How Customer Data Strategies Will Advance Digital Transformation in 2021

What are your customer data strategies for 2021: In this article by Redpoint CTO, you would get relevant insights on how to build customer data strategies for the future.

Leveraging customer data and analytics have been integral components of successful digital transformations for some time. Dramatic changes in customer behaviors in response to the pandemic accelerate the need for a customer data strategy that delivers a holistic experience, irrespective of channel. Evolving consumer behaviors include a preference for safe, contactless experiences such as buy online, pick-up in-store (BOPIS), curbside pick-up, and an increase in online, digital-first experiences – all of which increase the pressure on brands to meet the expectation for a holistic experience.

The unprecedented rate of change exposes the gap between data-driven, digital-first organizations and those still dependent on manual, inefficient processes for engaging with customers. The divide will become a chasm in the coming year. And with many of the new customer behaviors expected to become a fixture of an evolving new reality, 2021 will be a make-or-break opportunity for brands to be on the right side of the digital divide.

An AI and Machine Learning Tipping Point

A customer data strategy that includes AI and machine learning will be a foundational requirement in 2021 and beyond to deliver innovative, personalized experiences at scale that drive revenue growth. Advanced technologies power a data strategy that meets the expectation from today’s always-on, connected consumers who expect that brands will recognize they are the same customer across an omnichannel customer journey. In a recent Dynata study commissioned by Redpoint, 70% of consumers surveyed said they will shop only with brands that personally understand them.

A personal understanding and recognition presuppose that a marketing team has the capability of delivering real-time interactions that are in the context and cadence of an individual customer journey. For a dynamic journey that touches multiple channels, real-time could mean minutes, seconds or even milliseconds. Wherever or whenever a customer appears, a brand must be ready with the most relevant, next-best-action pursuant to that specific moment in the journey. Automated machine learning that powers a real-time decision engine provides marketing teams with the ability to provide a next-best-action, at scale, that is hyper-relevant to a customer’s journey. For this reason, I see the coming year as a tipping point for AI and machine learning to finally receive their due as essential tools for powering differentiated customer experiences.

Start with Customer Data, Overcome Data Hurdles

To differentiate in this rapidly evolving, digital-first environment, marketing teams must first get their data foundation in order, one that support a customer data strategy that leads to superior customer experiences. Even for data-driven organizations, a solid data foundation has been a challenge. In a Harris Poll sponsored by Redpoint, marketers identified real-time engagement (50%) and customer understanding (48%) as the biggest challenges to delivering an exceptional customer experience. Marketers identified a lack of data integration (28%) and channels that lagged the customer cadence (27%) as among the three biggest obstacles preventing CX goals.

Because of the inherent difficulties, I foresee roughly 50% of digital transformation in progress will stall due to incomplete or lacking effective customer data strategies in the coming year. To fully embrace the power of AI and machine learning, marketing teams must have their customer data in order, combining data from every source for a single customer view that is the foundation for deriving a next-best action.

Brands feel the pressure and recognize the urgency to convert to a transformed digital state, but they’re often unsure how to properly execute a digital strategy. To succeed in 2021 and beyond, however, brands stop equivocating and begin to take the necessary steps to get their customer data in order. It’s that important. In the Harris Poll, 37% of consumers said they will not do business with any brand that fails to offer a personalized experience.

To Win with AI, Change Your Mindset

To break through the barriers, organizations must escape the paradigm of believing manually written algorithms are necessary for creating differentiated customer experiences at scale. There is a general misconception that to humanize a customer engagement requires human involvement – what better way to mimic an authentic, real, personalized and emotive experience than to derive it from a marketing team with actual human experiences?

There are a few problems with this thinking in terms of creating unique, relevant omnichannel customer experiences. First, of course, is the fact that what is relevant, important or meaningful for one customer is likely not for another. Second, manual coding cannot scale broadly across an enterprise, or at least, not economically, and are thus restricted to broad audience segmentation. Selecting an audience of men 18-25 will not provide marketers with an understanding of an individual customer’s preferences needed to create a hyper-personalized experience. Third, manually written algorithms generally require data scientists to build models based on a desired business objective or metric. If an objective or a target audience changes, models must be taken offline and re-written – which means they are inadequate for keeping up with a customer, in real-time, throughout a dynamic customer journey.

The good news is that many marketing teams are at least somewhat aware of the limitless potential of AI and machine learning for creating differentiated customer experiences. Once they break free from a dependence on manually written algorithms, the sky will be the limit. Even if they fall into a hybrid approach where only high value models are handwritten and others machine generated, they will be much better off than forcing every model to be hand coded.  2021 will be the year for organizations to finally have the full faith and trust in the power of advanced technologies to drive personalized experiences as the core of a customer data strategy.

Jump on Board – Or Pay the Price

It’s important to note that these predictions aren’t out of the blue; many data-driven companies are ahead of the game, so to speak, having already embraced the power of AI and machine learning.

One Redpoint client, for instance, uses automated machine learning and a real-time decision-making engine to provide hyper-personalized, relevant next-best actions within milliseconds of a customer engagement on multiple online and offline channels – up to 25 million decisions every day. The customer, a web services company, attributed the platform to a double-digit revenue increase.

This is just one example of how in an increasingly digital-first world, putting customer data at the center of an engagement strategy and leveraging intelligent automation tools to provide a next-best action delivers significant results. The technology is available for any company to do the same. Rapidly changing customer behaviors should open more eyes in 2021 that the time to dither is long gone. This really could be the last, best chance for organizations to be on the right side of the digital divide.