Emerging technologies are key to executing an effective personalization strategy for digital marketing
Nearly two-thirds (63%) of digital marketing leaders continue to struggle with delivering personalized experiences to their customers, according to Gartner. In a survey of 350 marketing leaders from November 2020 through December 2020, “delivering personalized experiences” and “mapping digital messages to audience channel preferences” each increased in severity by eight and six percentage points, respectively, from a 2019 survey (see Figure).
Part of the problem is that digital marketing leaders are still scaling their use of emerging technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), to align with their customer acquisition and retention goals. Gartner’s survey revealed that only 17% are using AI/ML broadly across the marketing function.
“A comprehensive personalization strategy and roadmap can be deciding factors in the results marketers achieve from their personalization efforts, yet most marketing organizations lack an effective personalization strategy – let alone one that is explicitly linked to desired business and customer goals,” said Noah Elkin, vice president analyst in the Gartner for Marketers practice. “They should focus on addressing longstanding personalization challenges by channeling their existing collection and use of customer data toward customer needs that align with business goals.”
Figure: Challenges in Executing Digital Marketing Strategy
Source: Gartner (2021)
The use of AI/ML technology is closely tied to personalization objectives for marketers. In fact, 84% of digital marketing leaders believe using AI/ML enhances the marketing function’s ability to deliver real-time, personalized 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 organizations not currently leveraging AI/ML, trust remains a key inhibitor to more widespread adoption. However, the trust barrier declines with increased usage – whereas 75% of respondents piloting AI/ML worry about trusting the technology, only 53% of those broadly using AI in the marketing organization worry about trust in AI/ML. This is indicative of a steep but progressive acceptance curve.
To better address personalization challenges, digital marketing leaders focused on strategy and execution should consider the following:
- Create a Personalization Roadmap: Develop an organizational 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: Maximize what can be achieved with personalization by leveraging existing tools in conjunction with available data and content before committing to new technologies. Marketing organizations 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 organizational culture. Factor in staffing and training needs to build trust and bring the new technologies to life.