5 ways to improve CX and accelerate data-driven innovation

5 ways to improve CX and accelerate data-driven innovation

Digitization has changed the dynamics of business forever. Fundamental changes in consumer behavior and the growing shift to online channels over the past eighteen months accelerated digital transformation to the point where companies that have been unable to acclimatize have struggled to survive.

According to a study from McKinsey, digital offerings leapfrogged seven years of progress in a matter of only a few months. And the surge in digital adoption led to an exponential growth in data – data which companies are now looking to leverage to improve their competitive positioning and profitability in a revolutionized economy that thrives on data and analytics. So, as pervasive disruption continues and companies race to transform data into actionable insights —all while navigating privacy concerns and regulations — how can great customer experience (CX) strategies be shaped and data-driven innovation (DDI) flourish?

1. Forecast the future with (privacy-enhanced) predictive analytics

Traditional approaches to data analysis can’t always keep up with new standards and expectations. In a digital-first world, having the ability to foresee the future is a superpower that business leaders, particularly those focused on growth analytics (Chief Marketing Officers, Chief Digital Officers, Head of Customer Knowledge, Head of Data Monetization etc.), would love to have. Businesses already invest heavily in attempting to figure out where the market is heading and to anticipate what new or unexpected consumer behaviors are on the horizon; now, advancements in technology are making this easier.

Thanks to technological innovations, developments in predictive analytics are already shaping the future of digital marketing and customer experience. And with the predictive analytics market size estimated to grow from $10.5 billion in 2021 to $28.1 billion by 2027, businesses are adopting predictive modeling tools and big data technologies so that they can cash in on the benefits that come with having a deeper understanding of tomorrow’s consumer. Having the ability to utilize past and current data to forecast trends and behaviors allows companies to curate journeys, messaging and product recommendations that inspire consumer action. Not only this, but predictive insights also enable businesses to strategize for churn reduction and improve operational efficiency to gain an edge in the competitive CX landscape.

2. Unlock data silos for a 360-consumer view

What business leaders really want from data is the ability to improve and enrich customer experiences. Companies are collecting invaluable data all day, every day. Yet, often due to structural inefficiencies, poorly integrated technology systems and more recent regulatory concerns, that data often ends up trapped in silos. To put it into commercial perspective, insights from global executives found that data silos have been flagged as a key challenge by 90% of organizations in both 2020 and 2021, which highlights the lack of progress being made.

When data stagnates in silos, growth is hampered: it leads to an inability to efficiently evolve and scale processes; it allows inconsistent data (or a restricted view of data) to form the basis of critical decisions; and it prevents connected customer experiences from becoming a reality. Ironically, siloed data, which has often been considered to be more private due to restricted access within specific teams, actually carries significant privacy and security risks.

The need, therefore, for data strategies that promote wide-scale analysis over large-scale storage while protecting privacy is critical to business success. Although protecting data privacy and freeing data for analysis was long considered a juxtaposition, developments in the sophistication of privacy-enhancing technologies have highlighted that there no longer needs to be an either-or decision. On the contrary, businesses that leverage privacy management software that centralizes the measurement and mitigation of privacy risks can broaden the scope of data insights and boost the accessibility of longitudinal data for dynamic analysis while removing limitations surrounding data retention and storage under privacy regulations.

3. Navigate data change management and data governance across your organization

In order to improve business outcomes, drive growth and fuel innovation, there is now a critical need to treat data as a strategic asset so that its value is leveraged right across the business ecosystem. While every company is looking at some form of data strategy, many are struggling to overcome everyday challenges surrounding data integration, data literacy, data quality, data risks and more. With data now the lifeblood of an organization, and the only way to keep it flowing smoothly is to create and organizational shift through (1) an effective data change management process and (2) effective data governance and data stewardship.

Operationalizing a future-ready data strategy requires change management and agile data governance to solve key business issues through the alignment of people, processes and technology so that business outcomes can be achieved. Technologies and processes are designed for people. If they are not viewed as a catalyst for success, then people will become resistive to change. And if people lack awareness or understanding over why certain processes or technologies are necessary then the speed of response to change will be sluggish. Similarly, data governance provides oversight of the data that drives a business; it creates the framework for processes and policies surrounding data and the everyday management of that data. Combining the tenets of change management with an understanding of how agile data governance can empower analytics functions will enable data strategies to be operationalized efficiently, effectively and compliantly.

4. Strive for transparency, accountability and people-centred processes

Organizations that intend to stand the test of time should consider embracing and scaffolding brand promises that extend beyond their products More than ever, consumers are gravitating towards brands that align with their political, cultural and social values. And with consumers vocalizing their willingness to switch to different vendors and spend their money elsewhere when they perceive a misalignment in values and a breach of trust when it comes to their data, businesses have little choice but to pivot towards privacy-centric strategies that strengthen their market position by leveraging privacy as a commercial differentiator.

Companies are understanding that long-term consumer loyalty now hinges on trust and responsible data practices, which provide privacy-conscious consumers with the confidence and reassurance that their data is safe and being used responsibly. Those who quickly attune to the increasing consumer calls to protect privacy over profit, and to be seen as people rather than patterns in the big data engine, are those who will gain a competitive advantage. As such, there is now a surge in the adoption of privacy-enhancing technologies that can help businesses to pro-actively demonstrate their commitment to transparent and accountable data practices that pivot around people-centred strategies.

5. Power data strategies with privacy-enhanced data

Accelerated access to richer, more accurate data analytics is key to supporting business priorities and serving customers with personalized experiences. This requires collaboration across functions to overcome everyday data challenges and to develop a sustainable data infrastructure that provides the resiliency and agility needed to adapt to the every-changing regulatory landscape. 

When businesses opt for a privacy-centric approach to data management, they can simultaneously maximize data value while mitigating risks. Looking towards frictionless, interoperable privacy management software that can facilitate centralized governance across de-centralized teams is now key to overcoming data silos, data waste and data risks. When companies can measure their privacy risks, they can mitigate those risks through targeted de-identification and mobilize free-flowing, privacy-compliant data right across their business ecosystem. The bottom line is this: privacy, personalization and predictive modeling can coexist in a big data economy. Customer trust can be regained and retained when companies demonstrate responsible data use. And innovation can thrive when privacy is leveraged as a commercial differentiator.

Test-drive Trūata Calibrate: book a 15-minute demo or contact us to learn how our software can help you to overcome critical data challenges while you focus on building better customer experiences and driving innovation with privacy-protected analytics.