Marketing and information technology are increasingly becoming integrated. Experts say that as artificial intelligence is increasingly being used and ad targeting is relying more on automation, combining the two departments or drawing a strong link from one to the other within a brand or an agency could become commonplace. Lytics, a leading customer data platform (CDP), Thursday released the findings from a survey of 250 senior marketers and IT leaders. The survey, Marketing and IT: The Strategic Partnership, found that 81% of marketers believe IT teams will become increasingly involved in marketing efforts during the next five years. Jascha Kaykas-Wolff, president, Lytics, believes marketers must work with IT for safeguards on consumer privacy and to comply with increasing governmental regulations. With that change comes an expectation from both departments on accountability for marketing return on investments (ROIs).

The use of AI in B2B marketing can help businesses identify their ideal prospects, convert them into leads, and seamlessly guide them through the sales funnel in a more expedited and efficient manner than is allowed by traditional processes. AI has already become an integral part of modern-day marketing. However, the greatest leaps of AI in marketing have been largely limited to Business-To-Consumer (B2C) operations. That's because AI's basic ability to automate repetitive tasks has found many applications in B2C endeavors, where scale is the biggest challenge. Be it automated mass emailer distribution or chatbot-based customer service, the uses of AI are largely dependent on its ability to handle a high volume and fairly low variety of tasks.

Driven by customer demand, marketers are looking beyond acquisition and vanity metrics to full-funnel marketing that tracks Lifetime Customer Value (LTV). With the help of AI, they're also freeing up time to think more strategically. Let's start with what the customer wants In the Fourth Industrial Revolution, customers are now in control. They're always connected, they have options and they can vote with their feet if they're unhappy. Salesforce's recent State of the Connected Customer research shows that 57% of customers have stopped buying from a company because a competitor provided a better experience.

The new partnership will help marketing and sales teams maximize the ROI on their event marketing spend. With SummitSync's conference and trade show intelligence paired with automated lead engagement through Conversica's AI Assistants, brands will be able to drive higher quality sales meetings and convert more prospects to customers like never before. For event marketers, the joint solution automates many of the time-consuming tasks associated with event execution such as pre-booking meetings at events, coordinating on-site demos with salespeople and capturing follow-up requests for information. It frees event marketers to focus on delivering an outstanding end-to-end experience. "Conversica is an ideal partner for us because we serve a similar customer base and our combined technologies complement each other and increase the value we deliver," said Al Torres, president and co-founder at SummitSync.

Implementation of artificial intelligence (AI) or machine learning is currently relatively low – but in the next three years, top marketers expect to integrate these technologies to a greater degree, per the latest report [pdf] from The CMO Survey. Among respondents who are currently using AI, some 56.5% said they were using it for content personalization. While personalization has proven to be effective for marketing efforts, it is also time-consuming and difficult to do at scale. AI may be able to alleviate these issues. Another 56.5% of companies employing AI employ the technology for predictive analytics for customer insights.

Machine learning is revolutionising how companies are capitalising on Big Data to develop their marketing strategies. While the term encompasses a broad spectrum of technologies and approaches, in a marketing context it can be used to improve targeting, response rates and overall marketing ROI. To put it simply, machine learning involves the automated analysis of large volumes of data – such as consumer spending habits and purchasing behaviour, as well as demographic information – and using a mathematical algorithm and a computer to identify patterns and trends. The algorithm then tests predictions based on historical campaign data and learns from the predictions it gets right. With time, these algorithms become highly accurate as more data from campaign results is added.