Welcome to the latest instalment of our AI series, where we examine the trends and tools set to reshape the marketing landscape.
For businesses looking to improve customer experiences and boost marketing ROI, AI-powered technologies are becoming valuable resources. But which innovations are set to make the biggest impact? In this article, we explore three standout technologies that can help marketers work more efficiently and creatively, driving more transformative results.
1. Improving customer experiences (CX) with natural language technologies
A trio of technologies—Natural Language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG)—are together transforming how brands interact with consumers in real time. Picture a customer typing a query into an online chat function or calling a support line:
- NLP interprets their words and the meaning behind the shopper’s message, whatever the format (whether text or audio).
- NLU delves deeper to understand the true intent and context of their request.
- NLG then generates a natural, helpful response.
For example, a brand could use these AI tools to help their digital assistants identify when a consumer is expressing frustration, recognise that the issue is related to a late delivery and generate a sympathetic reply that includes tracking information.
Not only does this streamline support, but it can also foster customer loyalty by providing fast, relevant and personalised responses.
However, these systems do require careful implementation and ongoing training.
Poorly trained digital assistants can misinterpret queries and provide irrelevant information, which can frustrate customers, diminish brand trust and even trigger regulatory and financial penalties.
But given the right direction, virtual assistants could help deliver seamless customer experiences, assisted by the latest AI breakthroughs.
2. Unlocking insights with Synthetic Data Generation (SDG)
Synthetic Data Generation (SDG) is one of AI’s most innovative tools, especially for brands looking to enhance their data capabilities without breaching privacy.
By creating artificial data that closely mimics real customer data, SDG helps to fill any customer profile gaps within datasets.
This means your AI and Machine Learning (ML) models will be working with more robust and balanced input.
An essential part of the process when developing accurate and effective AI and ML models that help to reduce programmer bias and enhance privacy safeguards.
Picture a scenario where your customer data isn’t enough to train a ‘lookalike’ model accurately.
SDG can produce artificial data points that follow the patterns and traits of real-life buyers, helping marketers identify new, high-potential audiences to target.
For example, a B2B software company could use SDG to simulate the attributes and behaviours of their ideal customer, helping them identify and target new prospects with similar characteristics.
Or a management consulting firm could apply synthetic data to test the effectiveness of different outreach strategies, without risking their real client relationships.
SDG can also be used for testing and optimisation.
For instance, a B2B manufacturer could use SDG to model different pricing scenarios for their products, assessing how various strategies would impact sales and profitability – without exposing sensitive information about their real customers
When used effectively, SDG can turn data gaps into meaningful insights, but it’s important to start with a well-planned strategy to ensure the data remains useful and relevant.
3. Advanced personalisation with AI-driven Customer Journey Optimisation (CJO)
AI-powered Customer Journey Optimisation (CJO) can analyse patterns to guide individuals down the most conversion-friendly pathways, enhancing the impact of your marketing efforts.
Instead of following predefined routes, AI-powered CJOs use predictive analytics and reinforcement learning to guide consumers along the path most likely to lead to a sale. According to The Baynard Institute, cited by Shopify, 70% of users abandon their shopping carts.
When this happens, AI-powered CJOs can analyse past customer behaviours to identify similar patterns and trigger personalised follow-ups—such as targeted emails or retargeting ads—to encourage users to complete their purchases.
This same approach can be applied to B2B marketing, enabling sales teams to engage leads more effectively.
The result? Higher conversion rates, lower customer acquisition costs, greater customer lifetime value, and a seamless customer experience. However, as sophisticated as AI-based CJOs undoubtedly are, they still require a solid dataset to learn from and must be carefully aligned with brand goals.
Why skilled strategy still matters
With the right implementation, AI technologies like NLP, SDG and CJO can deliver dividends in customer experience, data insights and personalisation. So, it’s no wonder that according to Deloitte’s Spring 2024 CMO Survey, 75% of marketers are already using some form of AI.
However, these innovations don’t exist in a vacuum; they are only as powerful as the strategy behind them.
Are you ready to embrace the future of AI-enabled marketing?
If you’re looking for strategic support to refine your marketing, we’d be happy to chat. Reach out today to find out how we can help you.
