Artificial Intelligence - For the Efficient Marketer!
Last winter, Harley Davidson’s New York unit tested an AI-based marketing optimization platform called Albert as a pilot to generate sales leads. The platform, developed by the tech firm Adgorithms, crawls datasets across numerous digital channels such as Twitter, Facebook and Google to assess, analyse and measure marketing campaigns in real-time and then automatically optimizes them, significantly influencing outcome. The weekend pilot generated double the usual number of bookings for Harley New York.
And this is the difference, Artificial Intelligence can make. As the number of devices, platforms, media channels and tools proliferate, so does the information available to a marketer and the plethora of options available. The sheer volume of options and relevant channels comes at the cost of marketing efficiency; which AI is looking to address. The efficiency, precision and flexibility that modern automation and AI tools bring in has completely changed the manner in which a marketer can now reach his intended audience.
The idea that machine intelligence can automate marketing functions isn’t new. What has changed is the manner in which AI and other “intelligent” robots are being deployed by marketers. Machine intelligence is complementing business intelligence in decision making, acquiring the necessary aptitude to weigh in all data to make quick actionable decisions.
Albert, the AI-tool, increased dealership leads for HD New York by a whopping 2930% in three months, driving massive in-store traffic. That is the long-term marketing impact AI can deliver.
To the Basics
AI Marketing uses deep - database analysis, concepts of artificial and augmented intelligence and other prototypes such as Machine Learning, NLP and Bayesian Network. The significant differentiator is in the “reasoning”, which is performed by an “intelligent computerized algorithm” instead of a human.
At the core, AI-based marketing uses the complete set of means and techniques available, to enable behavioural targeting of marketing promotions and communication. A PRA (Perception-Reasoning-Action) logic is used by marketers deploying AI, to design a holistic marketing cycle, by automating the staggered marketing functions. The ultimate goal is to create a system in which the machine is capable of managing an entire marketing campaign, with minimal human intervention in routine, repeatable jobs.
What is happening now
NerdWallet, a San Francisco based American personal finance guide that helps people make and manage financial decisions, recently experimented with AI marketing, using LeadGenius, a SaaS-based start-up, to identify decision makers in their highest value B2B verticals such as consumer credit, auto insurance, and others.
Lead Genius uses a combination of artificial intelligence and human computation to identify and communicate with targeted sales leads. The company's crawlers comb through websites, business directories, government filings, and credit data to train a machine learning system for business-to-business sales. After a short pilot, NerdWallet has increased its engagement with Lead Genius across Business Operations, Sales Operations and Sales Enablement.
And that is the meticulousness and productivity that an AI-tool can bring in. The simultaneous data analysis, identifying complex patterns, that then help in publishing content and communication for the intended consumer, is the granular level of personalization that AI has brought in. And this can be repeated at scale.
This means that some marketing functions can now be deployed through AI – ensuring that early adopters are effectively reached out to. Human resources are then allowed time to concentrate on the tougher segments that require non-mechanical approach. AI tools use applied propensity models predict given events & detect user behaviour, such as scoring leads based on their likelihood to convert. They are the doers, executing tasks that would usually be done by a human operator.
Off course, all this is aided by relevant business intelligence, gathered from marketers, who design the tool towards collaborative use. This usage of AI & responsive human computation allows for seamless communication, analytics, mapping and execution, with data points; this level of hyper-personalization cannot be achieved by small marketing teams alone.
In 2016, ‘WordSmith’, the AI-backed writing tool, produced 1.5 billion pieces of content, channelling their tool to report on regular, data-focused events, such as quarterly earnings reports, sports matches and market data. Thus, for businesses which need large volumes of content to be produced, AI helped pick essentials from a pre-defined content sources and structure the same into a ‘human sounding’ article.
AI has been successfully used for content curation with companies such as Netflix and Facebook exploiting extensive customer data to recommend customized content, increase engagement rates and relevancy. Similarly, voice search, another common AI technique, could change future SEO strategies and organic traffic. Programmatic media buying can use the propensity models generated, to increase ROI on marketing spends.
Where do we go from here?
AI-propelled tools can help implement a multi-pronged strategy to reach out and interact with customers. We have seen companies deploy AI post sales as well, using extensive AI tools to effectively and successfully create multi-pronged CRM systems.
Chatbots are the most common example; companies using predictive behavioural analysis to accurately recognise and address drop-off points. AI is helping map customers across various digital platforms, finding opportunities for integration and collaboration with other businesses.
A new breed of marketers is emerging – part data scientists, part creative executioners, who seek to combine the powers of AI to creatively enhance customer experience. And while AI is useful, marketers should remember that machine intelligence can never substitute human resourcefulness. Like all technologies, AI should be strategically arrayed to extract profitable results. AI is still developing, and in the hands of an intelligent marketer, they can be profitably deployed to compliment human acumen and knowledge.
Brand and Marketing Leader | Most Influential Brand Leader 2023 - CMO Asia | Marketing Head | Strategic Marketing | Digital Marketing | Marketing Automation | Lead Generation | Brand Management |
7 年Very interesting...
Insurance Consultant, Strategist, Thought Leader and Trainer at Insurance Consultant & Trainer
7 年Hi Paresh - the case of HD is for B2C segment. Do you think we can extend it to a group of customers (example : group insurance) or B2B market. May be for the same datasets, algorithms differ.