The Future of Digital Marketing

The Future of Digital Marketing: Advanced Targeting Strategies

Kurt GraverMarketing & Sales

In the UK alone, digital ad spending is projected to reach £29.3 billion by 2025, accounting for 75% of total media ad spending [1]. With such significant investments at stake, entrepreneurs and marketers must understand and leverage the latest targeting strategies to maximise their return on investment (ROI) and drive sustainable business growth.

In this blog post, we’ll explore the future of digital marketing through the lens of advanced targeting, delving into the key strategies, technologies, and best practices that are shaping the industry. From artificial intelligence (AI) and machine learning to programmatic advertising and contextual targeting, we’ll provide actionable insights and real-world examples to help you stay ahead of the curve and thrive in the digital age.

The Evolution of Digital Targeting

To understand the future of digital marketing, it’s essential first to examine the evolution of targeting strategies over time. In the early days of digital advertising, targeting was primarily based on broad demographic factors like age, gender, and location. While these factors provided a foundation for segmentation, they often lacked the granularity and personalisation needed to resonate with individual consumers.

As technology progressed and data became more abundant, marketers gained access to a wealth of information about consumer behaviour, interests, and preferences. This gave rise to more sophisticated targeting techniques, such as:

Behavioural Targeting
To deliver more relevant, personalised ads, behavioural targeting involves analysing consumers’ online actions, such as website visits, search queries, and purchase history. Marketers can create highly targeted campaigns that drive higher engagement and conversion rates by understanding consumers’ interests and intent.

Psychographic Targeting
Psychographic targeting goes beyond surface-level demographics to consider consumers’ attitudes, values, and lifestyle preferences. By understanding the underlying motivations and beliefs that drive consumer behaviour, marketers can create more emotionally resonant campaigns that forge deeper connections with their target audience.

Contextual Targeting
Contextual targeting involves placing ads on websites or apps relevant to the promoted product or service. By aligning ad content with the surrounding editorial content, marketers can increase the relevance and impact of their campaigns, reaching consumers when they are most receptive to the message.

Lookalike Targeting
Lookalike targeting involves identifying the common characteristics of a brand’s best customers and using those traits to find similar audiences across digital platforms. By expanding their reach to new prospects who share attributes similar to those of their existing customer base, marketers can scale their campaigns efficiently while maintaining a high level of relevance.

While these targeting techniques have proven effective in driving results, the future of digital marketing demands even greater precision, personalisation, and automation. Enter the era of advanced targeting.

The Rise of AI and Machine Learning

One of the most significant developments shaping the future of digital marketing is the rise of artificial intelligence (AI) and machine learning. These technologies are revolutionising how marketers approach targeting, enabling them to process vast amounts of data, uncover hidden insights, and deliver hyper-personalised experiences at scale.

According to a recent survey by Deloitte, 82% of UK companies have already implemented or are planning to implement AI solutions, with marketing and sales among the top use cases [2]. By leveraging AI and machine learning, marketers can:

Analyse consumer data in real-time
AI-powered tools can process and analyse vast amounts of consumer data in real-time, enabling marketers to identify patterns, trends, and opportunities as they emerge. This allows for more agile, responsive targeting strategies that adapt to changing consumer behaviours and market conditions.

Predict consumer behaviour
Machine learning algorithms can analyse historical data to predict future consumer behaviour, such as the likelihood of a customer purchasing or churning. Marketers can proactively tailor their targeting strategies by anticipating consumer needs and preferences for better results.

Optimise ad performance
AI can automate the process of ad testing and optimisation, analysing performance data to identify the most effective targeting parameters, ad formats, and creative elements. This saves time and resources and drives better ROI by continually refining targeting strategies based on real-world performance.

Personalise at scale
AI-powered personalisation engines can analyse individual consumer data to deliver highly customised experiences across digital touchpoints. From dynamic ad content and product recommendations to personalised email and website experiences, AI enables marketers to create the kind of one-to-one engagement that drives loyalty and revenue growth.

