Implementing data and analytics in APAC region to optimize CX

Data and analytics in APAC region

Customer data and analytics are integral to creating personalized, relevant customer experiences. In the digital age, where customers are 51 percent more likely to switch brands if unsatisfied – as revealed by CX Network research – companies must utilize data and analytics to create enhanced customer experiences if they want to stand out from the crowd.

CX Network’s Realities of customer experience in APAC: 2021 report found that more than one-third of CX professionals based in the Asia-Pacific (APAC) region (36 percent) noted that data and analytics were one of the top-10 CX trends across APAC. Additionally, the report found that 24 percent of APAC CX practitioners cited siloed customer data as one of their top CX challenges.

By using customer data and analytics, businesses can tailor customer experiences according to consumer preferences at scale. This personalization can be very beneficial, as research by Instapage found that 74 percent of customers are ‘frustrated’ by website content that is not personalized.

Achieving success in this area, however, requires time and care to hone the data to be as beneficial as possible. Personalization requires high-quality data practices and impeccable data management and hygiene. Additionally, companies must unlock the power of first-party data.

Likewise, when implementing customer service solutions, it is imperative that companies action voice of the customer data to ensure they are providing their customers with what they actually want.

This benchmarking workbook, compiled by CX Network and Epsilon, provides insights and learnings from Johnson & Johnson, Huawei and Mars Inc. on overcoming the data, insight and analytics challenges those in the APAC region face.

Current methods of collecting and storing customer data

Customer data is integral to building relevant customer experiences. With the digital marketplace flooded with options for customers, many brands are relying on their use of customer data to create superior CX that attracts and retains customers. However, there are number of common data management mistakes that companies make in this quest for superior CX, which can harm their progress towards their goal.

Shivkumar Ananthakrishnan, director of strategic consulting at Epsilon APAC and MEA, explains the thoughts that lead to these data management mistakes:

1. Thinking data management is all about hiring analytics and data scientists.

Companies need to inculcate a culture that data and analytics is a contact team sport. Co-creation and partnerships with business, data and tech teams is the recipe for growth.

2. Building the solution without customer insights in mind.

Companies need to embed insights into the decision making from day one with a mindset of last mile empathy and constant improvements.

3. Creating a solution without a roadmap.

Companies need to think of investments backing a strong roadmap that balances delivering today and start early to solve for tomorrow’s problems.

“Companies need to be empowered to execute on its value creation imperative – this requires accelerating its shift to a more effective platform model, delivery processes aligned to rapid value creation through data, analytics, and a stronger engagement model with the consumers.”

Shivkumar Ananthakrishnan

Director of strategic consulting at Epsilon APAC and MEA

Ensuring data infrastructure to enable CX optimization

It is important for data to be sorted through and identified, to having avoid an abundance of data that is not being acted on. To better understand the data available across the entire company, David Wray, global accounting and reporting senior director at Huawei, suggests storing all data in a repository such as a data lake or other cloud environment.

“This will allow you to start to extract value from the data, whether its structured or unstructured, [in the form of] intelligent analytics insights,” Wray remarks.

Wray also notes that companies should make a conscientious choice about their master data management. Businesses can execute this by giving common naming conventions to data points and keeping the same terms for that data point throughout the company. By keeping these naming conventions consistent across all departments, companies can map and connect the data to other related and relevant pieces of information.

By storing and naming data using these solutions, companies can also remove silos and ensure that all departments have full visibility on shared customer data enabling each department to create optimized customer experiences.

Also read: CX Automation in APAC

Applying data for CX personalization

Customer data is integral to personalization. When looking to provide the infrastructure for personalization, companies should look to utilize customer data and signals in conjunction with a 360-degree view of the customer. This ensures that brands are able to accommodate customer’s changing needs, wants and pain points.

Epsilon’s Ananthakrishnan explains that it is critical to personalization that brands are able to identify consumers consistently across channels and devices, recognize consumer need states and respond in real-time with the most appropriate messaging.

“In all practicalities, most consumers now truly expect brands to be using big data and personalizing content. Because if you do not, they will go to someone who will,” he says.

Case study:

How Johnson & Johnson used customer data for personalization

As part of its growth strategy, pharmaceutical company Johnson & Johnson (J&J) Taiwan wanted to build closer consumer relationships by acquiring more high-value consumers and engaging with them effectively across the consumer lifecycle. The company wanted to improve consumer lifetime value to boost customer retention, revenue and profitability. The company, however, only had access to basic, non-model-driven customer segmentation. As result, J&J partnered with Epsilon to enable the brand to activate first-party data for effective customer engagement.

Also read: Personalize CX through the power of conversation

To better analyze J&J’s customer base, Epsilon employed a robust data acquisition strategy, and a reporting and analytics framework, split across four strategic consumer segments and supporting experience paths.

