If there were any doubts about the role of AI in digital marketing, the advanced capabilities of ChatGPT have unequivocally silenced sceptics. However, marketers were already well aware of its potential: according to Statista, 62% of marketing professionals incorporated marketing AI tools into their digital marketing strategies in 2022, marking a staggering increase from 29% in 2018.
AI-driven marketing has become immensely popular due to its unmatched precision and cost-effectiveness. Beyond aiding in customer interactions, artificial intelligence is progressively proving its value in creative domains such as writing, art, music, and coding – commonly referred to as generative AI.
For marketers, the question naturally arises: How can I harness AI in marketing to attract and convert more customers? Undoubtedly, AI elevates performance marketing campaigns to new heights, accomplishing tasks in mere seconds that previously consumed hours or even days.
Just look at the remarkable speed at which AI has evolved:
Let’s dive into the intricacies of performance marketing AI tools and technologies and explore specific methods to incorporate them into your campaigns.
Groundbreaking AI Technologies for Performance Marketing
Though AI may appear omnipotent, the scope of performance marketing AI technologies, instrumental in achieving measurable outcomes like clicks, downloads, and conversions, is often limited and occasionally conflated with applications. For instance, “marketing automation” is not an AI technology but rather an application of machine learning combined with natural language processing (NLP) – two foundational marketing AI technologies.
Contrary to the misconception that artificial intelligence might entirely replace human marketing, experienced affiliate and performance marketers recognise that the effectiveness of marketing AI technologies is contingent upon the marketer wielding it.
For in-depth insights into the dynamic interplay between artificial intelligence and human marketing, be sure to cheque out Phonexa’s Amplify webinar:
Underlying AI Technologies for Performance Marketing
|Machine Learning (ML)
|Self-learning algorithms that collect, interpret, and learn from data with certain freedom (not explicitly programmed)
|Product recommendations based on first-party data such as the user’s search and purchase history
|Multi-layer machine learning that digs deep into data and reveals complex patterns
|Image recognition by neural networks, including facial recognition and object detection
|Natural Language Processing (NLP)
|Understanding, interpreting, translating, and generating human language
|IVR systems, chatbots, virtual assistants, text generation, translation, etc.
|Converting spoken language into written text
|Voice assistants (Examples include Siri, Alexa, and more)
As a marketer, understanding the intricacies of AI technologies may not be necessary; however, knowing how to apply them within your campaigns is crucial. Fortunately, you can leverage marketing AI from start to finish, from AI content marketing to customer routing to conversion.
Here are five performance marketing AI applications that can revolutionise your campaigns:
1. Content Generation and Personalisation
AI, especially generative AI based on deep learning, defies the notion that it struggles with creative tasks. Statista reports that 55% of marketers use ChatGPT, and 42% use Copy.ai, an NLP software that generates content like social media posts and product descriptions.
AI in advertising is thriving, with some brands entrusting ad creation entirely to generative AI. For example, Heinz employed the text-to-image programme Dall-E 2 to visualise AI’s interpretation of “ketchup.”
AI aids in content translation, summarisation, curation, and, importantly, offers data-driven insights about user preferences and optimal timing for engagement. AI marketing automation software can send emails during the most responsive hours, optimising outreach.
While AI can automate content creation, human oversight is essential to avoid issues such as awkward wording, plagiarism, poor translation, and the lack of connection to the broader narrative and marketing strategy.
Here’s how you can write compelling blog posts with minimum effort.
2. Customer Journey Optimisation
In 2023, 35% of marketers believe their customer journeys are either “fully automated” or “mostly automated.” Customer journey optimisation involves collecting and analysing historical and real-time data as a customer progresses through the sales funnel.
Marketing AI can tap into lead data, dissecting the customer journey from A to Z. User behaviour analytics software can optimise lead flow and conversions, providing real-time insights into on-site performance, clicks, and conversions.
Chatbots, using natural language processing, machine learning, deep learning, speech recognition, intent recognition, and sentiment analysis, have evolved beyond self-service tools. According to Statista, 57% of B2B marketers use chatbots, with 55% generating new leads via chatbots.
Chatbots find applications on websites, social media, and mobile apps, enhancing user engagement and lead generation.
4. Call Routing
In call-reliant businesses, accurate and seamless call routing is critical. Contemporary IVR systems incorporate a fusion of marketing AI technologies, ranging from natural language processing and speech recognition to text-to-speech conversion.
Delve into the components of call centre technology.
When a caller contacts your business, it is imperative to offer them the most direct conversion path and consistent support across all touchpoints, addressing potential transitions, such as when a caller switches devices or dials an incorrect department. To achieve this, a cutting-edge AI-driven call routing system complemented by a meticulously designed IVR is essential.
