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Study: Low adoption of AI sees marketers struggling with personalised experiences

Study: Low adoption of AI sees marketers struggling with personalised experiences

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Nearly two-thirds (63%) of digital marketing leaders still struggle with delivering personalised experiences to consumers. According to Gartner's study which surveyed 350 marketing leaders from November to December last year, “delivering personalised experiences” and “mapping digital messages to audience channel preferences” each increased in severity by eight and six percentage points, respectively, from a 2019 survey.

Part of the challenge is that digital marketing leaders are still scaling their use of emerging technologies, such as AI and machine learning, to align with their customer acquisition and retention goals. The survey found that only 17% are using AI and machine learning broadly across the marketing function.

According to Gartner, the use of AI and machine learning technology is closely tied to personalisation objectives for marketers. In fact, 84% of digital marketing leaders believe using AI and machine learning boosts the marketing function's ability to deliver real-time, personalised experiences to consumers. Many digital marketers also see bringing automation, scale and efficiency to marketing activities across channels as the greatest value of AI and machine learning tools.

digital marketing leader survey release 1 figure 1

Trust remains a key inhibitor to more widespread adoption in companies that are not currently leveraging AI and machine learning. However, with increased usage comes a dip in the trust barrier. While 75% of respondents piloting AI and machine learning worry about trusting the technology, only 53% of those broadly using AI and the organisation worry about trust in these two areas.

To overcome personalisation challenges, digital marketing leaders should consider the following when creating a strategy and execution:

1. Create a personalisation roadmap: Develop an organisational framework that ties the deployment of emerging technologies to strategic digital marketing objectives. Factor in near-term costs and longer-term ROI projections as well as quantifiable impacts on the digital experience.

2. Leverage existing technologies first: Maximise what can be achieved with personalisation by leveraging existing tools in conjunction with available data and content before committing to new technologies. Companies should use AI and machine learning tools to mature their efforts by driving greater relevance in marketing engagement and increasing influence over customer behaviour.

3. Focus on change management: Marketers should approach the implementation of AI and machine learning technologies within a change management context, accounting for the impact they will bring to the organisational culture. Companies should also factor in staffing and training needs to build trust and bring the new technologies to life.

Photo courtesy: 123RF

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