By Mike Kiersey, Head of the EMEA Technology Organisation, Boomi
A study conducted in 2022 by leading customer relationship management agency Merkle confirmed what many in the retail industry already knew: personalisation boosts revenue and customer loyalty. 86% of consumers reported that they value personalised offers.
However, despite having some useful data like customer demographics, browsing history, channel preferences, and mobile app usage, smaller retail businesses are not implementing personalisation as efficiently as their larger industry rivals and are failing to deliver personalised messaging over the appropriate channels.
The question is, why?
The reason this is so common is that the data small retailers have is often fragmented, inconsistent, and spread across multiple separate systems, preventing access to an integrated and holistic overview of their customers.
Personalisation Delivers Mixed Results. Here’s Why.
To buck this trend, retailers have explored various methods, including consolidating customer data into a cohesive foundation. Aside from an intricate process, it requires substantial labour and capital, often taking several months for IT teams to integrate data and applications manually. Moreover, if the initial data quality is poor, the rate of off-target messages that negatively impact brand equity increases.
Adding to the complexity is that personalisation initiatives are typically confined to a particular business unit, such as Marketing and Loyalty. Unless data is integrated throughout all business units and the complete omnichannel customer ecosystem, then personalisation outcomes will be mixed at best.
With business applications subject to frequent changes, it is also common for large retailers to use numerous systems for different purposes, such as eCommerce, loyalty, customer service, and merchandising. When these retailers upgrade to newer systems, they need to build their fragile integrations all over again.
Achieving Omnichannel Personalisation
The increasingly advanced integration platform as a service (iPaaS) market is emerging as a compelling solution for addressing these stubborn personalisation challenges.
Leading iPaaS solutions provide retailers with intelligent connectivity and automation to dismantle rigid data silos, accelerate business processes, and unleash the potential of data – all crucial in driving personalisation.
For example, modern, rapidly deployed turnkey solutions provide data frameworks that facilitate the rapid development of personalised omnichannel customer journeys that are comprehensive, consistent, and timely.
Comprehensive. Retailers achieve omnichannel personalisation by collecting customer interaction data from all touchpoints, not just those required for specific functions such as eCommerce or brick-and-mortar stores.
Consistent. Data stored in different applications will always have discrepancies, with customer addresses and even names changing over time. The use of iPaaS data capabilities enables retailers to aggregate, cleanse and enrich isolated data into standardised records, offering unified and accurate visibility.
Timely. Personalisation returns soar when a retailer can do “marketing in the moment” by offering customers deals as they browse products. iPaaS solutions feed personalisation tools with almost real-time user activity data, allowing for direct outreach through multiple channels. The outcome is improved engagement, increased share of wallet, and customer loyalty.
Embedding a data-centric culture
As much as iPaaS solutions can effectively drive personalisation, potential is limited if the retailer’s business culture is not fully immersed in its data.
However, adopting a data-centric culture comes with its own set of difficulties. Outdated systems often do not support modern data analysis tools, and opposition to change amongst employees is common.
The answer to this lies in providing the workforce with relevant training or the onboarding of external partners who specialise in data analytics and culture implementation.
Another option is to review recruitment strategies. Hiring data specialists can enhance understanding of customer behaviour and preferences, allowing for more accurate identification of trends and patterns and more informed decision-making.
Reordering Retail’s Innovation Priorities
Retail industry innovation has traditionally focused on front-end customer experience applications. When the time comes for the C-suite to approve technology investments, this focus often comes at the expense of back-end systems, including integration platforms.
It’s a trend that makes little sense. Front-end applications depend on their integration with other systems within the retail ecosystem, and if overlooked, even the most cutting-edge front-end applications lose their potential.
The importance of embedding data-centric cultures is neglected despite continually evolving customer expectations. It is thus for departmental leads to champion the tools that provide data insights for improved personalisation and for the skilled personnel who can use them.