Artificial intelligence fundamentally transforms marketing as AI and machine learning capabilities accelerate with AI Trends, enabling brands new opportunities to optimise budgets, deepen customer understanding, craft personalised messaging at scale, and ultimately drive greater growth. This article explores three of the most promising AI applications for marketing success:
- Optimising digital advertising through automated analysis and bidding.
- Modelling customer journeys to predict behaviour and guide experiences.
- Extracting impactful insights from sentiment analysis across content.
When strategically implemented, AI-fueled marketing can deliver tangible increases in lead gen, sales, and loyalty. However, as with any bleeding-edge technology, aligning capabilities to business objectives is vital.
1. AI Trends Opens New Frontiers for Paid Advertising
Digital advertising remains central to modern marketing. Marketers urgently need to maximise impact as paid media costs continue rising across platforms like Facebook, Instagram, and Google search.
Fortunately, AI is stepping in to inject paid efforts with unprecedented levels of optimisation, automating previously manual and guesswork-reliant processes:
Algorithmic Bidding & Budget Allocation
Bidding and budgeting have historically been time-intensive manual processes for marketers. Today, algorithms leverage machine learning to automate and optimise these decisions through real-time data processing. By continuously analysing audience signals, ad costs, keyword performance, and other variables, these bidding algorithms adjust bids to acquire relevant users for each campaign’s most efficient cost per conversion.
Hyper-Relevant Audience Building
Given the high costs per click across Facebook, Instagram and Google ads today, reaching the right audiences who will engage and convert is key. Powerful AI Trends analyses on-site and off-site data to identify a brand’s highest-priority customers. It studies their characteristics and behaviour patterns. Then, leveraging platforms’ lookalike modeling capabilities, AI configures new custom audiences with a “shared DNA” to the ideal targets; people equally likely to click, purchase or take other desired actions.
Automated Multivariate Testing
Previously, testing more than one variable at a time, like different ad images or captions, was highly manual. Today, AI manages an automated, systematic process called multivariate testing to uncover the optimal combination of elements for the highest conversion rates. By testing holistically across dimensions like visuals, copy length, calls-to-action, layouts, and more, AI determines which permutations resonate best for audience impact.
Analysis and Reporting
AI has an innate ability for pattern recognition across massive datasets beyond human capability. New platforms applying AI provide granular analysis of post-campaign performance, benchmarking the effectiveness of different targeting strategies, creatives, audiences and publishing platforms. Analysing historical efforts, they spotlight the specific ingredients driving the strongest outcomes.
These innovations enable paid advertising strategies to constantly optimise and evolve, squeezing budgets further and achieving better results.
2. Applying AI Trends to Track, Understand, and Influence Customers
While mastering paid advertising channels is crucial, the goal is guiding prospects across their purchase journey to become delighted customers. AI Trends is revolutionising marketers’ capabilities here as well.
By combining principles from data science, psychology, and neuroscience, next-gen algorithms ingest multiple data sources to model decision journeys. This unlocks unparalleled abilities to:
- Predict Lifetime Value: Score customers based on propensity to purchase again, referral likelihood, and profitability for personalised nurturing.
- Forecast Purchase Triggers: Indicates the events and signals making someone primed to buy a product. Informs timing of offers.
- Map Decision-Making: Analyse the emotions, external factors, and psychological nuances behind purchases. Adapt messaging accordingly.
- Send Contextual Offers: Generate dynamic incentives pegged to each individual’s calculated inclination to convert when the offer is received.
- Continuously Personalise: Update understanding of customer preferences and motivations over time. Optimise recommendations and experiences in sync.
AI removes the guesswork by establishing feedback loops to constantly hypothesise, test, iterate, and predict optimal paths to drive conversion.
3. Extracting Impactful Marketing Insights from Language
From brand monitoring to campaign testing, some of the most popular applications of AI Trends analyse language around products and services. Natural language processing algorithms can digest enormous volumes of text data – too much for humans to handle – to uncover valuable nuggets, like:
Brand Health Tracking
AI tools can track emotions and perceptions associated with brands across news, reviews, social media, support forums, and other sources. This spotlights strengths, weaknesses, and opportunities.
Compare share of voice, key narratives, and positive mentions against competitors. Uncover threats, differentiate positioning, and build influencer connections.
Subject lines, social captions, landing pages – AI can A/B test endless combinations to determine objectively which variations generate the most positive engagement.
Emerging Keyword Opportunities
Continuously analyse search trends and online conversations to recommend rising queries and longer-tail keywords gaining traction. Capitalise early. This only scratches the surface of how NLP unlocks value. Ultimately, it empowers brands to listen, understand, and connect with audiences at scale to drive growth.
The Bottom Line
AI Trends can improve marketing KPIs like lead quality and volume, sales conversions, and customer lifetime value. However, success requires thoughtful implementation tailored to clearly defined business goals. Brands that effectively leverage AI early will gain sustainable competitive advantages. Now is the time for marketers to start testing AI-driven strategies, tools and platforms – before their competition beats them.