight into important marketing issues. An example use case from practice that you can get more of a grip on with a good data strategy is the following:
- “What is the return on investment on my email marketing campaign? I work in a B2B environment and the sales cycle often takes months. I have no idea whether these email campaigns contribute to the sales figures”
- “What is the growth potential of my sales region? Are there enough leads that comply with the GDPR and do it make sense to put my energy into it?
- “I organized a webinar with a third party. How many of my visitors are potential leads and how can they be automatically redirected to sales?”
The reason that the solution is often not readily available for these use cases is the fact that a lot of data is stored in separate systems that are not integrated with each other. These tools have their own (separate) reporting options, and their own data model and are limited to the data present in that specific tool. The result is a fragmented image. I recommend making the data centrally accessible and transforming it (making it usable) into a 'central data model'. Public cloud technology such as Google Cloud or AWS are platforms that are well suited for this. On LinkedIn, there is an article by me about 3 best practices with Google Cloud to integrate data, analytics, and activation into a so-called unified marketing stack also called the Customer Data platform.
That's why you need a data strategy that prevents this. Although the content of every data strategy is of course different, it consists of at least the following components:
Your data strategy should strengthen and support the overall business strategy, and the operational processes that are used. Set clear and measurable objectives related to the data strategy.
Roles and Responsibilities
In a data strategy, it is important to pay attention to organizational roles by documenting who does what with the data. This improves collaboration and communication and prevents duplication of work. Not everyone in an organization uses data in the same way and their roles in data collection, management, and analysis will differ.
The roles below will normally apply and execute the data strategy:
- Data engineers are responsible for building an efficient and reliable data architecture.
- Data scientists, work with the data that the pipeline produces
- Data analysts, they are specialized in analyzing and interpreting data.
- Business managers, help manage data operations and analyze business reports generated by data.
When defining roles, it is important that everyone who uses data, in whatever way, is included. For example, an account manager who stores and edits customer information has a role in data collection, and a sales manager may need that same data for analysis to plan the next marketing campaign.
If an organization uses multiple data sets, it is also important that the data strategy establishes who is the “owner” of each data source. By “owner” it meant the person who is responsible for the storage and security of the various datasets.
The data architecture consists of tools and processes that enable you to work with and analyze data. Infrastructure and software components are part of the data architecture. In order to be able to analyze your data, it is important that it is stored in a central place and that data is retrievable, such as in a data warehouse or a data lake. You also want to integrate and transform the data into a format that is suitable for analysis.
The basis for effective data management is data governance. Processes and responsibilities have been established to guarantee the quality and security of the data. The policy describes how data should be handled.
The Design of MarketingOps teams
Depending on the complexity and size of a company, a team can range from one to a handful of people.
A smaller MarketingOps team can only consist of a Marketing Operations Manager. Larger teams may include data analysts, marketing technology roles, and specialists.
Your team will vary based on size, complexity, and type of organization. For example, an e-commerce company has different specialists in its core team than a company that provides services. You can of course also hire one or more of the specialists externally.
A MarketingOps team is normally led by a Marketing Operations Manager. This manager usually reports to the Marketing VP. Among the managers are other team leaders or specialists.
These employees are involved in marketing processes, technology, and data analysis. Make sure you identify the people you will need from start to finish of the project and team up with them.
Provide a clear division of roles and record the stumbling blocks in a clear plan. Do you need specific technology to do your job well? Are all colleagues involved in this new way of working and willing to embrace Agile methods? Once you've got this in order, it's time to get started on your first project. Start small and think about which departments you will need to complete the project. Provide shared responsibility.
The role of the MarketingOps Manager
You now know what MarketingOps is and how to put together a Marketing Ops team. But what are the daily activities of the MarketingOps manager and what is her/his role within the process? A MarketingOps manager extracts insights from data collected during day-to-day work. They view dashboards and use data analytics to assess the performance of the marketing strategy. They ensure that data is accurate and that systems are aligned, linked, and integrated. This creates a data-driven and integral overview of the marketing efforts and adjustments can be made in time. Depending on the results, they may instruct to change or update configurations for CRM software and marketing automation platforms.
MarketingOps helps your employees to collaborate more effectively across different 'departments'. The MarketingOps Manager maintains an overview of the project and makes adjustments based on performance. I recommend in most situations start small and make clear agreements about tasks and responsibilities. Get together regularly and briefly discuss what everyone is doing and how the others can help each other. In this way, you create involvement and a collective sense of responsibility.
Crystalloids helps companies improve their customer experiences and build marketing technology. Founded in 2006 in the Netherlands, Crystalloids creates crystal-clear solutions that turn customer data into information and knowledge into wisdom. As a leading Google Cloud Partner, Crystalloids combines experience in software development, data science, and marketing, making them one of a kind IT company. Using the Agile approach, Crystalloids ensures that use cases show immediate value to their clients and make their job focus more on decision making and less on programming.
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