If anyone was skeptical about AI in digital marketing, the cutting-edge capabilities of ChatGPT finally put the nail in the Luddites’ coffin. Marketers, however, knew it all along: according to Statista, 62% of marketing professionals were using marketing AI tools as a part of their digital marketing campaigns in 2022 — a mind-blowing increase from 29% in 2018.
AI-powered marketing is all the rage for its unparalleled precision and cost-efficiency. Not only does artificial intelligence assist marketers with customer interactions, but it’s growing increasingly more helpful in creative tasks like writing, art, music, and coding – the so-called generative AI.
As a marketer, you be asking yourself, how do I leverage AI and marketing to draw and convert more customers? Indeed, AI takes performance marketing campaigns to the next level, completing in seconds what previously took hours and days.
Just look at the unprecedented pace AI has taken:
Source: Statista
Let’s get into the nitty-gritty of AI marketing tools and explore specific ways to use them in your campaigns.
As omnipotent as AI may seem, performance marketing AI technologies – ones helping to achieve measurable marketing results, such as clicks, downloads, and conversions – are quite limited and often confused with applications. For example, “marketing automation” is not an AI technology but an application of machine learning combined with natural language processing (NLP), two underlying marketing AI technologies.
On a similar note, artificial intelligence is sometimes thought to replace human marketing completely, which is not the case. Even seasoned affiliate and performance marketers agree that AI is only as good as the marketer behind it.
For exhaustive insights on the coexistence of artificial intelligence and human marketing, tune into Phonexa’s Amplify webinar:
| Technology | Description | Examples |
| 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 like the user’s search and purchase history |
| Deep Learning | Multi-layer machine learning that digs deep into data to reveal complex patterns | Image recognition by neural networks, including facial recognition and object detection |
| Natural Language Processing (NLP) | Understanding, interpreting, translating, and generating human language | Chatbots, IVR systems, virtual assistants, text generation, translation, etc. |
| Speech recognition | Converting spoken language into written text | Voice assistants (Siri, Alexa, etc.) |
As a marketer, though, you may not need a deep understanding of AI technologies but rather how to apply them within your campaigns. Luckily, you can leverage marketing AI from start to finish, from AI content marketing to customer routing to conversion.
Below are five performance marketing AI applications that can revolutionize your campaigns.
The common idea that AI is bad with creative tasks doesn’t hold water. In fact, the so-called generative AI – one based on deep learning, which is advanced machine learning – accurately spots patterns inherent to art, music, and writing. According to Statista, 55% of marketers use ChatGPT in their campaigns, with 42% using Copy.ai, an NLP software that generates content like social media posts and product descriptions.
AI and advertising are a match made in heaven. Some brands go as far as delegating the ad creation solely to generative AI. For example, Heinz used the text-to-image program Dall-E 2 to check what AI thinks “ketchup” looks like.
AI helps with content translation, summarization, curation, and – most importantly – provides data-driven insights about what users want and the right timing for satisfying their cravings. For example, AI marketing automation software can send emails during the most responsive hours — around 10 am and 4 pm on business days — while excluding the most clogged quarter hours.
Likewise, AI can analyze historical data and the customer journey to determine the right webpage layout, graphics elements, and CTAs for a particular customer. Intelligence marketing AI easily reconfigures the webpage for every user based on who they are and what they want, smoothly moving them toward the purchase.
Here’s how you can write compelling blog posts with minimum effort.
From creating tailored messages for different categories of customers to leveraging the right engagement timing, AI can significantly automate content creation. However, human oversight is still a must to dodge several bullets:
AI generates content in seconds, but it usually lacks connection to your bigger narrative, style, and marketing strategy. On the same note, AI generalizes too much, not discerning between shades of meaning or issuing the same information about two related yet different concepts.
The ineffective use of customer data was the second biggest hindrance in the customer journey in 2019, but the situation has changed dramatically since then. In 2023, 35% of marketers believe their customer journeys are “fully automated” or “mostly automated,” with only 21% ignoring customer journey automation.
In practice, customer journey optimization involves collecting and analyzing historical and real-time data as a customer moves down the sales funnel.
There are a few dimensions to the collected data:
Marketing AI can effectively tap into your lead data, dissecting the customer journey from A to Z, including what channels drive certain customers and how they interact with your brand on the way to conversion.
For better performance, you can dig into user behavior with user behavior analytics software, optimizing lead flow and conversions. AI-driven lead analytics software can provide real-time insights into on-site performance, clicks, conversion, and more. With video session replays, analytics software can help you identify friction touchpoints and room for improvement.
One of the first well-adopted AI use cases, chatbots started off as a self-service tool and evolved as a valuable lead generation and analytic instrument. According to Statista, 57% of B2B marketers use chatbots to understand their audience, with 55% generating new leads via chatbots.
You can implement a chatbot almost everywhere, including your website, social media marketing, and mobile app. Much like other marketing AI, chatbots use natural language processing, machine learning (simple chatbots), deep learning (advanced chatbots), speech recognition, and even intent recognition and sentiment analysis.
