Businesses that can harness AI powered marketing insights and personalisation are highly likely to outperform those businesses that don’t.

The value of AI powered marketing insights and personalisation

McKinsey found that 53% of companies report revenue increases from AI use in marketing and sales. 7% achieved greater than 10% revenue increases.

Using AI in marketing can help businesses drive performance improvements across the board:

• Conversion rates increase by an average of 20% when companies integrate AI into marketing. Some see up to 30% improvements through predictive analytics.
   
• Email marketing with AI personalisation performs well with $38 ROI for every $1 spent in e-commerce.
   
• AI-powered targeted advertising increases conversion rates by an extra 10%. Predictive analytics drives a 20% increase in sales efficiency.

What’s more, Boston Consulting Group research shows AI marketing leaders are:

• Are 2x more likely to update offers in real-time
• Have 2.5x higher revenue growth rates compared to traditional approaches
• Experience a 70% reduction in production costs
• Improve marketing content production speed 3x

Source: 50+ AI Marketing Statistics in 2025: The Numbers That Show AI Is Transforming Marketing
 

The value of AI marketing insights

1) AI is good at processing large, complex data sets
Modern marketers and businesses have so many data sources to evaluate e.g. web traffic, mobile apps, CRM, social media, email, ads, purchase history, customer support interactions, etc. that without AI, making sense of it all is overwhelming. 

AI excels at analysing large, messy datasets and can quickly spot trends, anomalies, and patterns that humans would miss or take days/weeks to uncover.

2) AI helps enable prediction and proactivity
Traditional analytics tend to focus on what happened (e.g. which campaign performed best). By contrast AI-powered analytics and predictive models can forecast future customer behaviour such as who might buy next, who might churn, which segments are most valuable. This means that marketers can act before the opportunity or issue appears. 

That shifts marketing from reactive to proactive. Marketers can tailor offers, reach out at optimal times, or redesign campaigns based on forecasted trends. 

3) AI improves efficiency and effectiveness
Using AI to generate insights saves time with fewer hours spent manually analysing spreadsheets or a wide range of data sources. Marketing teams using AI report that it improves productivity and reduces their manual workload. 

Now even small teams or SMEs can achieve what previously only large firms with data-teams could.

4) AI brings a competitive advantage

• In business agility. Companies that leverage AI-powered insights can respond faster to market shifts, optimise campaigns constantly, and test ideas quickly giving them an edge over competitors relying on static or quarterly reporting. This is particularly advantageous in sectors where margins are tight and customer acquisition/retention costs are high.
• In customer understanding and experience. AI can build deep, dynamic customer profiles blending demographic, behavioural, contextual, and even feedback data to understand segments, preferences, and likely future actions. 

With faster responses and better customer understanding as a foundation, personalisation can become smarter and deliver more relevant content/offers, better timing, improved retention, and stronger customer loyalty.
 

The value of AI marketing personalisation

1) AI helps meet customer expectations
Increasingly consumers expect brands to ‘get them' and share tailored offers, relevant content, and contextual recommendations with them. Surveys show that a large share of shoppers value personalisation and that personalised discounts or loyalty rewards significantly influence purchase or brand-sharing behaviour.

2) AI enables personalisation at scale
As the number of digital touch-points grows (web, mobile, email, ads, apps, social media), manual segmentation and customisation become impossible. AI can process vast behavioural, contextual, and real-time data to deliver hyper-personalised content, offers, and experiences. 

Recent data shows that marketing-automation and AI-driven personalisation are already delivering measurable results - better open and click-through rates on emails, higher conversion rates, and overall increased efficiency. 

3) AI helps improve customer experience, loyalty, and business growth
AI-powered personalisation can help build connections with customers that cultivate a stronger sense of value, belonging or being understood. This boosts loyalty, repeat business, and brand advocacy. 

But even with the advantage AI marketing insights and personalisation can bring they won’t automatically solve all your problems, and, used unwisely could even cause a few.
 

AI insights and personalisation need a human touch.

