According to a recent Merkle Customer Engagement report, MarTech is now the single most significant area of investment for marketing resources, with CMOs reportedly spending 29% of their budgets on MarTech in 2018. And if CMOs had extra money in their budgets they would spend even more on MarTech as shown in the chart below.
So, what’s driving the growth in MarTech? The ability to process large, disparate volumes of data and glean deeper and deeper customer insights is whetting the appetites of marketers in all industries. Right now, the main ingredients are AI and machine learning.
AI has exploded in recent years, as machine-learning algorithms have made use of the huge increases in computing power providing users with the ability to rapidly query large volumes of data. AI in MarTech is growing as it can offer detailed insight at every touchpoint along the customer journey from media consumption to purchase. As it evolves, the hope is that AI may even uncover hidden opportunities by connecting the dots humans might miss.
AI’s ability to collect and predict data about customer preferences allow marketers to understand and target their customer base with a laser focus never dreamed of until recently. In theory, it will lead to better targeting, much higher response rates and return on marketing and advertising spending should increase accordingly.
AI will help in both lead nurturing and building customer loyalty as it provides a better predictor of customer reactions to competitive/market actions. Marketers are excited because AI insights can help them be more effective at every customer touchpoint and every stage of the customer lifecycle.
For most marketers, content is king. Whether it’s on their website, advertising or any interaction with their customer. With AI, content recommendations can be automated and AI insight can help create a more personalized experience.
Keyword accuracy. Learning is the heart of developing better keywords, particularly long tail keywords. AI and machine learning will rapidly accelerate the process of finding the most effective long tail keywords that generate a higher ranking on search engines.
A/B testing can be effective, but also time-consuming. With AI and machine learning, the process can be greatly accelerated. For example, Adobe Target uses AI and machine learning to produce detailed and constant testing on a massive scale. It can track a customer’s overall experience down to the color of the button they click. It quickly measures how customers respond and new testing experiences can be refined and retested in short order. Real time results can be instantly used to meet customer’s evolving needs.
Other AI & machine learning opportunities:
- The rise of 5G will present more opportunities to interact with customers via AR and VR.
- Voice searches can be more quickly analyzed and leveraged.
- Video, the most popular form of consumed content can be better evaluated.
- Predictive modeling will be more accurate.
- Integration with social media. AI can generate immediate responses and lower the cost of related customer service.
But even with its seemingly unlimited potential, only 30% of companies are expected to use AI in their sales processes by 2020 according to Gartner. Companies who can successfully adopt AI sooner rather than later will have a clear competitive edge.
Marketers have a healthy appetite for deeper, more accurate and faster customer insights. It’s a never-ending, insatiable desire to have the ability to deliver the right message, to the right individual, at exactly the right time. With the help of AI and machine learning, MarTech will soon help marketers rely on more their heads and less on their gut.