Call Routing AI Technologies
AI-driven call routing systems ensure precise data-driven routing by employing the following marketing AI technologies:
|Automatic Speech Recognition (ASR)
|Converts spoken language into text by acoustic language models, allowing various text-based routing paths
|Natural Language Processing (NLP)
|Understands the caller’s intent, enabling complex tasks like sentiment analysis and language generation
|Machine Learning (ML)
|Interprets historical and real-time caller data into multiple patterns, enabling precise data-driven routing
|Verifies callers and validates inbound calls
These technologies identify callers, verify them, and direct them to the right live operator or provide independent solutions for simpler requests.
Related read: Maximise your business with call analytics software.
5. Predictive Modelling
Predictive modelling, driven by machine learning, utilises predictive analytics to simulate future outcomes without launching actual campaigns. By interpreting historical and real-time data, it provides data-driven predictions for future campaigns.
Predictive modelling allows marketers to simulate different scenarios and adjust variables until they identify a winning AI marketing strategy.
AI and Affiliate Marketing
Affiliate marketing has embraced AI technologies across various facets, from lead generation to customer support to sales to fraud detection. AI applications in affiliate marketing vary from narrow-focused marketing AI technologies like facial recognition to complex chatbots, IVRs, and virtual assistants, as well as sophisticated data analytics and predictive modelling.
From the initial AI description by Alan Turing in 1935 to advanced AI models like ChatGPT, DeepMind, and AlphaGo, AI has evolved to cover all aspects of life and business, with affiliate marketing being a significant beneficiary.
AI in Digital Marketing
|Effective segmentation is crucial, enabling you to deliver the right message to the right audience at the right moment. Technologies like machine learning and deep learning delve into customer data, unveiling intricate patterns such as contextual behaviour and psychographics. Present-day AI algorithms possess a deep understanding of customers, providing businesses with a wealth of insights.
|AI-driven decisions simplify affiliate marketing, streamlining campaign management to the extent that active supervision is often the only requirement. For instance, AI can establish an automated affiliate marketplace for affiliate networks, promptly matching supply with demand.
|Ad and Link Placement
|Strategic ad placement is paramount for cost-effective affiliate marketing, and AI excels in this area. Artificial intelligence analyses historical data, real-time user behaviour, and content relevance to identify optimal locations for affiliate ads and links. Moreover, AI algorithms can conduct A/B testing or simulate affiliate campaign outcomes, determining successful elements without substantial investments.
|Creating numerous website copies for diverse audiences is impractical, but AI allows content customisation based on the user’s location, preferences, and settings. Leading platforms like Amazon, Netflix, Spotify, Facebook, and Google leverage AI to deliver personalised recommendations and responses tailored to individual users.
|In affiliate marketing, attribution is a critical aspect, and AI seamlessly links customers to their affiliates by integrating data from CRM systems, ad platforms, affiliate networks, and other involved processes. AI-powered affiliate software enables sophisticated attribution models, moving beyond basic last-click attribution to include position-based, cross-device, time decay, and other models that distribute revenue based on an affiliate’s specific contribution.
|Designed to handle big data and identify patterns autonomously, AI evolves independently based on newly acquired data. This remarkable feature ensures that AI algorithms stay current, adapting swiftly to the dynamic affiliate marketing landscape. For example, if AI identifies fraudulent traffic, it can autonomously decide to pause the campaign, notify you, or find an alternative traffic source, restructuring its acquisition strategy.
Regardless of the AI application – whether it’s content generation, customer segmentation, or affiliate partner searches – AI performs tasks incomparably faster than humans, with processing speed contingent on the scope of implementation and desired optimisation level. Supervising AI is far simpler than brainstorming independently, allowing you to conserve energy for critical strategic decisions and non-automatable tasks.
Using Marketing AI Technologies to Deter Online Fraud
With approximately 10% of affiliate traffic being fake and 17% of links deemed fraudulent, combating affiliate fraud has emerged as a prominent AI application. From fake leads to cookie stuffing to URL hijacking, AI effectively monitors affiliate traffic, issuing warnings and halting campaigns upon detecting signs of fraud.
