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Marketing AI: In-house vs. Outsourcing

When marketers are certain about the goals they want to use AI for, the question remains how to deploy it effectively?

With Artificial Intelligence becoming an industry-wide technology, marketing heads are starting to look for ways to build their marketing mix around it. At this stage, they already have an idea what they are going to use AI for, but the question that still stands is whether to develop Marketing AI internally or to outsource it. 

Welcome to your new department: in-house AI

In order to understand what it means to develop the AI technology in-house, we need to look into the core competencies behind it. 

First of all, it is all about understanding your data. Therefore, you should be looking for a data scientist, who will be tasked with analyzing your customer behavior and marketing performance data. The problem-solving skills of a data scientist requires an understanding of traditional and new data analysis methods to build statistical models or discover patterns in data. 

In plenty of cases relying only on a data scientist alone might not be enough. If your business generates vast amount of data what is spread across multiple sources, you might need to hire a data engineer to prepare the “big data” infrastructure to be analyzed by your data scientist – this covers designing, building and integrating data from various resources, as well as writing complex queries on that and making sure it is easily accessible and optimized for the best performance. 

Moreover, when it comes to understanding your customers, you will need to combine the insights your data scientist generates with at least some expertise in emotional intelligence and neuroscience to make them actionable. This is because you want to understand not only how your customers engage with your campaigns, but also why they behave in a particular way. 

Combining the free competences – data science, data engineering and neuroscience – should provide you the necessary foundation to start building your in-house AI platform. From now on it is going to be all about data labeling, data preparation, data modeling and training your AI so that it could understand your customer data and provide insights that would serve your marketing goals. 

Getting serious. Outsourcing your Marketing AI

It is tough to be a marketer. Being under pressure to meet the business goals, making sure your campaigns deliver, and ensuring your brand’s leadership over the competition are all demanding and stressful tasks. In such an environment, the idea of pouring scarce resources into the development of your own AI platform sounds like a joke – consider all the time that you will waste while your competition will go with an easy to deploy platform-as-a-service solution. 

Truth is, Customer Modeling Platform (CMP) vendors own not only the expertise you need to deploy AI, but also have the capacity to provide you with scalable data modeling solutions in minutes. 

Outsourcing your marketing AI, would also benefit your organization from a few additional perspectives. First of all, CMP vendors such as Genus AI often offer data enrichment services as a part of their offerings. This means that you will not have to look for any data vendors, which can be a trial and error experience before you find something useful. 

Secondly, CMP vendors can also offer some additional functionality that could not be developed in-house. Take content scoring as an example. Vendors like Genus AI are able to score your creatives, ad copy and emails and align different behavioral traits to them, which itself is an insight into what works for your audience.

Did we mention the speed at which you grasp the benefits of an AI vendor? Your marketing team will be adjusting their campaigns in minutes, not weeks and months. 

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