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In today’s rapidly evolving digital landscape, consumer brands face unprecedented challenges. From geopolitical uncertainties to shifting consumer behaviours, the marketing landscape is more complex than ever.

Yet, many of us in the industry find ourselves held back by legacy systems that hinder our ability to adapt and thrive in this new environment.

This post explores how AI-driven marketing can help overcome these barriers and revolutionise our approach to consumer engagement.

The AI Revolution in Marketing

Artificial Intelligence (AI) has made remarkable strides in recent years.

According to a 2021 PwC survey, 52% of companies have accelerated their AI adoption plans due to the COVID-19 crisis. In marketing, AI is transforming everything from customer segmentation to content creation.

These advancements are powered by sophisticated AI models and tools.

For instance, OpenAI’s GPT-3 is revolutionising natural language processing, enabling more human-like interactions in chatbots and content creation.

Overcoming Legacy System Barriers

While the benefits of AI are clear, many consumer brands struggle with implementation due to legacy systems.

Here’s a step-by-step approach to overcome these barriers:

1.     Audit Existing Systems

Start by thoroughly assessing your current technology stack. Identify areas where legacy systems are holding you back and prioritise them for upgrade or integration.

2. Implement a Customer Data Platform (CDP)

A CDP can unify customer data from various sources, including legacy systems.

This creates a single source of truth for AI models to work from. Platforms like Segment or Tealium offer robust CDP solutions that integrate well with existing systems.

3. Adopt Cloud-Based Solutions

Cloud platforms offer scalability and easier integration with AI tools. They can also help bridge the gap between legacy systems and newer technologies.

Consider solutions like Amazon Web Services (AWS) or Google Cloud Platform, which offer a range of AI and machine learning services.

 

4. Start Small and Scale

Begin with pilot projects in specific areas, such as personalising email campaigns or optimising social media posts.

This allows you to demonstrate value quickly and build support for larger initiatives. For example, you might start with an AI-powered tool like Phrasee for email subject line optimisation.

5. Invest in Training

Ensure your team is equipped to work with new AI tools. According to a Deloitte survey, 68% of executives say that skills gaps are holding them back from AI implementation.

Platforms like Coursera offer courses on AI and machine learning that can help upskill your team.

6. Leverage APIs

Many AI tools offer APIs that can integrate with existing systems. This allows you to add AI capabilities without completely overhauling your infrastructure.

For instance, IBM Watson’s Natural Language Understanding API can be integrated into existing customer service platforms to analyse customer sentiment.

7. Prioritise Data Quality

AI models are only as good as the data they’re trained on.

Implement data cleansing and governance practices to ensure your AI initiatives are built on a solid foundation.

Tools like Trifacta can help with data preparation and quality management.

Case Study: AI Success in Consumer Brands

Consider the success of Sephora, a leading beauty retailer.

By implementing AI-driven personalisation recommendation initiatives, Virtual Artist and Color IQ powered by machine learning algorithms, Sephora saw a 11% increase in conversions from product recommendations.

Their AI system analyses customer data from multiple touchpoints, including in-store interactions and online browsing behaviour, to deliver highly relevant product suggestions.

Looking Ahead

As we navigate the complexities of modern marketing, AI offers a path forward for consumer brands burdened by legacy systems. By taking a strategic, step-by-step approach to AI implementation, we can unlock new levels of customer engagement and business performance.

The journey may seem daunting, but the potential rewards are immense.

As McKinsey reports, AI has the potential to deliver additional economic output of around $13 trillion by 2030, making it one of the most important commercial opportunities in today’s fast-changing economy.

Emerging AI technologies like reinforcement learning models are set to further revolutionise marketing. These models, like those used by DeepMind in game-playing AIs, could optimise marketing strategies in real-time, adapting to consumer responses and market conditions on the fly.

In conclusion, while legacy systems may present challenges, they need not be insurmountable barriers to digital transformation.

With careful planning and a commitment to innovation, consumer brands can leverage AI to not just keep pace with change, but to lead the way into a new era of marketing excellence.

By embracing tools like GPT-3 for content creation, machine learning recommendation engines for personalisation, and reinforcement learning for strategy optimisation, brands can create more engaging, effective, and efficient marketing campaigns than ever before.

The future of marketing is AI-driven, and the time to start that journey is now. Are you ready to transform your marketing strategy with the power of AI?