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A Journey From Big Data to Small Data
How to use customer behaviours to drive an Omnichannel experience
“Big Data” is a marketing term that has been used extensively over the past decade to emphasise the need to collect, process, and activate the vast, ever-changing, amounts of data available to improve the customer journey and offer a more personalised experience. This caused brands to invest heavily in data-lake technologies to help brands collect, catalogue, and process their data to create actionable insights. The vast majority of these implementations resulted in outdated customer insights as the solutions were mainly batch-oriented and did not quickly respond to fast-moving customer intent signals due to the technology constraints of the time.
In today’s hyper-connected world, people interact in real-time with brands through multiple offline and online touchpoints. People now expect highly personalised, connected experiences with brands that are aligned to their intent, interests, and values. These interactions create a treasure trove of data that can be leveraged to gain valuable insights and provide a deeply personalised customer journey. The resulting data signals, often referred to as “small data”, provide a wealth of information about customer preferences, behaviours, and interests.
By collecting and analysing these data signals, companies can gain a competitive edge by using these insights to personalise their marketing efforts and improve customer experiences, resulting in increased brand loyalty and revenue. Small data signals can come from multiple channels within the client’s ecosystem, both in the owned (physical spaces, email, app, website) and paid space (social media, video, connected TV, etc). These signals need to be collected, aggregated, and attached to customer profiles in real-time to deliver on the client expectations that in turn deliver stellar business results. (See our Heathrow case study.)
Organisations need to embark on a radical rethinking of their data and technology operating models if they are to deliver on customer needs and future-proof the overall experience to acquire, grow, and retain more customers. Like any transformation initiative, several focus areas need to take centre stage in the process to ensure the changes deliver on the business vision and objectives.
Omnichannel and Personalisation Roadmap
Setting a clear roadmap helps deliver speed-to-value for the business. Personalisation and channel enablement must be prioritised for high-value and low-complexity use cases that are relevant to the organisation as opposed to strictly a value or complexity-based approach. Delivering on a crawl-walk-run roadmap is far more impactful for the organisation as opposed to standing still for the extended period required for a “Big Bang” approach. For example, depending on the industry, web personalisation use cases using behavioural data directly from the website can help deliver the most value with the least amount of integration effort and as such are a very good first step for organisations to start on their personalisation maturity journey.
Data Strategy
Following the definition of the personalisation roadmap, businesses need to evaluate their data landscape and identify the key data systems that will deliver the data to fuel the roadmap. Typically, this process will help uncover organisational gaps around data availability, recency, accuracy, governance and documentation. Early mitigation of these gaps will help in the seamless delivery of the strategic objectives and help provide an additional dimension in the use case delivery prioritisation process.
A “data fabric” approach is recommended for the data strategy definition. Systems should connect to other platforms and freely exchange data without a middleware layer to broker the exchange which adds latency and complexity to the landscape. This will ensure the delivery of the required data to the right systems to enable data democratisation and foster a data-driven approach.
Technology Assessment
After the data strategy is developed, next is assessing the technology systems that host, process, analyse and activate data across the organisation. This thorough technology assessment ensures lacklustre systems are identified, and a roadmap to replace them is established. Most businesses prefer a vendor-based approach to capitalise on efficiencies and benefit from a product roadmap. However, this approach requires robust due diligence with clearly outlined scoring criteria aligned to organisational objectives.
Governance and Permission
Privacy is a key consideration with a key focus on the regulatory framework that applies to the jurisdictions companies operate in. Organisations have focused on regulatory requirements (e.g., GDPR, CCPA) and have delivered key improvements in areas around data privacy, accessibility, and portability. A data governance framework that adheres to local requirements is key to ensuring compliance. In the context of personalisation, an additional dimension comes into play – customer permission.
The legacy approach to gathering customer permission at the broadest possible level (e.g., marketing opt-in) is no longer considered best practise and might hamper the ability to execute use cases that require data analysis, profiling, and segmentation. A full audit of the governance around data and associated terms and conditions is important so issues that prevent use case activation can be addressed.
Invest in the Right CDP
Customer data platforms (CDPs) provide the ability to process data at scale by joining offline data with online and behavioural signals. CDPs unify customer data across all channels, including email, social media, website, and mobile app, creating a 360-degree view of the customer. By leveraging the power of CDPs, companies can deliver a seamless omnichannel personalization experience that helps drive brand loyalty and value for the customer. That being said, not all CDPs are created equal. Organisations need to ensure they invest in a platform that offers end-to-end real-time capability including the ingestion, unification, processing, and finally activation of the customer data. The utility of a CDP platform is diminished if profiles are unified and small data signals are aggregated only once a day, which results in “stale” customer details and insights. Adopting a CDP also ensures organisations can reap the rewards from product innovations that can deliver additional value to the business. The advent of AI capabilities in leading CDPs over the last year demonstrates the advantages. Innovation is delivered at breakneck speed with capabilities in the ML and AI space spanning analytics, audience discovery, segment creation and activation, and, of course, real-time journey optimisation.
Investing in the right platform that delivers on organisational requirements but also has a robust roadmap is the cornerstone of today’s marketing ecosystem.
Where to Start
Defining the strategic vision with a focus on the areas outlined above is the key first step in the process. Delivering a personalised customer experience is an ongoing endeavour that requires organisations to deploy the required capabilities with a well-defined measurement framework. That way they can optimise the customer journey in response to customer signals and personalisation variant effectiveness. After all, technology allows brands to deliver the age-old marketing mantra – the right message … at the right time … to the right audience … through the right channel.
