Customer experience has outpaced pricing and product as the key brand differentiator in recent years. According to PWC research, 86% of buyers are ready to pay more for superior customer experience. Failing to deliver contextual experiences in these extraordinarily challenging times is a recipe for disaster. As customers become more digital-savvy and expect personalized omni-channel experiences, brands need to bridge ‘personalization' gaps on a war footing by making the most of their customer data.
Data-driven personalization enables brands to maintain customer loyalty, generate faster ROI, and discover new growth opportunities. Although brands exhibiting customer intimacy succeed in delivering tailored experiences, customers are always wary of how their personal data will be collected, stored, and used by various service providers. Privacy concerns often impede personalized marketing efforts. As various nations implement stringent data regulations (such as GDPR and CCPA) to ensure customer data protection and privacy, marketers should formulate new strategies to generate value from personal data.
The current marketing conundrum seems to be vicious, as businesses need to avoid compliance breaches and huge penalties, as well as procure and put customer data to effective use. Organizations can establish their road to success, only if they strike the right balance between personalization and privacy.
According to Gartner, despite privacy concerns, millennials take brands into their confidence and share more information in exchange for personalized experiences and improved convenience.
This draws our attention to the privacy paradox - the conspicuous disparity between customers’ concerns about privacy and their actual online behavior:
Penny Gillespie, VP Analyst at Gartner says that organizations can hack the privacy paradox by combining identity data with behavioral data. To avert compliance risks and attain profitability, businesses should take the following measures:
Gather only the essential data
Collect only the essential data that helps deliver value to your customers. Consumers expect personalization to help them during the purchase phase. If they get more value in exchange for their data, they will be ready to disclose more information. Nearly six in ten customers would be ready to share details, such as location and lifestyle data, with their banks and insurers in exchange for faster loan approvals and low-priced premiums.
Brands should collect data not just to establish that they know the customer, but to provide experiences and services that matter the most ‘in-the-moment’. Amazon’s personalized product recommendations (for example, suggesting the user to buy a back case or a screen guard along with a mobile handset) is a classic example of leveraging data to deliver customer value.
Make data collection and usage transparent
Company websites, mobile apps, and other business software should provide clear descriptions on how and what kind of personal data they collect. A survey held by the University of South Carolina found that 50% of smartphone users in the U.S. would be willing to share their location data, only if they understand the benefits. Businesses should design use cases and highlight how they can make tailored offers, if they know more about their customers.
You must provide links to the privacy policies adopted by your brands and explain them in simple language, avoiding legal jargons. Allow the customer to decide what data they will be sharing with you, who else will be able to access the data, and how long it will be stored in your database. Introduce simple ways to request customer intervention while collecting data, such as the usage of cookies.
Implement robust data governance practices
Most organizations, starting with the C-level executives, ignore data governance as a mere set of policies. According to McKinsey, a large number of organizations waste 30% of their enterprise time on low-value tasks due to the lack of quality-assured data governance. Besides value generation, solid data governance prevents enterprises from getting exposed to costly compliance and regulatory risks.
Effective data governance should comprise a targeted data strategy driven by the governance stewards designated from different departments, across all levels of the organizational hierarchy. These stewards should set the standards for data governance and direct employees to become data protection champions. It’s also important to sync the data governance strategy with business priorities and overall corporate strategy. The right level of data governance allows organizations to identify low risk enterprise data that can be shared with employees and high risk data like Personally Identifiable Information (PII), which should be kept under lock and key.
Data governance is highly critical when businesses try to take advantage of analytics, digital, and other transformative opportunities that can enhance their CX. It’s time enterprises start integrating data governance as a key component of their organizational strategy.
Ensure data compliance and protection
The average total cost of data breaches has reached an all-time high since the outbreak of the COVID-19 pandemic. According to a study by IBM, there was a 10% surge in the average total cost of a breach in 2020-2021. Compliance failure being one of the top causes. Many legal and compliance teams are yet to acquaint themselves with the intricacies of data privacy laws. Increase in international data transfers, digital transformation, cloud migration, remote working, huge datasets, and the changing business and technology landscape will only compound such problems.