Real-World Examples

The Economist used AI-powered targeting to increase subscriptions by 300% while reducing cost per acquisition (CPA) by 80%. By analysing subscriber data to identify key attributes and behaviours, the publisher created lookalike audiences on Facebook that were most likely to convert [3].

Virgin Holidays uses AI-powered chatbots to provide personalised travel recommendations and streamline booking processes. By analysing customer data and preferences, the chatbots could deliver tailored suggestions and handle common queries, resulting in a 33% increase in bookings [4].

The Power of Programmatic Advertising

Another key trend shaping the future of digital marketing is the rise of programmatic advertising. Programmatic refers to using automated systems to buy and sell digital ad inventory in real-time, using data and algorithms to optimise targeting, placement, and pricing.

Programmatic advertising will account for 94% of total digital display ad spending in the UK by 2022 [5]. The benefits of programmatic are clear:

Programmatic automates the ad buying process, eliminating the need for manual negotiations and insertion orders. This saves time and resources, allowing marketers to scale their campaigns quickly and easily.

Programmatic uses data and algorithms to target ads with unparalleled precision, ensuring that the right message reaches the right audience at the right time. By leveraging a wide range of targeting parameters, from demographics and interests to behaviour and context, programmatic enables marketers to create highly relevant, personalised ads that drive engagement and conversions.

Real-time optimisation
Programmatic platforms use real-time data and machine learning to continually optimise ad performance, adjusting bids, placements, and creative elements on the fly to maximise ROI. This ensures that campaigns always run efficiently, adapting to changing market conditions and consumer behaviours.

Programmatic provides a high level of transparency into ad performance, with detailed reporting and analytics that allow marketers to track key metrics and make data-driven decisions. This helps build trust and accountability between advertisers and publishers, ensuring that ad spending is used effectively and efficiently.

Real-World Examples

Nestlé used programmatic advertising to promote its KitKat brand in the UK, targeting consumers based on location, weather, and time of day. By serving contextually relevant ads in real-time, the brand saw a 9% increase in sales and a 28% increase in ad recall [6].

British Airways used programmatic to target travellers with personalised offers based on their search history and travel preferences. By leveraging data from its website and app, the airline created highly targeted ads that drove a 50% increase in click-through rates (CTR) and a 20% increase in bookings [7].

The Future of Contextual Targeting

While behavioural and demographic targeting has been the backbone of digital advertising for years, the future of targeting is increasingly focused on context. Contextual targeting involves placing ads on websites, apps, or videos relevant to the product or service being promoted based on keywords, topics, and sentiment.

The benefits of contextual targeting are twofold. First, it ensures that ads are served to consumers when most receptive to the message, increasing the likelihood of engagement and conversion. Second, it helps to address growing concerns around data privacy and ad fraud, as contextual targeting relies on the page’s content rather than personal data.

As privacy regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have emerged, many marketers are turning to contextual targeting as a more privacy-friendly alternative to behavioural targeting. A recent survey by GumGum found that 69% of UK marketers believe contextual targeting will be key to digital advertising in a post-cookie world [8].

To maximise the effectiveness of contextual targeting, marketers are leveraging advanced technologies like natural language processing (NLP) and computer vision to analyse the content of web pages and videos in real time. This allows for more granular, nuanced targeting based on sentiment, emotion, and visual elements, creating a more immersive and engaging ad experience.

Real-World Examples

Adidas used contextual targeting to promote its outdoor apparel line, serving ads on websites and videos related to outdoor activities like hiking and camping. By aligning its ads with relevant content, the brand saw a 40% increase in ad recall and a 33% increase in purchase intent [9].

Unilever used contextual targeting to promote its Knorr brand, serving recipe ads on food-related websites and apps. By leveraging contextual signals like ingredient keywords and meal types, the brand created highly relevant, personalised ads that drove a 3% increase in sales [10].