With the framework in place, J&J can now:

Enable deliberate contact and targeting strategies to increase invoice-based loyalty response and website engagement. Create potential opportunity gain analysis to determine the impact of non-targeted consumers on purchase behavior. Develop and translate insights into personalized email recommendations to ensure the most relevant communications to drive engagement.

Using first-party data to gain first mover advantage

First-party data refers to any data a company collects directly from its customers. As this data comes directly from customers, this allows businesses to better connect with customers and understand their preferences. This allows them to engage more efficiently with both potential and established high-value customers. Epsilon’s Ananthakrishnan says that through first-party data, companies can understand:

1. Demographics:

Refers to general characteristics of the population. These are usually socioeconomic in nature and can include a person’s age, gender, race, income, education and employment status.

2. Psychographics:

Refers to data regarding consumers’ personalities and interests. This includes personality traits, hobbies, lifestyles and values. While this can be harder to obtain, it can dramatically improve the way you engage with your consumers.

3. Behavioral:

Refers to data around consumers’ behaviors across your online and offline touchpoints. This includes transactions, browsing behaviors and interactions with the brand.

4. Geographical:

Refers to data on consumers’ physical locations. This ranges from country, region and city-based data to specific GPS coordinates of a consumer at any point in time. It can also be data regarding the consumer’s proximity to a retail outlet.

Pivoting to a first-party data program

When looking to pivot to first-party data, brands should make a clear roadmap that is explicitly linked to their business goals and objectives. Ananthakrishnan explains that as a first-party data program is a long-term investment, to get started on the journey businesses should clearly define their objectives for the program and identify use cases for first-party data that will help them achieve their objectives.

Adam Ng, founder and CEO of online payment service TrustedMalaysia, explains how first-party data is crucial for personalization: “First-party data can show companies how customers are interacting with their content, how they respond to ads, and more. This will all help [them] make [their] promotions and business better.”

To collect first-party data, he advises brands to invest in as many first-party data sources as possible, while also utilizing tools they may already have like email, SMS, apps and their company website to their advantage.

Actioning voice of the customer and employee data

To offer tailored experiences that sufficiently address both customer and employee pain points, companies must learn to decode both direct and indirect feedback from customer and employees.

Ayelet Mendel-Girin, general head of customer experience at Australian fintech Humm Group, says an integral part of actioning VOC data is helping your business not just to listen to customer voice, but plan, prioritize and act upon it.

It is also important that brands identify the right kind of data and data sources to mine for the experience they wish to create. By noting these sources, brands can get right to the heart of customer and employee sentiment to make crucial business decisions.

Epsilon’s Ananthakrishnan urges companies to not only identify the right kind of data, but also to consider the value of that data. While meeting customer wants and expectations is important, he explains that companies need to understand the value those consumers bring to your brand.

“You will hear direct recommendations to delight consumers as they see it from the grass root level, that gives you a good indication on where the bets are working and where they are not from a customer experience lens,” Ananthakrishnan states.

Also read: VoC in APAC

Reducing customer churn using VOC data

Amelia Maye, voice of the customer lead at Australian superannuation and pension fund AustralianSuper, notes that companies can use VOC feedback to reduce customer churn.

Initially, AustraliaSuper analyzed the numeric data surrounding NPS scores to predict churn. The company found that low-level detractors (0-4 NPS) were much more likely to churn that those who gave higher scores, with those that gave their NPS as zero being 154 percent more likely to churn than those who gave a score of 5-10.

Maye notes that by identifying those most likely to churn, companies can then target insights and feedback given by those who give low NPS scores.

“There is a misconception in many corporations that VOC programs is something extra on the side of core business necessities. If you can prove that the VOC initiatives contribute to less customer churn, you can calculate the dollar sum it has saved the business,” she explains.

By exploring why customers gave a specific low score, businesses can then tackle the specific pain points leading customers to churn.

“You will hear direct recommendations to delight consumers as they see it from the grass root level, that gives you a good indication on where the bets are working and where they are not from a customer experience lens.”

Shivkumar Ananthakrishnan

Director of strategic consulting at Epsilon APAC and MEA

Final remarks

By using the insights gleaned from customer data and analytics to deliver personalized customer experiences to buyers across APAC, brands place themselves in a stronger position to foster customer loyalty. An example of this is J&J Taiwan activating their first-party data to increase customer engagement and boost their customer retention, revenue and profitability.

Implementing proper data management and listening to voice of the customer and employee data to identify pain points and areas of improvement puts brands in a better position to provide tailored, seamless customer experiences. This is seen in AustralianSuper’s case where they utilized direct VOC feedback to reduce customer churn and increase NPS.

To keep up with customer expectations in APAC around personalized service, companies should dedicate themselves to optimizing their data management capabilities to avoid losing their competitive edge.

Read the PDF report here