Dear [name in here]: Tech go-slow ‘hits personalisation’

digital twoGartner’s 2019 prediction that personalised marketing would be dead as a Dodo within five years might have been greeted with ridicule at the time, but the company says nearly two-thirds (63%) of digital marketing leaders continue to struggle with delivering personalised experiences to their customers.

In a survey of 350 marketing leaders from November 2020 to December 2020, “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.

The firm reckons that part of the problem is that digital marketing leaders are still scaling their use of emerging technologies, such as artificial intelligence and machine learning, to align with their customer acquisition and retention goals. Gartner’s survey revealed that only 17% of firms are using AI/ML broadly across the marketing function.

Gartner for Marketers vice president analyst Noah Elkin said: “A comprehensive personalisation strategy and roadmap can be deciding factors in the results marketers achieve from their personalisation efforts, yet most marketing organisations lack an effective personalisation strategy – let alone one that is explicitly linked to desired business and customer goals.

“They should focus on addressing longstanding personalisation challenges by channeling their existing collection and use of customer data toward customer needs that align with business goals.”

Gartner insists the use of AI/ML technology is closely tied to personalisation objectives for marketers. In fact, 84% of digital marketing leaders believe using AI/ML enhances the marketing function’s ability to deliver real-time, personalised experiences to customers. Many digital marketing leaders see bringing automation, scale and efficiency to marketing activities across channels as the greatest value of AI/ML tools.

In marketing organisations not currently using AI/ML, trust remains a key inhibitor to more widespread adoption, the survey reveals. However, the trust barrier declines with increased usage – whereas three-quarters (75%) of respondents piloting AI/ML worry about trusting the technology, only just over half (53%) of those broadly using AI in the marketing organisation worry about trust in AI/ML. This is indicative of a steep but progressive acceptance curve, Gartner reckons.

To better address personalisation challenges, the firm says digital marketing leaders focused on strategy and execution should consider a number of factors, including:

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.

Leverage existing technologies first: Maximise what can be achieved with personalisation by using existing tools in conjunction with available data and content before committing to new technologies. Marketing organisations should use AI and ML tools to mature their efforts by driving greater relevance in marketing engagement and increasing influence over customer behavior.

Focus on change management: Approach the implementation of AI/ML technologies within a change management context, accounting for the impact they will bring to the organisational culture. Factor in staffing and training needs to build trust and bring the new technologies to life.

Not quite the death-knell for personalisation after all, then Gartner.

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