Data Orchestration Crucial for Better Online Customer Experience

Joseph Suriya, Director, Marketing, Tealium
Joseph Suriya, Director, Marketing, Tealium

What are the biggest changes you have seen in digital technology across APAC over the past 10 years?

There is greater customer demand for first-rate user experiences compared to a decade ago. Brands have to evolve their strategies to keep up with the customer, providing seamless interactions and a consistent experience across a wide range of platforms. This is resulting in marketers shifting their focus from the transaction to the experience, where the customer and their lifetime engagement with the brand are at the centre of every marketing strategy.

From a technological viewpoint, this customer-centric focus requires marketers to bring together the vast number of digital solutions used to optimize the customer journey over the last few years into a more manageable stack. It is also leading to an increased focus on granular first-party data to help understand the customer and their needs through detailed profiles. Where brands may once have acted on instinct, or what they felt was right, they now use data to ensure they are making the best decisions.

How has regulation such as GDPR impacted businesses in APAC and their ability to manage and use consumer data?

GDPR covers any organization that handles the data of EU citizens — and in today’s global economy, this means it impacts most companies; including those in APAC. Yet attitudes towards the regulation remain mixed. On the one hand, there is an appreciation that complying with the new rules brings many advantages: by giving individuals power over data and more visibility into usage, the GDPR can reduce privacy concerns, increase trust, and build lasting customer relationships. But on the other, following legislation that goes beyond regional law is difficult. Ahead of enforcement, more than half of firms in Singapore weren’t ready and one month later, only a quarter of Japanese companies had met fundamental rules.

Businesses must keep working towards compliance and recognize that the GDPR doesn’t necessarily require a total internal overhaul – a common misconception. Companies will often find they can make existing systems adherent by connecting them, instead of replacing them.

What can businesses do to better leverage the explosion of customer data we’ve seen as a result of the digital age?

In short, it means putting the data created by greater connectivity into action. As adoption of smartphones, tablets and wearable technology has grown — with 8.6 billion devices set to be in use across Asia by 2020 — the quantity of data produced by consumers has exploded. So, brands now have a larger pool of transactional, demographic, and behavioural information to draw upon than ever. But before they can harness this data as a basis for tailoring customer experiences, companies need to translate it into cohesive and usable insight. And this is no simple task; in fact, 34% of marketers state that the difficulty of unifying data sources is the greatest barrier to better understanding customer journeys.

The evolution from brands talking about DMPs to CDPs as their primary consumer data tool has been very apparent over the past few years in marketing. What’s the difference between these platforms from your perspective?

The answer to this lies in the history of both tools. DMPs were originally designed to gather information about online activity, categorize it and build audience segments, which then fed into other systems such as DSPs. As the complexity of consumer journeys increased, DMPs tried to meet the need for a persistent view of individuals. But because they were only able to store third-party cookies, it was difficult to effectively resolve the many identifiers created by different channels and devices. And this is where CDPs come in. CDPs can collate, synchronize, and activate data from varied sources: generating one centralized store of insight marketers can use to understand and trace individuals across touchpoints. This results in the capability to take consistent and relevant action in real time across an organization’s entire tech stack from a universal data foundation.

This isn’t, however, to say CDPs supersede DMPs; the two can be effective when used in partnership. For example, a CDP can give marketers a ‘single source of truth’ and a complete picture of customer journeys. This insight can then be shared with DMPs to produce better audience segments that ultimately boost ad targeting precision and results.

What can brands do to get closer to the holy grail of a true 360-degree view of their customers in real time?

If brands want to obtain a real-time 360-degree customer view, they must ensure data is well orchestrated. And this means following several core stages that aim to continuously harmonize data. To start, customer interaction data must be collected from every possible source such as apps, sites, and stores combined into a single layer, standardized, and cleansed. Simultaneously, this information should also be stitched and enriched; with smart tools used to assess incoming data and transform it into individual profiles that are linked with data from particular devices, once owners are identified.

Because all of this is done in real time, the end product is a complete up-to-date customer profile. Exactly the insight marketers need to understand customers and deliver engaging experiences across channels. Though it’s worth noting that to accommodate ever-evolving individual preferences and habits, they must also check that their orchestration platform integrates with other systems and constantly ingests new data.

How are AI and machine learning changing the way brands engage with their customers?

AI and subsets such as machine learning are already beginning to broaden the horizons of customer interaction by adding new channels to the mix. The best-known examples of this are chatbots — used to provide instant 24/7 services by major brands from Starbucks to MasterCard — and the growing presence of digital tools in physical stores. As recently seen with the Guess and Alibaba FashionAI store, which trialled blending real shopping and a range of intelligent tech; facial recognition, smart touchscreen mirrors, RFID-tagged items.

But it’s also important to highlight the applications that are making a sizeable difference to customer experience behind the scenes. Machine learning, in particular, is fuelling advances in data processing; giving brands the means to collect and analyze customer information at scale, and extract valuable insight. This in turn, means data can be quickly harnessed to improve interactions by enhancing contextual relevance and personal resonance. So long as marketers are taking adequate measures to keep quality and accuracy high, including avoiding bias among the human teams driving AI and data fragmentation.

What are the biggest challenges you see with brands getting to grips with big data in APAC?

One of the most significant challenges is providing communications that keep pace with omnichannel activity. According to a Google study, the majority of APAC consumers prefer to research online and buy in store; with 70% doing so while browsing real shelves. But activity varies by market; Australia and Japan, for example, have large numbers of digital shoppers – especially Japan, where e-commerce revenue is currently more than $80 million.

So, there is no room for archetypes; marketers need all-inclusive insight into the behaviour of specific target audiences. Only by identifying which devices, shopping environments, and ad types work best for individuals can they provide personalized experiences that flow as part of a seamless cross-channel conversation. And that necessitates agile integrated tech, which can be problematic in certain markets that have historically relied on legacy systems. Despite its forward-looking approach to mobile, Japan still tends to use CRM databases that don’t necessarily have the capacity to work with other systems and therefore can’t share data easily.

Finally, how can brands intelligently pull all their data together to build a better, more personalised and more holistic customer experience for 2019 and beyond?

The role intelligent data plays in customer experience will continue to grow as more brands recognize the value of building communications around individuals. Forrester research has shown brands focused on customer experience achieve an annual growth rate of 23% and twice as much return on ad spend — and data is an integral element of this.

But to get every interaction right, brands mustn’t overlook the basics. Constructing a strong foundation of compliant, accurate, objective and perfectly orchestrated data is critical for communications to make a positive impact.

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