Artificial intelligence (AI) is infiltrating marketing, unleashing new capabilities that offer businesses opportunities to boost performance and gain advantages… if they stay on top of the marketing AI trends and developments. While large enterprises dominate headlines with big budget AI marketing initiatives, nimble small businesses can also tap into a growing array of accessible, affordable AI tools to punch above their weight.

However, with so much noise and advice coming from all directions, it’s easy to feel overwhelmed. Wading through the hype to understand which innovations show the most promise and how to pragmatically apply them for real business value has become a real challenge. Many business owners and marketers of small-to-medium businesses (SMBs) have only vague notions of AI and how it intersects with areas like data analytics, automation and personalisation. They recognise AI as an important emerging force but lack concrete ideas on leveraging it effectively.

The launch of marketing AI technologies to the masses has – we believe – made it easier for small businesses to compete with the larger players. However, education around the ethical application of the tools was (and still is) lacking. That’s why, throughout this article, we’re running you through different areas that you can work with AI across your marketing. We’ll be looking at AI innovations at their most basic level, where solutions can deliver the most value, what to look for when evaluating options, and how you can start putting these tools to work on surmounting their most pressing marketing challenges.

2024 Marketing AI Trends:

1. More Conversational Ads

One of the biggest AI advancements in advertising is the ability to respond to customer inquiries and interactions more conversationally across mediums like social media platforms, search, and web. Working with AI, ads can become more contextual – understanding the underlying meaning within text, images, and video to determine optimal responses in the moment.

Rather than simply showing the same generic ad to every customer, ads can now “converse” by answering questions, providing specifics, recommending relevant products, or routing users to more information. Natural language processing, the ability for AI algorithms to comprehend human sentences and phrases, makes these conversational experiences possible at scale.

For small ecommerce companies, conversational ads provide a major opportunity to drive more qualified traffic that converts better once landing on your site. When ads directly answer the queries or meet the needs of searchers and viewers upfront, it builds engagement and intent, bringing users who are further down the sales funnel. AI-powered chatbots can handle the human-like dialogue while accessing customer data and order information to enable personalised, relevant exchanges.

The main benefit for SMB ecommerce sites is reducing ineffective impressions and clicks where users don’t end up taking meaningful actions. Conversational ads demonstrate relevance in the first exchange, so traffic sources like paid social and Product Listing Ads in Search generate higher intent visitors. For small marketing teams overwhelmed with managing multiple campaigns, letting AI optimise these “conversations” is also extremely efficient. And with chatbots able to operate 24/7, they enable scaling more personalisation than human agents ever could.

2. AI-Generated Ad Copy

One of the most tedious and time-consuming elements of running multiple ad campaigns is constantly having to produce written copy including headlines and ad text. AI can enable small businesses and marketers to have an “automated copywriter” that can independently ideate and generate endless effective headlines and body copy.

These AI tools function by ingesting data points like target customer demographics, product/service details, unique selling propositions, ideal outcomes, and past top-performing ads. Sophisticated natural language generation algorithms then compose relevant copy targeted to those specs. The AI examines multiple combinations of key phrases, emotional sentiment, calls to action, etc. to assemble ads tailored for your situation.

The main advantage for SMBs is significantly faster ad iteration and testing. Small teams no longer have to manually create dozens of ad variants to find winnings ads for each campaign. Your AI copywriter handles this grunt work automatically, delivering quality, polished ads for your human team to then test and refine further. And because these tools continually optimise, they leverage learnings to produce better ads over time in an automated flywheel.

With AI-powered copy, SMBs can achieve more personalisation scaled across their advertising programs. The algorithms detect what messaging best resonates with each customer segment and which products/services they commonly seek. So every campaign and ad unit can feature its own auto-generated, hyper-relevant copy. Freely generating so many ads unlocks more complexity without overburdening small marketing teams.

3. Automated Bidding and Budget Allocation

As SMBs expand their digital advertising across more channels and campaigns, properly managing bids and daily budgets becomes highly complex. Too manual, and it bogs down productivity for small teams or suboptimal allocation leaves ROI (return on investment) on the table. This is where algorithms calibrated to your key performance indicators (KPIs) can optimise penny-level variables dynamically to drive better outcomes.