The Importance of Cross-Channel Integration

As the digital landscape becomes increasingly fragmented, with consumers engaging across a wide range of devices and platforms, the future of targeting depends on seamless cross-channel integration. Marketers must be able to deliver consistent, personalised experiences across touchpoints, from social media and search engines to email and mobile apps.

To achieve this, marketers leverage advanced technologies like customer data platforms (CDPs) and identity resolution solutions to create a unified view of the customer journey. By stitching together data from multiple sources and devices, marketers can create a more complete, accurate picture of each consumer, enabling more targeted, personalised campaigns.

According to a report by Epsilon, 80% of consumers are more likely to do business with a company that offers personalised experiences across channels [11]. By leveraging cross-channel data and targeting strategies, marketers can create seamless, integrated experiences that drive loyalty and lifetime value.

Real-World Examples

Starbucks used cross-channel targeting to promote its mobile app and loyalty program, leveraging data from its website, email, and in-store transactions to create personalised offers and recommendations. By delivering a consistent, seamless experience across touchpoints, the brand saw a 20% increase in app downloads and a 15% increase in loyalty program signups [12].

ASOS promoted its fashion and beauty products using cross-channel targeting, leveraging data from its website, app, and social media channels to create personalised product recommendations and ads. By targeting consumers with relevant, timely messages across devices, the brand saw a 28% increase in conversion rates and a 36% increase in average order value [13].


As the digital landscape continues to evolve rapidly, the future of marketing belongs to those who can harness the power of advanced targeting strategies. From AI and machine learning to programmatic advertising and contextual targeting, the tools and technologies at our disposal have never been more sophisticated or powerful.

By leveraging these strategies to deliver hyper-personalised, contextually relevant experiences across channels, marketers can drive engagement, loyalty, and revenue growth like never before. However, success in this new era requires more than just technology—it requires a deep understanding of consumer behaviour, a commitment to data-driven decision-making, and a willingness to experiment and innovate.

At SGI Consultants, we understand modern marketers’ challenges and opportunities, so we’ve developed the SOAR Marketing System. SOAR stands for Standout Branding, Orchestrated Connections, Amplified Reach, and Revenue Maximisation – four key pillars that underpin a successful digital marketing strategy.

By leveraging the principles of advanced targeting within the SOAR framework, we help our clients create targeted, effective marketing campaigns that drive meaningful results. Whether you’re looking to enter new markets, launch new products, or simply improve the effectiveness of your existing marketing efforts, the SOAR system provides a proven roadmap for success.

Suppose you’re ready to take your digital marketing to the next level and harness the power of advanced targeting for your business.

In that case, we invite you to learn more about SGI Consultants and our SOAR Marketing System. Contact us today to schedule a consultation and discover how we can help you achieve your growth goals.

[1] eMarketer, “UK Digital Ad Spending 2021”,
[2] Deloitte, “State of AI in the Enterprise”,
[3] WARC, “The Economist boosts digital subscriptions with AI-powered targeting”,
[4] Virgin Holidays, “How Virgin Holidays increased bookings by 33% with AI-powered chatbots”,
[5] eMarketer, “Programmatic ad spending in the UK 2022”,
[6] WARC, “Nestlé drives KitKat sales with programmatic advertising”,
[7] Sojern, “British Airways Increases Bookings with Sojern’s Programmatic Marketing”,
[8] GumGum, “Contextual Advertising: The New Frontier”,
[9] WARC, “Adidas drives brand engagement with contextual targeting”,
[10] WARC, “Unilever’s Knorr drives sales with contextual targeting”,
[11] Epsilon, “The Power of Me: The Impact of Personalization on Marketing Performance”,
[12] Starbucks, “How Starbucks Drives Growth with Personalized Mobile Experiences”,
[13] ASOS, “ASOS sees 28% increase in conversion rates with cross-channel targeting”,