In 1966 Time Magazine predicted, “remote shopping, though entirely feasible, will flop.” Fifty years on, it’s clear how wrong fortune tellers can be. In the UK, online sales are set to hit £67bn this year — £27bn of which will be absorbed by mobile. While bricks and mortar stores still have strong appeal, consumers have undeniably taken to digital shopping.
Consumer journeys are spread across myriad online and offline touchpoints, leaving behind unique data footprints that can be used to accurately map their ever-changing journeys. So, how can this insight help retailers better understand consumers and what points should they consider to successfully build it into their strategies?
The benefits of a unified data trail
Analysing shopper behaviour isn’t a new concept for retailers. Yet thus far, scope has been limited, with each company only using insight from its own store, website or app. Unified data – information integrated from several sources – enables retailers to gather intelligence on not just its own customers, but on its competitors’ customers as well.
Take Nike, for instance. The sports retailer is facing increasing competition from Adidas in the US, with sales of Adidas’s Superstar trainer resulting in it becoming the top-selling active shoe for the first time in a decade. Mark Palmer, Nike’s CEO, says the brand is now looking to better connect with consumers and differentiate its retail experience from the competition. A unified data strategy could provide Nike with the insights the brand needs to achieve its goals.
For example, our data shows that Adidas is currently experiencing significantly higher footfall on weekdays than Nike in the US. This suggests that Nike will benefit from implementing a strategy to encourage weekday consumers away from Adidas and into Nike stores, such as by serving targeted offers and discounts at an opportune moment. The success of this strategy can be further bolstered by Nike using unified data to understand what consumers are interested in, how they behave across channels, and their demographics.
Ultimately all retailers can benefit from a more extensive range of data sources and the means to tie them together efficiently. As connected devices have transformed the way consumers shop, new methods have emerged to make big data actionable, such as ambient intelligence.
In short, ambient intelligence leverages the capabilities of smart technology, using Artificially Intelligent (AI) tools to enable integrated data analysis. Essentially, the approach entails gathering and assessing data from different environments, such as purchase history, location, social media interactions, and Wi-Fi use. When used with the right data science models, this data produces an all-inclusive picture of individuals, covering their unique needs and preferences.
Mastering cross-channel performance
If retailers want to unlock the full strategic potential of this insight, they must go one step further and combine it with cohesive attribution data.
Too often, performance is measured solely via methods such as last-touch attribution that attribute all credit for conversions to the final point of contact in a consumer’s journey. But, this approach ignores the complex nature of modern paths to purchase. Consequently, it is vital for retail brands to utilise tools that provide a comprehensive understanding of effectiveness.
By far the easiest way to do so is by partnering with platforms that can sync attribution data between online and offline channels, and merge it with consumer insight. This will allow retailers to ascertain the precise impact of marketing messages and promotions across touchpoints. In turn, they will then be able to establish what’s working and what isn’t, and reconfigure strategies accordingly.
For instance, retailers can use in-store visitor and purchase data to judge the efficacy of special promotions and optimise product displays to engage particular shopper segments. Nike, for example, could determine whether consumers who passed OOH screens or received promotional offers to their mobile phones went on to make a correlating purchase from it’s store. This knowledge enables retailers to truly understand what tactics work for their audience, and where spend should be allocated accordingly.
With data becoming increasingly integral to retail success, it is also important for the industry to take note of an upcoming change that will have a significant effect on the way data is managed: the General Data Protection Regulation (GDPR). Due to come into force in May 2018, this new set of data laws introduces several rules for data deployment, as well as privacy protection. Thus, it is essential for retailers to ensure internal data procedures are compliant — in terms of gaining consent for data usage and storage — and carefully vet technology partners to ensure they are adherent.
As Time Magazine’s online shopping skeptic has shown, it’s hard to tell exactly what the future will bring. But data will be always be key. Consumers already want bespoke experiences that flow seamlessly between touchpoints and the bar for quality is constantly rising. In fact, over 50% of consumers expect that by 2020, companies will be able to predict their needs before they even express them.
To keep up with consumers and their evolving demands, retailers will therefore need a unified pool of data that not only enables them to consistently track consumer journeys, but also provides a deep view of individual needs and tastes, and message preferences. To achieve this, retailers must follow in consumers’ example, and embrace the multi-channel world.
Also published in RetailTech News.