Utilizing AI in your business marketing is more cost-effective and simpler to implement than you think.
6 min read
Opinions expressed by Entrepreneur contributors are their own.
Finding a logical starting point for bringing artificial intelligence integration into your marketing strategy is intimidating, no matter what your budget looks like. However, for the SMB and startup entrepreneur without the wiggle room to experiment, getting started often feels incredibly risky or out of reach. But we’re reaching a point where it’s becoming a necessity for any brand looking to stay competitive.
Instead of being intimidated by big brands and their respective AI capabilities, small businesses should look to them for inspiration and utilize the lessons already learned by these companies, who can burden the risk of trying different AI strategies.
Here are three areas of big-brand AI implementations that we know work and are ripe for SMBs to try: search marketing, targeted displays and social media ads.
Search marketing
Search marketing is one of the biggest marketing tools any small-to-medium sized business has at its disposal, especially one reliant on a strong local population to keep it afloat. Think healthcare organizations, real estate companies, and more. Large brands have been leveraging the optimization AI can provide within search marketing for many years and it’s one of the most accessible options for start-ups and smaller brands needing to reach their local communities. Not only can AI help by automatically optimizing campaign keywords, site performance and relevant tags, but it often yields a better result at a lower cost than what the company previously saw.
Related: 3 Ways Artificial Intelligence Has Sparked Marketing and Sales Growth
Additionally, artificial intelligence layered on top of search marketing can ensure these businesses are keeping on trend with mobile — it is a mobile-first world after all — and recapture web visitors that may previously have been lost along the funnel. Geofencing, in particular, can help a business drive brand awareness and target specific leads through their phones. For example, if a realty company sets its geofencing parameters to target the parking lot of hospital it can present itself to an audience that might be in needs of its services such as new employees, traveling families and more.
Using AI in search marketing has been a tried and true strategy for major brands for a while and fortunately, there has been a trickle-down effect making it increasingly effective for those who don’t have a big brand budget and marketing team. As the consumer begins to adapt to artificial intelligence voice assistants, many large businesses are beginning to adapt their web presence to appeal to the likes of Alexa and Google Home. In the future, SMBs and startups may want to consider adapting for voice search marketing, as well.
Targeted displays
Impactful ads and branding are the cornerstones of any successful marketing initiative. Unfortunately, due to a lack of resources, smaller teams often resort to a one-size-fits-all approach to creating ads and often don’t have enough bandwidth to properly analyze the results.
But as AI grows in sophistication, targeted display tools are getting better and better at learning about the customer and adapting to what messages and images that appeal to them most. Netflix is a great example of a company capitalizing on this in a super practical way — AI is the reason why you may have noticed the movie and TV thumbnails change every once in a while on your screen. Its highly sophisticated targeted display algorithm is learning what makes you watch and what has you skipping right over.
According to Salesforce, this personalized approach has serious impact on purchase intent too, suggesting they drive 26 percent of e-commerce revenue in one survey. While a company might not have a Netflix budget, there are still plenty of cost-effective options that can help learn which images, text and colors get clicks and which ones don’t. LOCALiQ’s internal AI creative tool Grandstand, for example, uses a type of AI called deep learning to predict creative and design performance to make small businesses’ ads most impactful with audiences.
Social ads
Social media advertising has an incredible ability to micro-target specific audiences and when used responsibly, it’s a highly effective marketing tool that gets a boost when AI is added to the mix.
Coming in at a low starting cost, with minimal risk, social ads can be an easy entry point for business of all sizes to make AI work for them. Not only can a business, such as a real estate management company, target people in the area, but the AI can also constantly be updating and optimizing the ads to drive more engagement visits and touchpoints with your intended audience. Tools like this are already a core strategy for digital agencies and publishers and are now being made accessible for small and medium-sized businesses as well. The Network, for example, utilizes AI engines to constantly work to optimize search and social ads to ensure they’re getting to the right people at the right time, and increasing ROI for advertisers of any size.
Related: AI Isn’t Replacing Workers; It’s Picking up the Slack. Here’s How.
These innovative solutions are paving the way for even more intelligent technologies down the road. As AI grows in flexibility these social media-based AI tools are getting better and better at learning customer behavior and intent and adapting to their needs, so much that we’re even seeing chatbot technology become more and more accessible for the SMB or startup. Soon, not only will these businesses be able to hook more eyeballs into their services via social media ads, they’ll be able to take another step into the funnel by engaging them and answering questions via the AI.
