Credit by: Nick Ismail
Artificial intelligence in marketing is part of a long list of traditional departments being shaken up by technology, in this case, AI. Technology is not only disrupting entire industries, but it is also changing the dynamics of departments.
Think about how radical the change has been in advertising and marketing, portrayed in the 1960s by the hit TV show, Mad Men, compared to today, for example. The landscape has shifted from the physical to the digital and marketing, like many other disciplines, has had to adapt to this shift; reaching customers via different platforms with different means. The message has also changed and in today’s world, personalization is king.
Below, three industry experts examine how; AI is disrupting marketing, in both B2B and B2C settings, changing traditional roles and functions, and championing collaboration.
How can AI and ML automate the personalization process?
AI/ML are well suited to deliver personalization. In truth, personalization at scale is impossible without AI/ML – by nature, these capabilities curate specific needs and wants for each individual target. AI/ML can determine a recommended offer as a starting point and through learning, cycles can improve the personalized offer. The path to success for each target will vary and the result is a unique offer; as the machine learns, the best offer can be achieved for each individual target.
How can deep learning solutions enable marketers to access big data, for the most targeted marketing possible?
Learning systems improve as the quantity and quality of data increases. These systems examine events and work to understand causality. Furthermore, learning systems are trained to predict future events based on the signals found within big data. Learning systems that are built to scale are designed to handle massive amounts of data and can leverage that data to understand insights and causality that most human analysts cannot or will not see. The most intimate insights are often those that require complex connections across several types of data. These complex connections represent opportunities to communicate and extend offers for highly successful targeted marketing.
How is AI being used by organizations to align sales and marketing target the same accounts?
The alignment of sales and marketing teams is critical to ensure a successful account-based marketing strategy. A recent report from Sirius Decisions found that organizations with alignment between sales and marketing operations achieves 24% faster growth and 27% faster profit growth.
Sales and marketing teams are now able to get real-time insights into customer’s behavioural patterns through technologies such as AI and machine learning. Getting to know the customers better by understanding personas, goals, pain points and where they are in their buying journey ultimately enables go to market teams to work in unison to improve experiences. With deeper insight into their customers and better alignment thanks to clean data, they can make sure all engagements with customers and prospects are relevant, personalized and consistent.
How is AI being used to determine buying coalitions by marketers?
The first step is to identify what is meant by a ‘buying coalition’. A buying coalition more accurately reflects the temporary alliance of distinct personas that are assembled to make a purchasing decision. Before, organizations don’t have automated contact creation, and it is only available in the sales reps mind. Now, organizations are able to more accurately target the right buyers at the right time.
By applying AI to CRM data, organizations are able to create full contacts for all potential buyers engaged in the decision-making process by capturing relevant activity and associating with the correct opportunity. AI can then track all touchpoints with various opportunity contacts, analyze how they were engaged and who was engaged before and after them to show both the optimal number of buyers needed to close a deal and also how to sequence and communicate to these buyers in order to build a strategic coalition. This can only be done once AI has mapped the CRM data to the correct opportunity. We’re able to do this with our own persona-driven analysis as well.
How can AI track sentiment to marketing campaigns?
By using AI and more specifically, sentiment analysis, companies can monitor what people say about their brand and based on that insight, deliver what consumers want to see. Traditional metrics are quantity-focused; number of views, clicks, comments, shares, etc. Sentiment analysis, however, goes beyond demographics to the quality of the interactions between the public and your brand.
Using AI and machine learning, businesses can analyse the engagement with messages and other outputs to see the meaning behind the messages. This helps you understand what kind of reactions specific events or marketing campaigns have generated – either positive, negative, or neutral. Sentiment analysis can help to detect responses to campaigns, identify promoters and detractors, and focus on sub-segments of your market with even further segmentation. You can also proactively identify issues with the product or message and identify competitor mentions.