As digital advertising continues to grow YoY and market leaders such as Apple and Google update their privacy policies, companies that run digital will need to adapt. This will be further emphasised by the death of the 3rd party cookie by 2022 and as a consequence, adtech will need to be rebuilt and reinstalled.
This is where the importance of a digital marketing engineering team comes into play, as datasets can now be in the billions and even trillions of records. Having caught up with Robert Webster (Founder of Canton Marketing Solutions), he reminisced that back in 2001, a large marketing dataset would fit on a very basic excel spreadsheet. Now with the ability to analyse granular log level data, a different set of skills are required, such as cloud computing, API’s, dashboarding and AI.
This increased demand for technology skills coupled with upcoming industry changes will mean additional talent will be required in the near future.
What is the role of a Digital Marketing Engineering Team?
As mentioned in a previous article, their role is to help Digital Marketing teams:
- Effectively set up and integrate their technology stack
- Improve workflow and optimisation automation
- Improve reporting automation and visualisation
- Analyse AI and Big Data outputs
What are the key skill sets required?
1. The Solution Architect
The Solution Architect will have experience across multiple technology platforms as well as experience in translating business requirements to technology requirements. They will help marketing teams to:
- Develop architecture diagrams that illustrate the flow of data across the business or marketing department
- Keep on top of emerging technologies and help the business identify the best tools for the job e.g. creating a matrix to determine the tool of choice for data ingestion for reporting, such as Funnel, Supermetrics, Domo or ad-hoc API scripts
- Liaise between the marketing team and the development team to ensure requirements are being met
- Troubleshoot issues with installed adtech and reduce platform discrepancies (the plague of adtech stacks)
2. The Coder
- Set up and connect to marketing platform API’s to automatically pull performance data e.g. Google Analytics, Facebook, Flashtalking, Amazon DSP
- Develop Google Adwords scripts that automate common procedures or interact with external data
- Further understand and develop their site, ultimately improving SEO performance as well as conversion rates
3. The DBA
The database analyst will use their data modelling, database design and SQL experience to help marketing teams:
- Develop physical, logical and conceptual data models
- Create and manage data schemas
- Write procedural queries to automate tasks
- Maintain data security, scalability and speed of execution
- Provide the BI Analyst with clean datasets from which they can gather insights
- Perform ad-hoc analysis on internal or client datasets to identify issues and improve performance e.g. match rates between systems
They will be proficient in SQL as well as procedural languages, such as:
4. The Cloud Guru
The Cloud Guru will have experience working across multiple enterprise cloud platforms like Amazon Web Services, Google Cloud Platform and Microsoft Azure. They will help marketing teams to:
- Develop, build and maintain a cloud data warehouse, working in tandem with the DBA. Data can then be fed in from multiple sources e.g. csv, google sheets, excel files or api connections
- Build clear data pipelines that can be used for marketing reporting e.g. Utilising Google Cloud Platform's Pub/Sub, Cloud Scheduler, Cloud Functions and BigQuery tools to help automate data ingestion from source platform (via APIs) to BigQuery and finally to a Business Intelligence tool of choice (e.g. Google Data Studio, PowerBI, Tableau etc)
- Grow their understanding and working knowledge of the data science/machine learning as a service (MLaaS) capabilities that the latest cloud platforms can offer, such as, Amazon SageMaker, Azure ML or Google Cloud AutoML
5. The Business Intelligence Analyst
The BI Analyst will have a strong background in data analysis, BI tools as well as a working knowledge of SQL. They will help marketing teams to:
- Visualise marketing data, allowing for quick and easy analysis and insight gathering
- Alleviate pressure on the marketing team as they will no longer have to produce ad-hoc reports in tools such as excel
- Investigate any data discrepancies or anomalies and feed these back to the marketing teams, who can then fix at source
Where to start?
For a number of reasons, these skill sets are often difficult for marketing teams to find and hire:
- Most do not have a background in digital marketing
- Within larger organisations, they normally sit within development teams and are therefore not a dedicated resource
- Within smaller organisations, they can be expensive to hire and may not be required long term
However, there are a number of different options available to marketing teams to work around these issues:
- Organisations can hire expert consultants that have the context of seeing these issues before with other advertisers. They will also have both a marketing and technology background
- Larger organisations can hire dedicated marketing engineers that also know media
- Smaller organisations can bring in expert consultants on a short term basis to help lay the foundations
With Apple's iOS 14 privacy move and Google’s phasing out of the third-party cookie, organisations will need to redefine their digital architecture, adtech roles and responsibilities as well as grow their digital marketing engineering teams sooner rather than later. The roles described throughout this article will help shed a light on the key skill sets required in order to achieve this.
If you or anyone you know feels that assistance is required, please feel free to get in touch with Canton as we have had the pleasure of working with a number of small to large organisations to tackle these problems and help them prepare for the future.