Digital marketing needs the right strategy to leverage AI. Source: Shutterstock

Digital marketing needs the right strategy to leverage AI. Source: Shutterstock

Thinking of marketing with AI? Here are some strategies to consider

BUSINESSES need to grow, and in the digital age, it is important that growth happens quickly to drive impeccable sales results.

Chief marketing officers (CMOs) have since resorted to digital tools and solutions to help them market businesses efficiently and effectively.

Digital marketing has since become such a competitive space. Especially when automation tools have allowed CMOs and marketing teams to launch campaigns quickly and promote higher productivity.

Artificial intelligence (AI), however, makes it possible for marketers to not only automate marketing processes but also analyze varying sets of data to create interoperable connections between them.

Additionally, AI provides meaningful and in-depth insights that help marketers make better decisions. In short, AI is great, and the benefits of leveraging the tool go on and on. However, it is not always the easiest to leverage.

The are several challenges that may limit marketers from truly reaping the benefits of the solution, especially if not tackled earlier on.

So, here are some strategies that can help marketers who are keen to deploy AI in augmenting digital marketing:

# 1 | Building a solid business case

Marketers should never undermine the true importance of having a business case that not only supports the need to deploy AI in digital marketing but also reflects a long-term deployment and integration plan for the technology.

The business should entail the use cases that would be in place, the way the solution will be streamed into marketing processes, the changes in the operational processes once AI is integrated successfully, the kind of new talents that need to be recruited – if ever needed, and lastly, the collaboration that would need to happen between teams to yield measurable results from AI.

Additionally, during this stage, the case should address how the workforce can be prepared to navigate the new technology. In other words, reskilling and training plans should be included to show that the team is truly ready to bring an intelligent machine into the operation.

# 2 | Securing the investment

Businesses are all about taking risks, but it does not mean that organizations will jump into investment opportunities indefinitely. High-level decision-makers still need to be convinced.

CMOs need to be able to appeal to the interests of investors when it comes to AI by showing them how it will help growth, revolutionize reach, and create new opportunities.

On top of all that, marketers need to convey the value of data, in-depth insights and predictive analytics to help investors see how their capital funding would ultimately elevate the business to new highs and secure greater revenues.

# 3 | Measuring the return on investment

Usually, during the use case stages, businesses will have a hard time measuring their return on investment (ROI) and this is mostly because not all forms of AI performance are measurable and quantifiable.

Even if they are quantifiable, it would still take a lot of time to measure against the current standards of KPI that the team is using. Albeit, AI’s output can still be proven to be effective by using AI itself.

Through the advanced analytics capabilities that the tool offers, AI can generate real-time insights and pull data patterns that reflect how its deployment has had an impact on employees’ productivity, engagement, and the team’s overall decision-making abilities.

The key is to always start measuring areas where data is already complete and standardized.

For AI-based marketing to truly take off, marketers need to structure and implement the right strategies beforehand. Having the right strategies truly pay. Especially when results generated add value to the KPIs.