AI doesn’t have human creativity or emotional intelligence. For AI to work well it must be used with a human touch:

1) Check your data for quality and completeness.

• Poor and / or fragmented data will lead to poor insights. Ensure that data is collected, cleaned and properly integrated.
• AI personalisation depends heavily on clean, unified data. Without that, personalisation efforts may underperform or feel inconsistent.

2) Make sure your AI activity underpins your company goals.
AI insights need to feed into decision making that is aligned with achieving business objectives. Don’t create reports just because you can!

3) Use human oversight and creativity with AI

• AI gives patterns and predictions, but humans need to interpret them, choose which to act on, and maintain brand voice and ethics.
• Too much automation, or over personalisation can have a negative impact. Carry out a human sense check and think about how you would feel if you were on the receiving end of your own communications / activity
• Content will work best where it is driven by human creativity and emotional intelligence 

4) Always be transparent and trustworthy in how data is used.
Ethics, privacy, and trust are important. Businesses must balance personalisation and data usage with respect for user consent, transparency and data protection. Over-personalisation or misuse of data risks damaging trust.

5) Treat AI insights as hypotheses.
Test, measure and learn as much as possible to make sure that you keep on track and are getting the most out your AI insights and personalisation.
 

How SMEs can tap into the power of AI insights and personalisation

Within a couple of months of using AI insights and personalisation most SMEs can achieve:

• A measurable increase in conversions
• More repeat purchases
• Higher email engagement
• A clearer understanding of customer behaviour
• Automated marketing that saves time

Here’s how:

1. Start with the data you already have

You won’t need as much data as you might think! You’ll almost certainly have enough data to begin personalisation e.g.

• Website analytics (Google Analytics, Plausible, etc.)
• Email engagement data (opens, clicks, purchases)
• CRM or customer lists
• Social media interactions
• POS or e-commerce history
• Customer service transcripts

The data from these can be exported into a simple table or connected through ready-made integrations.

You don’t need a unified Customer Data Platform to get started. A few clean spreadsheets will be enough to get you off the ground with AI analysis and insights.

2. Many marketing platforms already have AI-enabled tools built in. Use them!

Most marketing tools used by small businesses include personalisation and predictive insights. You don’t need to build AI.

Here are examples of accessible AI features from some of the most common marketing platforms:

Email & marketing automation | Mailchimp, Brevo and Klaviyo - AI segment suggestions, send-time optimisation, personalised content.

E-commerce | Shopify, WooCommerce - AI product recommendations, personalised offers.

CRMs | HubSpot, Zoho - AI scoring, next-best action, churn prediction.

Advertising | Google Ads & Meta Ads - AI targeting, dynamic creative, automated bidding.

Make sure that you take advantage and turn on the AI features you’re already paying for / that are already included. Start small with things like automated segments, dynamic product feeds and personalised email blocks and build from there.

3. Identify two or three high-impact personalisation opportunities

Focus on areas that will have a clear Return on Investment. The biggest wins usually come from:

a) Personalised email

• Product recommendations
• Behaviour-triggered journeys
• Abandoned cart flows
• Cross/upsell sequences

b) Personalised website experiences

• Dynamic homepage content based on past visits
• Recommendations ('You may also like…')
• Geolocation-based offers
• Returning customer recognition

c) Personalised ads

• Dynamic ads based on browsing or cart behaviour
• Predictive audiences
• Lookalike modelling done by the ad platforms’ AI

Pick just one area to start (email is usually easiest) and scale from there.

4. Adopt ‘no-code' AI insight tools

You don’t need technical skills to access AI analytics tools that can analyse your marketing data and create insights that are easy to understand.

Here are some AI marketing tools that you could consider using:

• Google Analytics with AI insights
• HubSpot AI analytics
• Klaviyo’s Churn Risk Prediction and Customer Lifetime Value (CLV) predictions
• Mixpanel’s automated insights
• ChatGPT for ad analysis or campaign performance summarisation (export your data and ask!)