To implement a systematic compliance framework, organizations should first define and document the standards they wish to adopt to manage personal data. The strategy should encompass all the key stakeholders and organizational units. It’s important to hire SMEs who can develop legally compliant policies and practices. To protect PII and Sensitive Personal Information (SPI), companies must identify and tag personal data when it’s collected. With a robust consent management platform, organizations can ensure the privacy of PII and allow users to control how the data will be shared.
Read our case study: How we built a diverse and scalable consent management platform for a leading telecom giant in Asia
Brands should devise proper measures to track, locate, and safeguard personal data in accordance with the recommended legal standards. No system is 100% foolproof. Organizations must regularly revisit their data breach response plan and escalation process to mitigate cyber intrusions and compliance infringements.
With the emergence of new data compliance and privacy laws. the enterprise risk of collecting, storing, organizing, and using customer data to deliver personalized services is growing day by day. Equally challenged are the marketers who need diverse sets of user data to seize every moment they interact with their customers. Good data is the foundation of every personalization effort. Personalization champions adopt the ‘crawl-walk-run’ approach to create a customer-centric culture with engaged and motivated employees.
“If you can’t fly then run, if you can’t run then walk, if you can’t walk then crawl, but whatever you do you have to keep moving forward.”
Inspired by these words of Martin Luther King Jr., the crawl-walk-run approach emphasizes that businesses should set mini goals and realistic milestones to progress from 0 to 100 over a period of time, step-by-step.
Crawl personalization focuses on using easily collected data and content. For instance, customer’s geolocation data can be used to personalize a section of your homepage with the registration details of an event you’re hosting or sponsoring in the city. You can also set up drip email campaigns to target users who’ve downloaded your case study or visited specific pages on your website.
The walk personalization approach focuses on sharing additional content and collecting more data to target precisely defined user groups. For instance, you can send out reminders to the users who’ve registered for an event via your website or mobile app. If a particular page on your website drives more traffic, serve the readers with more relevant content to improve contextualization.
The run approach requires extra data collection and research, extensive content creation, and integration with other systems to create a personalized, long-term impact. For example, the data gathered by your CRM can be used to personalize content on sites or mobile apps. The run approach also involves leveraging omnichannel experiences, such as enabling the customer to fulfill an order via e-commerce mobile app and later sending a discount voucher via email.
The crawl-walk-run approach underscores that the evolution of business technology should align with the evolution of each business. It helps companies to understand their customers better and improve personalization across every touchpoint.
Traditional digital products require complex customizations and integrations to deliver personalization. E-commerce applications, content management systems, and other traditional marketing suites lack integration, rely on legacy tech, operate in silos, and are slow in catching up with the modern customer. Digital Experience Platforms (DXPs) like Drupal allow businesses to fill the personalization gap by providing a unified user experience across all channels and activities. DXPs come equipped with a well-integrated and cohesive set of technologies that drives personalization throughout the customer journey.
By 2025, the global DXP market size is expected to be at USD 15.90 billion. Instead of building and launching a whole page in WordPress, a DXP enables marketers to create content blocks or components that can be generated dynamically. The emergence of microservices architecture, headless CMS and commerce, and composability make DXPs a highly popular personalization tool among marketers. Built-in algorithms powered by AI, API-first architecture, low code, open architecture, robust tools and capabilities, disaster protection, and a strong data foundation are the components that make up modern DXPs. All these qualities enable DXPs to leverage real-time personalization and segmentation.
To strike the right balance between data-driven personalization and user privacy, businesses should rethink their data policies and compliance practices. Assess the following:
Does your organization’s personalization program count your customer's security and privacy experience?
What is the current state of your security and privacy tech stack?
How are you generating analytical insights from personalization without triggering any costly cyber breaches?
How secure is your enterprise’s cloud system?
Is your enterprise maintaining a register for tracking system risks and critical IT and data assets?
Are your employees aware of the need to protect customer data?
Delivering personalization at scale, while respecting data privacy regulations at the same time, requires pondering over the above and many other questions.
Are you caught up in the middle of the personalization and data privacy quandary? Untangle the knots by talking to our consultant.