How Artificial Intelligence Combats Affiliate Fraud
|AI easily identifies potential issues, such as abnormally short on-site sessions, significant deviations from the normal click-through rate (CTR), or high bounce rates. It swiftly detects red flags by comparing historical and real-time data, taking immediate action when inconsistencies arise.
|The collaboration of machine learning and natural language processing analyses user behaviour patterns, including purchase history, browsing habits, and the genuine intent behind customer interactions. AI effectively discerns bots and fake leads by evaluating parameters such as browsing patterns, click patterns, mouse movement, and more.
|AI plays a crucial role in screening affiliate traffic, assigning trust and intent levels to individual customers. This ongoing screening maximises revenue and ensures the health of affiliate campaigns, partnerships, or networks by blocking fraudulent leads.
|In addition to combating fraud, AI ensures compliance with global and national laws and regulations, including provisions from institutions such as the Federal Trade Commission (FTC), General Data Protection Regulation (GDPR), and Payment Card Industry Data Security Standard (PCI DSS). AI tools are built to align with key affiliate marketing regulations and can even monitor legislative changes.
|Looking ahead, predictive analytics identifies potentially unprofitable campaigns and fraudulent partners, assigning success probabilities to specific endeavours. Marketing AI technologies are trained on both legitimate and fraudulent cases, continuously evolving by learning from new data to recognise unscrupulous activities based on dynamically changing probability thresholds.
Many AI fraud detection systems undergo training on both legitimate and fraudulent cases, utilising extensive datasets to acquire the ability to distinctly and promptly identify dishonest activities. When surpassing the established threshold, emergency algorithms come into play, triggering system notifications about detected fraud or automatically blocking it.
Here’s an example of a marketing AI-powered fraud detection process:
- AI collects comprehensive data on ad clicks and application installations, including device types, IP addresses, views, clicks, and user identifiers.
- The collected data is compared to learnt patterns and the fraud threshold, with AI assigning a risk score to specific actions, affiliates, or traffic sources.
- If the risk score surpasses the threshold, AI sends an alert or automatically blocks the fraudulent activity.
Best of all, AI continually evolves with the incorporation of new data into the system, adjusting to the continuously advancing techniques of fraud.
AI Gets Embedded Over Time
To grasp the trajectory of artificial intelligence marketing, observe the universal pattern of increasing adoption of new technologies. Only 13% of customers in 2019 were eager to use chatbots rather than traditional communication channels, unsure whether the emerging marketing AI technology would improve or worsen their shopping experience. Three years later, 25% of customers were “happy” or “very happy” to communicate with a chatbot when contacting a business.
Here’s our take on where the future heads and the place of AI in it.
The synergy of AI and marketing is evident, transforming the industry by combining yesterday’s impractical AI tools with a human touch. As marketing AI technology advances, everything that can be automated will be, and businesses that fail to keep pace risk losing in the competitive landscape.
The future indicates a continued shift towards automation, with marketing AI becoming an integral part of various business processes. AI and marketing’s collaborative evolution provides efficiency while retaining a human touch. An Amplify webinar featuring Erik Huberman, Founder & CEO of Hawke Media, and Talar Malakian, CMO at Phonexa, explores leveraging AI without compromising the human aspect. Topics covered include ad spending optimisation, AI-powered trend analysis, AI in performance marketing, and interpreting customer intents through AI-drawn data.
Enhance Your Affiliate Marketing With Phonexa
Phonexa offers an all-in-one performance marketing suite that seamlessly ties revenue back to campaigns and affiliates.
For just $100 a month, access eight proprietary solutions under one contract and a single set of credentials. Phonexa’s software suite includes lead tracking and distribution, call management, predictive modelling, user behaviour recording and analytics, real-time click tracking, email marketing, suppression list management, and automated accounting.
Phonexa’s Software Suite Composition
|LMS Sync: lead tracking and distribution
|Call Logic: call management software
|Cloud PBX: dedicated virtual cloud phone system for inbound and outbound calls
|HitMetrix: user behaviour recording and analytics
|Lynx: real-time click tracking and analytics
|E-Delivery: email marketing platform
|Opt-Intel: suppression list management
|Books360: automated accounting software
Frequently Asked Questions
What’s special about artificial intelligence?
Artificial intelligence simulates human behaviour, independently learns from new data and experiences, and adapts to changing conditions. While excelling in math, pattern recognition, and logical thinking, AI may lag in emotional intelligence, soft skills, and some creative tasks.
What is marketing AI?
Marketing AI involves using artificial intelligence technologies across the marketing spectrum, automating tasks from research to content creation to advertising. Marketing AI excels in data collection, predictive analytics, automation, scaling, and basic customer support.
What are the main performance marketing AI technologies?
Key performance marketing AI technologies include machine learning (ML), deep learning, natural language processing (NLP), and speech recognition.
Is performance marketing AI expensive?
Enrolling in a pay-as-you-go subscription model offers affordable access to top-tier marketing AI software. For example, Phonexa’s marketing automation software suite starts at $100 per month.
Will marketing AI eventually replace marketers?
While AI augments marketing teams, complete replacement within the next few decades is unlikely. Embracing AI now is wise, as it transforms marketing and sales strategies, becoming indispensable for competitive survival.
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