AI in martech – Five problems it solves for marketers

30-second summary:

• Personalization combined with AI can help you make the most of all the data you are collecting. It allows you to be more strategic with your tactics that will bring you closer to your objectives.
• Social media posts, mentions, reviews can all contribute to the overall sentiment analysis. AI can help you filter all the feedback to organize the themes you need to focus on.
• Instead of looking at different tools in silos, you are able to build a holistic overview of the customer experience. Relationship management can be easier when combining automated journeys, predictive analytics and segmentation that can improve the customer experience.
• The idea of ‘buy-side AI’ uses AI platforms to focus on the key data that will lead to success. In other words, it can analyze consumer data in real-time to improve your bidding results.
• What’s important is to introduce AI to our marketing stack as the solution to several of our current problems. Despite the challenges, having additional help that goes beyond the human eye can lead to many benefits.

We are experiencing a fast era of digital transformation and Artificial Intelligence (AI) is at the forefront. When it comes to marketing technology (martech), there is a big opportunity to scale your business while keeping up with their latest trends.

It’s not enough to predict that AI will be soon part of your marketing strategy. This is not about the future anymore but about your current strategy and how you can optimize your martech stack to achieve the best results.

This is a good time to explore the pain points that AI can solve for your martech and how to make the most of it.

We are looking at four ways that you can integrate AI in martech to solve recurring marketing problems.

Scaling personalization

Personalization is important when trying to deliver the best customer experience. It’s equally important when you want to improve engagement to turn prospects into customers.

All stages of the funnel have one thing in common. They appreciate a branded message that seems to be useful and relevant to them.

Personalization combined with AI can help you make the most of all the data you are collecting. It allows you to be more strategic with your tactics that will bring you closer to your objectives.

For example, AI can help you analyse the data from your website visitors to tweak your message based on their preferences and habits. It can also help you improve segmentation to send the right message at the right time.

It’s good to remember that AI is not just about collecting and understanding data. It is also about understanding human behavior and how the next actions can affect a purchasing decision.

Improving sentiment analysis

The best way to stay relevant is to listen to your customers and what they want from you. You need to know what they think about your brand and how to interpret their reviews.

Social media posts, mentions, reviews can all contribute to the overall sentiment analysis. AI can help you filter all the feedback to organize the themes you need to focus on.

It can save you time but also help you uncover insights that you might have missed in the past. The fact that you can dive into data historically gives you a significant advantage to adjust your tactics based on your findings.

Whether it’s a complaint or an emerging trend, social listening combined with AI can be a great ally to your strategy.

Saving money integrating martech tools

A common challenge when managing your martech stack is managing the integrations and whether your tools can work together.

This is a common problem in bigger companies with different teams using different tech. When adding new tools to your martech, it is important to explore how they can work together with your existing stack.

For example, CRM and machine learning can help you save money and resources provided that they are integrated.

Instead of looking at different tools in silos, you are able to build a holistic overview of the customer experience. Relationship management can be easier when combining automated journeys, predictive analytics and segmentation that can improve the customer experience.

It’s interesting to note that according to Gartner, marketing automation is the fastest-growing sub segment for CRMs.

Optimizing advertising spend with AI

There are many reasons to involve AI in the management of your advertising spend. As we are increasing our marketing budgets recovering from the initial shock of COVID-19, it is important to be effective with our tactics.

It’s not always easy to attribute a conversion to a specific channel or tactic. Similarly, it is not easy to predict the success of a campaign.

This is where AI can help. Taking aside the human bias and the possibility of an error, machine learning can help you scale your advertising efforts.

For example, it can help you assess the capabilities of different vendors and how they stack up against each other.

It can also help you stay competitive with your campaigns’ performance. The idea of ‘buy-side AI’ uses AI platforms to focus on the key data that will lead to success. In other words, it can analyze consumer data in real-time to improve your bidding results.

There is a learning process involving AI that can maximize your success while reducing the budget you are wasting with no luck.

Using AI as the first step towards business transformation

Adding AI to the marketing mix can help us think of the bigger picture. It’s not just about adding a chatbot to our customer service or integrating machine learning.

What’s important is to introduce AI to our marketing stack as the solution to several of our current problems. Despite the challenges, having additional help that goes beyond the human eye can lead to many benefits.

It’s an opportunity to use data in a way that will make customer acquisition, up-selling, churn prediction, and retention easier.

Thus, it’s useful to explore AI both for the short and long term wins. Look at the technology that will optimize your current struggles.

How can you make the most of what you have with only a few additions? What are the key problems you are trying to solve?

What’s next for AI in martech?

AI is still at an early stage compared to its potential. That’s why it’s the perfect time to explore how you can integrate it into your current strategy.

According to McKinsey & Company, there will be a big performance gap by 2030 between those who are fully adopting AI technologies and those who are still behind. More specifically, AI front-runners could potentially double their cash flow by 20% by 2020.

Thus, it’s time now to bring together the tools and tactics that will help you maintain your competitive advantage over the next few years.

Start with your current team and tools and research on what you need to change to be ready for the use of AI in a more strategic way for your business.

source https://www.clickz.com/ai-in-martech-five-problems-it-solves-for-marketers/261778/