Automated bidding allows businesses to delegate bid management to AI under clear direction on ideal conversions or other target metrics. Machine learning processes millions of bid adjustments on the backend to discover combinations that will mathematically achieve set optimisation goals whether around cost per purchase, return on ad spend (ROAS), cost per click (CPC), or other objectives you care about most.

Similarly, automated budget allocation uses prediction modelling and statistical analysis to shift daily campaign budgets to better performing platforms, campaigns, ad sets, etc. If the AI engine determines specific paid social initiatives generate substantially better ROAS, it will automatically increase funding there while reducing budgets for lower-potential areas. This reallocates resources to where AI calculates incremental dollars will achieve the highest impact.

For SMB marketing teams that lack experience or bandwidth to oversee convoluted bidding strategies across channels, letting AI manage these variables lifts a huge burden while improving performance in areas like conversions and profitability. The algorithms handle constant market fluctuations and respond with appropriate bidding adjustments up or down accordingly. Rather than making manual changes in fits and starts, AI bidding enables persistent optimisation every moment new data enters the system.

4. AI-Enhanced Content Creation

Creating high-quality website content, blog posts, emails, and other marketing collateral consumes substantial resources for busy business owners and small marketing teams. Between ideating topics, outlining content, writing drafts, and optimising publishing, limited bandwidth leaves many small teams unable to produce content at the volume and frequency needed to attract visitors and leads. AI applications can now alleviate much of the heavy lifting when developing useful, engaging content.

AI content tools aid the process in three primary ways: research assistance, content structuring, and content generation. To begin, the AI can ingest key information about your business, products, services, target personas and analyse trends and search data to output promising content ideas that address customer interests and search intent.

From there, content structuring functionality helps to organise researched ideas into article outlines and content frameworks. The AI proposes logical groupings of topics and subtopics along with ideal sequences and hierarchies for the sections. This framework forms the backbone that human writers can build upon.

For resource-constrained teams, this allows maintaining websites with lots of fresh, optimised content that speaks to customer interests without becoming beholden to manual creation.

5. Predictive Analytics

With online interactions and transactions generating more customer data than ever before, unlocking actionable insights can be overwhelming for business owners lacking analytics expertise. This is where AI can step in – continuously processing volumes of behavioural, conversational, and sales data to uncover trends and signals businesses can act upon to enhance outcomes, in minutes.

Predictive analytics encompasses various techniques and machine learning algorithms that help model the probability of future events based on large datasets. The AI examines variables like past conversion rates tied to certain customer segments and campaign channels under an array of conditions. It then builds probable models to forecast similar scenarios, essentially predicting the likelihood of a specific success metric before outcomes actually occur.

For SMBs, these analytical models support sharper decision making through indicators like:

  • Probability a segment will purchase after email Nurture Sequence A vs Sequence B
  • Projected sales impact from increasing digital ad budgets by $X across identified high-potential regions
  • Chances of customer cancellation if Service Z subscription pricing rises Y%
  • Rather than relying solely on rear-view intuition, predictive insights illuminate which actions statistically show the greatest ROI upside even before you invest budget. This enables SMBs to orient strategy, messaging, offers, and experiences around the highest-potential opportunities while mitigating risk.

Ongoing adoption of machine learning analytics builds a flywheel where models become continually more accurate as more data enters the systems. Over this next year, predictive engines will crunch inputs like never before, bolstering precognitive indicators you can translate into measurable sales impact.

Getting Started with AI-Powered Marketing

Marketing AI adoption will continue accelerating rapidly in the months and years ahead. Those that strategically apply the right technologies can gain advantages over competitors who delay implementation. The key is focusing first on one or two capabilities (use cases) that clearly align with your most pressing operational constraints and performance gaps.

While the AI marketing landscape offers many emerging innovations to consider, the five covered in this article represent some of the more mature solutions where real-world cases have proven substantial wins for small businesses. Prioritising areas like conversational ads, automated copywriting, AI-based bidding, optimised content creation and predictive analytics lays the foundation for transformative impact.

As you vet potential tools and partners to explore these AI-driven strategies, be sure to seek out trusted advisors who can match the right technologies to your unique business situation. With help bridging the knowledge gap on how to pragmatically activate AI for your needs, savvy small-to-medium businesses can deploy cutting-edge marketing that works smarter, not harder.

Ready to Discuss Your AI Marketing Options?

Book a free 30-minute no-obligation call with our team to discuss which innovations show the most promise for your marketing and growth objectives this coming year.