Many marketers are still talking about AI like it’s on the horizon, but the truth is it’s here and all the big brands are using it. Any small business looking to stay competitive needs to figure out how to bring AI into the marketing team and take advantage of all the lessons already learned big brands and make a strong showing right from the start.
What’s changed (and what to do differently now)
A few meaningful shifts since this was written make AI marketing both more powerful and a bit more nuanced to run well—especially for SMBs. The core ideas (search, targeted display, social ads) still hold, but the best practices around them have evolved.
### 1) Privacy and tracking limitations require cleaner data and smarter measurement
Customer privacy expectations and platform restrictions have reduced the reliability of older “easy mode” tracking (for example, heavier reliance on third‑party cookies and some forms of cross-site tracking). As a result:
– **Prioritize first‑party data** (email lists, CRM, onsite engagement, loyalty programs) and use it to build audiences and measure outcomes.
– **Adopt privacy-safe measurement** such as aggregated conversion reporting, modeled conversions, and server-side or API-based conversion tools where appropriate.
– **Focus on incrementality** when possible (lift tests, geo-tests, holdouts) rather than assuming all platform-attributed conversions are equally real.
**Practical takeaway:** AI optimization works best when you feed it high-quality conversion signals. Getting your conversion tracking and CRM integration right is now a competitive advantage, not a technical nice-to-have.
### 2) AI-powered creative is now a baseline skill—so brand guardrails matter
Generative AI has made it dramatically easier to produce ad variations (headlines, images, scripts, landing page copy). That lowers cost and speeds testing, but it also increases the risk of:
– Off-brand messaging and inconsistent voice
– Unverified claims or compliance issues (healthcare, finance, housing, etc.)
– “Generic” outputs that don’t differentiate you
**Best practices:**
– Create **brand and compliance guardrails** (tone, approved claims, disclaimers, prohibited phrases).
– Use AI for **variation and iteration**, but keep a human review step for accuracy, legality, and brand fit.
– Maintain a **single source of truth** (product facts, pricing, offers) so AI-generated copy doesn’t drift.
### 3) Search and social platforms increasingly optimize with “black box” automation—feed them the right inputs
Many ad platforms now push automated campaign types that rely heavily on machine learning. These can perform very well, but they require:
– **Clear goals and conversion hierarchy** (lead, qualified lead, booked call, purchase)
– **High-quality creatives and landing pages** (you can’t “bid” your way out of a weak offer)
– **Enough budget and time for learning** (frequent changes reset learning)
**Best practices:**
– Tighten what counts as a “conversion” to reduce low-quality leads.
– Import offline outcomes (qualified lead, closed deal) where possible so the AI learns what *really* matters.
– Structure campaigns to avoid fragmenting data (too many small ad sets can starve the algorithm).
### 4) Content discovery is expanding beyond traditional search
Consumers increasingly discover businesses through multiple “search-like” surfaces: social platforms, short-form video, marketplaces, and AI assistants. This doesn’t replace SEO—it broadens it.
**What to do:**
– Keep core SEO fundamentals strong (fast site, clear pages, local profiles, structured data).
– Publish content that answers questions clearly and can be reused across channels (web, social, email).
– Ensure business information is consistent everywhere (hours, services, location, reviews).
### 5) Chatbots and AI assistants work best when they’re connected to real operations
Chatbots are more accessible and useful than ever, but performance depends on the quality of your underlying customer experience.
**Best practices:**
– Connect bots to **FAQs, inventory/service menus, booking, and CRM** where possible.
– Set **clear handoff paths** to a human (especially for high-intent leads).
– Monitor conversations to find gaps, then update the knowledge base and website content accordingly.
### 6) Ethics, transparency, and customer trust are performance levers
As AI-generated content becomes common, customers care more about authenticity and accuracy.
**Best practices:**
– Avoid misleading personalization or “creepy” targeting.
– Verify factual claims and testimonials.
– Be mindful with sensitive categories (health, financial status, housing, children).
—
If you’d like, I can add this section into the piece with the same voice and formatting as the original (e.g., as a “New considerations” header near the end), or tailor it specifically to one industry such as real estate, healthcare, or local services.