For a call-reliant business, accurate and seamless call routing makes a difference between a win and a failure. Modern IVR systems are a blend of AI technologies, from natural language processing to speech recognition to text-to-speech conversion.
Explore what makes up call center technology.
As a caller dials your business, you must provide them with the shortest conversion path and unwavering support across all touchpoints while taking care of all possible transitions along the way – for example, when a caller switches a device or dials the wrong department. For that, you need a state-of-the-art AI-driven call routing system topped by a well-thought-out IVR.
| 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 |
| Voice Biometrics | Verifies callers and validates inbound calls |
Call routing AI technologies unmistakably identify callers and distribute them to the right live operator – or even solve simpler requests independently (balance check, status confirmation, subscription renewal, etc.).
Related read: Maximize your business with call analytics software.
Whether you are searching for untapped markets, expanding locations, or testing new approaches, AI-driven predictive modeling uses predictive analytics to simulate future outcomes without launching real marketing campaigns. At the end of the simulation, you get data-driven predictions for your specific initial data.
The core of predictive modeling is machine learning. The software interprets historical and real-time data – demographics, time, location, and more – into insights into your future campaigns. By toggling switches and adjusting variables, you can simulate any number of scenarios until you find your winning AI marketing strategy.
As one of the most adaptive business avenues, affiliate marketing has long embraced AI technologies across the board, from lead generation to customer support to sales to fraud detection. Whether affiliates, advertisers, or affiliate networks, marketers can fully automate or at least prop up their campaigns.
However, not every AI is the same, ranging from narrow-focused technologies like facial recognition to complex chatbots, IVRs, and virtual assistants to even more complex data analytics and predictive modeling. From the first AI description by Alan Turing in 1935 to the most advanced AI models like ChatGPT, DeepMind, and AlphaGo, AI has evolved to cover all avenues of life and business, with affiliate marketing being among the main beneficiaries.
Source: Statista
| Segmentation | Accurate segmentation is key, allowing you to hit the right people with the right message at the right time. Technologies like machine learning and deep learning can dig deep into customer data to reveal complex patterns like contextual behavior and psychographics. Today’s AI algorithms know customers better than they know themselves, giving businesses tons of insights to avail of. |
| Automation | AI decisions simplify affiliate marketing and streamline campaign management to the point when you don’t have to do much more than supervise your ecosystem. For example, AI can create an automated affiliate market for affiliate networks, instantly matching the supply and demand. |
| Ad and Link Placement | Strategic ad placement is key to cost-effective affiliate marketing, and nobody does it better than AI. Artificial intelligence analyzes historical data, real-time user behavior, and content relevance to uncover the best affiliate ad and link locations. Likewise, AI algorithms can conduct A/B testing or simulate affiliate campaign outcomes to determine the winners without heavy investments. |
| Engagement | You can’t create a hundred website copies for different audiences, but you can use AI to tailor content depending on the user’s location, preferences, and internal settings.
Likewise, chatbots can issue different answers based on the keywords in the customer’s message. |
| Attribution | With attribution being one of the most sensitive aspects of affiliate marketing, AI unmistakably connects customers to their affiliates by integrating data from CRM systems, ad platforms, affiliate networks, and other process participants. AI can develop more complex attribution models than basic last-click attribution. With AI affiliate software, you can enliven position-based, cross-device, time decay, and other types of attribution that distribute revenue based on the contribution of a particular affiliate toward the purchase. |
| Relevance | Designed to process big data and spot patterns, AI doesn’t need specific guidance but can learn independently based on the newly acquired data. This incredible feature means your AI algorithms will never age, quickly adapting to the ever-changing affiliate marketing landscape. For example, should AI spot fraudulent traffic, it can decide to halt the campaign, issue you notice, or find an alternative traffic source independently and restructure its acquisition strategy. |
No matter what AI does – generate content, segment customers, search for affiliate partners – it does it incomparably faster than any human, with the processing speed depending on the scope of implementation and the desired optimization level. It’s much easier to supervise AI than brainstorm things yourself, saving energy for key strategic decisions and tasks that cannot be automated.
With around 10% of affiliate traffic proving fake and 17% of links fraudulent, overcoming affiliate fraud has become one of the major AI applications. From fake leads to cookie stuffing to URL hijacking, AI can effectively monitor affiliate traffic, issuing warnings and putting campaigns on hold should the signs of fraud be detected.
Source: Statista
| Pattern Recognition | Whether abnormally short on-site sessions, a significant deviation from your normal CTR, or a high bounce rate, AI can easily detect red flags and act accordingly. Most fraudulent activities cause a visible inconsistency between historical and real-time data, which is discovered by AI the very moment such an inconsistency happens. |
| Behavior Analytics | Machine learning and natural language processing can work together to analyze user behavior patterns like purchase history, browsing habits, and even the true customer’s intent when speaking.
