How to improve your marketing performance combining Human and Artificial Intelligence

The rapid evolution of the MarTech ecosystem implies new challenges when it comes to building the best possible infrastructure.

Regardless of their size, Companies can connect different solutions together, finding the ideal mix for their business objectives, thanks to AI and Machine Learning solutions, along with the rise of the No-Code movement.

During a workshop of the last MarTech Summit by IAB Italy, ByTek - the MarTech Company of Datrix - illustrated how to design an effective MarTech stack and how the role of people is still fundamental for any initiative in order to succeed.

2022 MarTech trends and CMO perception

According to a recent research by Gartner, the use of MarTech remains stable even in a more and more uncertain context. 68% of MarTech Industry leaders and early adopters of this approach are facing significant challenges utilizing their stacks full breadth of capabilities.

In the pandemic scenario, the need to expand the marketing technology stack has become crucial, but global CMOs are struggling to make progress in this regard, also due to scaled budgets not aligned with challenging objectives. How can you do better with less?

Companies are willing to improve their company equipment: + 41% for MarTech strategy, + 50% for business intelligence.

Marketers focus on a strong shift in perspective: it no longer prevails the best-of-breed approach (as before 2020), but there is a clear preference for integrated and holistic solutions, all-in-one suites, which can centralize data, its management and operability, providing a holistic and complete vision.

How to design an effective MarTech Stack: the role of AI

Modern companies must base their growth strategy on data.

There are 4 steps:

1. Data Collection, to unify a huge and chaotic amount of data;
2. Data Governance, to structure and order the data lake;
3. Data Enrichment, to provide useful insights through interpretation;
4. Data Activation, to make these insights actionable, to turn them into strategic marketing decisions’ pillars.

These 4 phases correspond to specific technologies and tools, including:

1. the use of pixels, forms, beacons and IOT for Data Collection;
2. CRM, Data Lake, CDP and Analytics for Data Governance;
3. CRM Modeling and Customer Intelligence for Data Enrichment,;
4. ADV Audiences, E-mail Marketing and Automation activities for Data Activation.

Artificial Intelligence, or Augmented Intelligence, plays a key role in each of these phases and applications. Therefore, even if standard algorithms are already widely available, we need to start using AI with a different approach to manage larger amounts of data, rather than immediately focusing on predictions.

Today, many companies experience difficulties in starting immediately with a highly complex and completely custom project, and eventually they find themselves unable to carry it out and obtain the value they need.

In this sense, AI & Machine Learning are real enablers, since they can:

• manage huge amounts of data;
• transform data into insights;
• enrich the data with trends and alerts;
• effectively monitor anomalies.

Therefore, we think of AI and ML as integrated with Data Governance (thanks to Anomaly Detection solutions), with Data Enrichment (through Clustering and Trend Detection actions), and with Data Activation (with Triggering and Sales Empowerment).

The Human Factor: MarTech is not all about AI

According to Massimo Chiriatti, Lenovo’s Chief Technical & Innovation Officer, ex-IBM and author of the book “Artificial Inconscience”:

“The machine anticipates and runs many ways at great speed, but it must wait for us until we decide whether and how we want to follow it.

Because the machine doesn’t know it could be wrong and it doesn’t know how to regret it, it doesn’t even know why it’s doing this.”

This is an excellent starting point for understanding how Human Empowerment - the human factor - remains key to every decision and marketing activity; and how AI is an incredible tool to enhance human intelligence, but certainly not to replace it.

In fact, only human intelligence is able to:

• Convert company values ​​into goals and objectives into tactics and KPIs

Corporate values ​​are the foundation of every strategy and tactic, be it marketing, sales or IT. Often the greatest challenge is understanding how to transform a principle into a goal, and eventually how to turn the goal into the best tactics to achieve it and the numerical KPI to measure its success.

No technology is (yet) able to manage this process, because it involves conscience and ethical values. A machine will aim for efficiency, not wondering if the actions it pursues are in line with corporate ethics. Furthermore, Artificial Intelligence will need different factors ​​to train the algorithm, and once again it is up to people’s conscience what can be defined as a success and what is in fact a failure.

• Design the best stack and govern it on the basis of digital maturity and the ability to apply it, as well as ethics

Always starting from company values ​​and principles, the role of people is to govern technology, especially when it’s complex, according to company needs and objectives. In this process there are not only economic implications, but also moral and strategic ones. Deciding whether to entrust the collection of customer data to one vendor rather than another involves conscientious choices, which to this date only a human being is able to make correctly. Machines do not have, and perhaps never will, sufficient understanding and decision-making autonomy to carry out a solution fully compliant with the company mission, even when making a certain choice leads to lower results than another.

• Transform data into insights thanks to the interpretation of trends

Machines are extraordinarily capable of processing huge amounts of information in a very short time, without making mistakes. It would be crazy to have human beings do this process, who are by nature slower and more imprecise. But lately we are realizing that only an insight-driven approach can truly guarantee the growth of a company, not a mere data-driven approach.

We are talking about the ability to extract meaning and ideas from the amount of data and trends that the machines are able to manage and produce. Here too, deciding what is truly valuable to us and what isn’t. To truly benefit from the technological stack and the AI algorithms implemented, choosing and interpreting an insight is a fundamental process, if not the most important, and it is still exquisitely human.

• Operate the tools through empathy

We believe that the MarTech stack and algorithms are extremely powerful tools at the service of people, to increase human and marketing skills.

The activation of these tools involves creative empathy, otherwise we will not be able to communicate effectively with our audience, choosing colors, texts, tone of voice, in line both with our business goals and with values ​​and corporate objectives.

This does not mean we should not take advantage of the many processes based on A / B testing and retrospective data analysis, which also support creative choices. However, the experiments conceived and designed by people for other people remain highly human, as well as the success criteria, which determine the result of the experiment.

Hermeneutic ability, creativity and feelings are not reproducible by machines. They are human pluses, the supreme value added by our brain, even in the professional field.