Achieving superior results: a bridge between data and personalization


Nowadays, personalization encompasses and goes beyond those plain approaches, delivering considerable, yet mostly undiscovered, possibilities in the quest towards superior customer experiences.

Posted on

Among the several marketing efforts and tactics today’s’ businesses are aiming to apply and implement within their organization, personalization is one of the most convenient endeavours. It can be defined as an overall contextual marketing practice, which is extremely adaptive to your customers’ time-changing needs and expectations. It is demonstrated to drive your marketing efforts towards a refined customer engagement, and a meaningful long-lasting relationship with your audience. Nevertheless, personalization could exceed being a basic marketing tactic, based on old-fashioned and possibly irrelevant segmentation techniques, or a mix of decisions only supported by demographic data. Most businesses conceive personalization as using the customers’ names on their email marketing practices, sending specific offers for special occasions, such as the users’ birthdays, or merely adapting content based on consumers’ browsing or purchasing history.

Personalization should be an overall strategic approach, which might be conjugated with customer journeys, omnichannel efforts, and customer centricity. Having a unique, robust, and solid strategy incorporating personalization as one of the main attainable goals and pillars, is a desirable and a core imperative. Hence, your organization is recommended to sought-after creating a complete 1:1 experience for its customers. In order to attain such a result, a few organizational adjustments are required, generally starting from your strategy, which also involves balancing different practices in an integrative, iterative and interactive process. Customer centricity, improved customer experiences, omnichannel efforts, and practical tools need to go hand in hand with personalization initiatives, so as to obtain worthy and meaningful outcomes. Luckily, today’s’ advanced technologies might provide significant support in delivering high-tailored 1:1 personalized experiences. The success of your personalization efforts lies in data and bridging those data to your initiatives.

Bridging data and personalization

The actual amount of available data and the numerous possibilities to collect, retain, and analyze those data has brought many businesses to a data overabundance. As a consequence, organizations do not hold all the required resources to extrapolate useful insights from those data. Most of the times, businesses do not possess the time to process all information responsively to their customers’ constantly changing needs and expectations. On top of it, as an aggravating factor, misleading strategies to efficiently and effectively manage those data and analytics processes often are in place. Therefore, before opting for any data collection and analysis tools, marketing automation platforms, or scaling up those processes, a business considering to invest in personalization efforts is recommended to answer a crucial question. How to translate knowledge developed from data in 1:1 individualized experiences, ultimately creating differentiated and competitive value for your organization and its customers?

The solution lies in bridging data and personalization, by modelling data to each individual, across channels, in order to settle a form of personalization addressing every single customer experience. Hence, your business is recommended to start adopting real-time targeting practices based on live business contextual data, in order to collect time relevant insights. Moreover, it is suggested to focus on both platforms and marketing automation investments which would leverage live data available, real-time elaboration of those data, making immediate advancement in customer insights in order to elaborate adaptive personalized initiatives. Using more refined personalization methods, such as solutions offered by automation platforms (e.g. machine learning), would support your business in collecting several customer incentives over time, and observing how those incentives impact in real-time over users’ behaviours.

Finally, another suitable practice is to opt for cross-referencing different kind of data, such as segment and content analysis, behavioural data, purchasing history and patterns, demographics, loyalty programs, etc. Those might be aggregated and developed into a unique, ideally individual, predictive model of your customers’ future behaviour. Besides, this approach would secure your business against one of the major barriers to implementing effective personalization: siloed and static data. From this perspective, having a unified customer data platform would allow your business not only to avoid this challenge but to smoothly incorporate predictive analysis models as a part of your strategy. This, in turn, would secure your business into ultimately bridging the gap between data and personalization, achieving superior results when it comes to contextualized, high-tailored, 1:1, and seamless customer experiences.