Weekly News Insight: AI Marketing
Will Artificial Intelligence become the future of marketing?
It feels like only yesterday when the internet was introduced to the world and transformed the way business operates. Back that time, the talk of AI and robotics are millions away in the future. Companies are busy building their strategies around data analysis and programming. Today, the advancement in technology has revolutionized the concept of information gathering.
Digital age as we know it, promotes the implementation of business intelligence, artificial intelligence, data mining, block-chain, and big data among others, in enhancing marketing operations. Accenture predicted that AI will boost profitability by 38% and generate $14 trillion of additional revenues by 2035.
So how will AI affect marketing in the future?
Five Ways to Implement AI in Marketing Today
Artificial intelligence (AI) boils down to a relatively simple concept: using machines to process data and automate repetitive tasks. AI also helps with seamless integrations that have been overlooked and taken for granted.
While AI, by definition, seems quite simple, the execution and process are not. Here are five internal applications for AI that you may not have integrated into your practice yet, according to Forbes.
Sales prediction
Systems such as Salesforce, Active Campaign and many more, has incorporated predictive analytics (AI) into their services. Users can now search their database for most engaged leads and prospects along with other key indicators. This information helps marketing team to yield higher close-rate percentages.
Ad bids
Google is leading the way in AI development, testing and integration. Google’s paid ad campaign, Smart Bidding, uses AI to test, monitor and adjust the user’s Google Ads bid strategy with the intent of improving the quality and return on investment (ROI) of the campaign.
Dynamic ads
AI can use predictive analytics to serve the most relevant online ads to prospective customers. Sometimes this means providing Google a list of landing pages companies would like to use in an ad campaign. AI will then scan the pages and identify critical phrases and keywords for each page that organization can leverage to create dynamic ads.
Improve internal process
Obviously, AI helps tremendously in a company’s internal operation with its automated capability. From automated proposal tracking, campaign reports, to automated email marketing to send and personalize emails delivered, AI has virtually helped increasing efficiency and responsiveness of an organization while providing real-time access to the data it collected.
Chatbots
Chatbots allow brands to have conversations and answer inquiries, even when the office is closed. It also helps providing an immersive and interactive customer experience.
Is AI Ready to Transform Marketing Industry?
Artificial intelligence and machine learning tools are becoming increasingly common for their unprecedented levels of efficiency. However, Forbes believed that 90% of the organizations will face significant barriers to full adoption due to the complexity and relative unfamiliarity with the technology.
Some of the biggest challenges to AI marketing success include:
The lack of IT infrastructure
A robust IT infrastructure is necessary for successful implementation of AI due to the nature of the technology that requires vast quantities of data as well as powerful hardware. Setting up such an infrastructure can be expensive. Not to mention, such complex infrastructure requires frequent updates and regular maintenance, which could be quite challenging for startup and small medium organizations.
The lack of data utilization
Acquiring a decade worth of data can be a major obstacle. Indeed, we are living in the era of big data, for businesses to go beyond standardized metrics and draw deeper insights. But not all organizations are able to effectively utilize the data produced, which in turn could AI to deliver poor results.
There’s no constant in evolution
The ever-changing nature of the marketing arena makes it impossible for data sets to remain consistent over the years. On top of that, the advertisement market isn’t static and previously successful models face difficulty as consumer behavior evolves. Businesses need to account for this risk of a gradual decrease in efficacy by allocating safeguards, such as a continuous learning curve for the AI algorithm.
The lack of AI experts
Regardless of the hype that surrounds AI, the truth is that only a small fraction of the population can be considered professional experts. Marketing organizations will likely be forced to face intense competition when looking for AI talent. As the number of companies that are looking to integrate AI technology into marketing increases, the existing pool of AI talent will likely fall sufficiently short on filling these new positions.
Incorporating AI into B2B Marketing Strategy
AI has been a hot topic in business to business (B2B) marketing for several years now. From improving account identification to using intent-level data to better understand prospects and customers to being able to deliver a one-to-one connection at scale, AI is the driving force behind much of the B2B marketing innovation today.
More than 84% of B2B marketers and salespeople are using, implementing, planning to use or evaluating AI. But, there is a clear disconnect between understanding the value of AI and implementation.
Forbes shares three tips for B2B marketers to overcome those barriers and embrace AI.
Understanding the challenges
Marketers don’t need to have a full in-depth knowledge about AI but instead, they need to have a solid understanding of what challenges they need to solve. Marketers need to see AI as foundational, enabling applications that are solving the specific marketing challenges they are trying to address. So instead of adopting AI, they need to adopt sophisticated marketing technology, sales technology or advertising technology applications or solutions that can help them solve specific challenges.
Understand what AI can and can’t solve
The next step is to determine how AI can help. AI is great at synthesizing massive amounts of data and examining trends that predict future behavior. What AI isn’t going to solve for is having bad data or a lack of creativity.
Depend on AI vendors
Vendors are an often-overlooked AI resource. Over 40% marketers either aren’t aware of or aren’t using the AI capabilities that are part of vendor solutions. Companies can rely on their vendors to deliver AI-based solutions that can be integrated into any technology ecosystem.
