Designing Experiences For Data Posted on | WARC


Why we should be designing experiences for data rather than people

Designing experiences for data not people should now be an industry norm, argue MullenLowe Group APAC’s Jonathan Hart and James Hollow – we can no long reason our way into strategies or creative directions when we have the simultaneous ability to empirically create insight and test our assumptions.

Using data to support what is already believed is a direct betrayal of the legacy of science that created this system that allows data to be created, captured and analysed. Integrating data into the existing process is not the answer, nor is including data as another ‘perspective’.

As marketing organizations, we need to disrupt our own approaches by incorporating data creation at the start of the process to design and build empirical knowledge that can then be tested and continually enriched through subsequent customer interaction. When syndicated data is universally available, only proprietary information can generate category defying insight that can give a brand a competitive advantage.

Today’s most valuable brands understand this and are built through experiences that are connected, customer-centric, and refined over time using intelligence derived from empirical observation. The use of behavioural data has proven to be the strongest signal of preference, the most reliable method of identifying motivation, the clearest measure of satisfaction and the best predictor of future behaviour. When this data is created with purpose and intent, it enables radical ways of accelerating growth.

Amazon is one such brand built on empirical behavioural insight. It designed Amazon Go, a cash-free convenience store launched last year, as a lab for observing customer behaviour dynamics such as pricing, placement, layout and offers, with insights applied to its Whole Foods store network and future formats.

Most companies lose sight of the customer’s decision-making process once they leave owned properties. US-based Progressive Insurance has recognized this, and features competitor policy and quotes on their site, allowing them to create data about which policy configurations customers ultimately choose. As this dataset also contains information about who did not choose their policies, it creates a rich dataset for predictive analytics to determine things like consideration sets, price sensitivity and the importance of individual policy features.

It is now possible to capture and analyse customer data at an increased granularity, forcing brands to move away from cohorts and focus on single customers. In addition, new technology has created the ability to orchestrate functionality and personalize content at the individual customer level across every interaction with a brand.

By focusing on ‘the customer’ not ‘customers’, data-driven disruptor brands are rapidly coming to dominate previously well protected markets, while traditional consumer goods giants have seen their business models so threatened by D2C brands that they have acquired the disruptors, as with Unilever’s acquisition of Dollar Shave Club and Edgewell Personal Care’s acquisition of Harry’s.

In APAC the rapidly evolving digital payment space is a microcosm of data-driven disruption. Even in developed markets, disruptors like Australia’s Afterpay are using sophisticated needs-based behavioural clusters to refine its service in granular ways to reflect behaviour driven by different attitudes towards credit. The brand is expanding overseas aggressively, its confidence underpinned by this proprietary insight.

Payment service Paidy, which started in Japan but already has operations in Taiwan, is based on analysis of users’ credit scores to provide frictionless payment across a wide range of merchant platforms. It is another disruptor that is now creating unique types of customer data to inform a differentiated product and marketing strategy.

If agencies want to remain relevant to data-driven brands like these then they too need to make radical changes in processes and mindsets to ensure their survival. Agencies must organise themselves around the customer journey. This means we stop planning for campaigns, channels and platforms and start planning for content, orchestration and interactions.

We cannot and should not rely on latent data created by platform and media activity in which we search for a proverbial ‘needle’. Nor can we advocate for grabbing any data in any way to join the big data trend, not least because data comes with costs and creates new liabilities that can be crippling.

Instead, we need to embrace a strategic data approach that generates information about each customer, their preferences and their motivations, so that we can deliver a better brand experience to them in that moment and in the future.

This approach, designing for data creation, may sound like it is putting the machine first and the human second, but it is in fact the one that most empowers the role of creativity and human insight. It provides a much more informed and sophisticated platform from which to make brave decisions and take bold actions.

The idea of designing for data creation may seem like a leap for many, but the first step is as simple as asking:

  • What data will this experience create that will usefully inform future decisions?
  • How will this data then be activated as part of the experience

The answers to these questions, alongside other elements of an experience, puts experience design in lock-step with data strategy.

Secondly, an honest look at the analytical resources available may reveal the critical difference between what has long passed for “analytics” in our industry versus what is needed. The former is based on the passive practices of reporting and dashboarding fed by data generated from generic tagging exercises. The latter by the inquisitive practices of data scientists and professional analysts armed with techniques such as predictive modelling and machine learning-based clustering techniques that enables answers to questions posed at the planning phase.

So yes, the implications of this new paradigm require reform of both processes and talent strategies, but it really is the only proven route to creating superior customer experiences that will lead to sustained advantage.

James Hollow, CEO, MullenLowe Group Japan
Jonathan Hart, Head of Data Science & Analytics, MullenLowe Group APAC 

This article was originally published on WARC