Consider setting up automated weekly AI reports showing:

• Key drivers of conversion
• Drop-off points
• Content/ad performance patterns
• Recommendations for optimisation

5. Build customer personas with AI (based on real data)

You can get AI to help create buyer personas by uploading anonymised customer data and getting AI to:

• Cluster customer types
• Identify motivations
• Reveal behavioural patterns
• Forecast trends or seasonality
• Suggest messaging that resonates with each persona

You can do this using tools like ChatGPT, miro or Hubspot’s Make My Persona. Create segments from real data that you can target with highly relevant marketing activity.

6. Use AI to scale content personalisation

Once you know your segments, you can use AI to generate content variations based on them, things like:

• Email subject-line variations
• Product descriptions targeted to segments
• Personalised landing-page copy
• Different ad creative for each audience cluster

Even with a small team you can personalise at scale! Consider creating content ‘templates’ and targeting different versions at key segments (keeping it relatively small and simple to start with) e.g.

• 3 versions of ads 
• 3 versions of email copy per funnel stage
• Dynamic website blocks that match user interests

7. Automate Customer Journeys

Marketing automation is perhaps where small businesses can get the most benefit from using AI.

Keep things simple when starting out with marketing automation and concentrate on a few core automated journeys like:

• Welcome series personalised by acquisition source
• Abandoned cart with product-specific recommendations
• Post-purchase journeys with personalised upsells

Once you have these set up and working well, you can expand and look at automating other customer journeys e.g.

• Churn-prevention flows
• Repeat purchase reminders
• Segment-specific education sequences

Avoid trying to map and automate an entire customer lifecycle at once and build the journeys with the best immediate revenue impact first.

8. Build trust and respect privacy

Being too quick off the mark or over-familiar can come across as being a little ‘creepy’ and could alienate customers.

When using personalisation ask for preferences transparently and explain the value of sharing their preferences (e.g. Let us know your favourite styles and we’ll send you details of products that you’ll like).

To help build trust and demonstrate transparency consider publishing a simple privacy promise explaining how you use customer data to create a better experience (and not for surveillance).

9. Measure, learn and repeat (with improvements)

Don’t ‘set and forget’!

Test, measure and learn as much as possible to make sure that you keep on track and are getting the most out your AI insights:

• Test small variations
• Use AI to analyse what worked well (and what didn’t work so well)
• Review and update segments and triggers regularly
• Scale winning experiences
   

Summary: The value of AI powered marketing insights and personalisation

Using AI in marketing can help businesses drive performance improvements across the board:

• AI enables deeper understanding of customers. AI helps process large and complex data to help uncover patterns, predict behaviours (who may buy, who may churn) allowing marketers to be proactive rather than reactive.
   
• It levels the playing field - even small businesses can compete. Most small businesses already have enough data (e.g. web analytics, email stats, CRM lists) to start using AI insights.
   
• It enables personalisation at scale. AI helps deliver personalisation across multiple touchpoints (email, ads, website, e-commerce) at scale helping to deliver the tailored experiences that customers now expect.
   
• But human judgement is still critical:
  • Make sure that your data is clean and integrated
  • Use human oversight to interpret and sense check AI’s recommendations and ensure they are aligned with your business goals
  • Remember that AI doesn’t have human creativity or emotional intelligence (use AI with a human touch)

It’s relatively easy for SMEs to use AI in marketing:

You can start with the data you already have. You don’t need a huge database to benefit from AI insights. 

Leverage your existing tools. Many marketing platforms already include AI-driven features like email personalisation, product recommendation and ad-targeting. 

Focus on the highest-impact areas first e.g. personalised email flows, dynamic website content, ads or recommendations for returning customers. 

Maintain a human-first approach. Use AI to inform and scale, but apply human creativity and emotional intelligence, brand judgment and ethics.
 

Other articles on AI in marketing that may interest you:
In the age of AI in marketing, is trust the most sustainable competitive advantage?
7 unorthodox ways to get more GenAI traffic for your website
Could an over-reliance on AI and automation be hindering your marketing efforts?