Behavior analytics makes it possible to eliminate potentially fraudulent leads and optimize the customer journey for high-intent customers. |
| Screening | AI can cut fraudulent leads off advertisers and affiliate markets and screen affiliate traffic, assigning an individual level of trust and intent to every customer. The ongoing screening process maximizes revenue and maintains the health of your affiliate campaigns, partnerships, or network. |
| Compliance | Fighting affiliate fraud is important, but you must also comply with global and national laws and regulations. Most AI tools were built compliant with the main affiliate marketing provisions and institutions, such as Federal Trade Commission (FTC), General Data Protection Regulation (GDPR), and Payment Card Industry Data Security Standard (PCI DSS). It’s not out of the question that AI can monitor the legislation landscape, informing you about important changes and updates. |
| Predictive Analytics | Peeking into the future, predictive analytics can spot potentially unprofitable campaigns and fraudulent partners, assigning success probabilities to a particular endeavor. |
Most fraud detection AI technologies are trained on legit and fraudulent cases, consuming big data to learn to unmistakably and timely recognize unscrupulous activities based on the dynamically changing probability threshold. Surpassing the threshold puts emergency algorithms into action when the system notifies about the fraud or blocks it automatically.
Here’s an example of mobile ad fraud detection by AI:
The best thing is that AI evolves continuously as new data is fed into the system, adapting to the ever-improving fraud techniques.
To understand where artificial intelligence marketing is heading, consider the following universal pattern: over time, people are adopting new technologies at an increasing pace. In 2019, only 13% of customers were enthused about using chatbots instead of traditional communication channels, unsure whether the new tech 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.
It’s pretty clear where this world goes. Everything that can be automated will be automated, and those unable to keep pace with the progress won’t have a fighting chance in the ever-toughening competition for customer attention.
The synergy of AI and marketing is already there, with yesterday’s impractical AI contraptions turning marketing on a dime while retaining the human touch. Speaking of the human touch, there’s a fresh webinar where Erik Huberman, Founder & CEO of Hawke Media, joins Talar Malakian, CMO at Phonexa, for a hot debate about how to leverage AI so as not to lose your soul to the machine.
Among the topics are:
Here you go:
Uniting the best AI technologies under one roof, Phonexa offers an all-in-one performance marketing suite that ties revenue back to campaigns and affiliates. Whether clicks, calls, emails, or SMS, you don’t have to spend time juggling reports but can get it all within a single dashboard, empowering your marketing with ever-updated data.
For only $100 a month, you can get access to eight proprietary solutions under one contract and a single set of credentials. Phonexa puts you in the driver’s seat of your affiliate marketing campaigns without the need to juggle heterogenous marketing AI tools.
| LMS Sync: lead tracking and distribution |
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| Call Logic: call management software |
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| Cloud PBX: dedicated virtual cloud phone system for inbound and outbound calls |
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| HitMetrix: user behavior recording and analytics |
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| Lynx: real-time click tracking and analytics |
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| E-Delivery: email marketing platform |
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| Opt-Intel: suppression list management |
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| Books360: automated accounting software |
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Choose your subscription plan now or schedule a free consultation to learn more about how you can elevate your affiliate marketing with Phonexa.
Unlike no other technology, artificial intelligence can simulate human behavior and independently learn from new data and experiences, adapting to new conditions on the fly. In many areas, AI demonstrates unparalleled decision-making, flexibility, and autonomy.
A vivid example of the superiority of AI over humans is Stockfish. Chess engines have surpassed human players to the point where they can’t even achieve a draw. Even back in 1997, when chess engines were quite primitive, Deep Blue won a series against the former world champion Garry Kasparov.
Long story short, AI always beats humans in math and pattern recognition and sometimes also logical thinking. At the same time, AI is still behind in emotional intelligence, soft skills, and some creative assignments.
Marketing AI involves using artificial intelligence technologies in marketing and sales across the full range spectrum, from marketing research to content creation to advertising to campaign management. AI easily automates routine tasks that previously took hours and days if performed by a marketer. It excels in data collection and analysis, predictive analytics, automation, scaling, and basic customer support, among many other things.
At the same time, marketing AI sometimes struggles with contextual and emotional understanding, ethical decisions, sensitivity, and strategic planning.
The main performance marketing AI technologies include machine learning (ML), deep learning, natural language processing (NLP), speech recognition, and more. Arguably the most important AI technology, machine learning enables customer data collection and analytics. A no less important technology is natural language processing, which can extract insights from all kinds of customer data.
Performance marketing AI is insanely difficult to develop, but you don’t have to. You can enroll in a pay-as-you-go subscription model to get access to top-tier marketing AI software for only a few hundred dollars a month. For example, Phonexa offers its proprietary marketing automation software suite starting at $100 per month, unlocking access to eight solutions for leads, clicks, phone calls, emails, SMS messages, accounting, and more.
While marketing AI is a threat to certain areas of previously human-driven marketing, it’s unlikely to completely replace marketers within the next few decades. However, there’s no doubt technologies like machine learning and natural language processing will augment marketing teams and unlock more accurate and cost-effective marketing strategies.
It’s wise to embrace the marketing AI technologies while they haven’t gone too far and become too difficult to understand. At some point, AI will transform performance marketing and sales to the point where no company can survive the competition without cutting-edge AI-powered tools.
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