How one of the greatest retail success stories used data to dominate
Cate Trotter, Insider Trends Head of Insights’ seminar on the future of retail technology included little mention of in-store experience. Instead, it focused on her contention that a move away from broadcast relationships with passive consumers to meaningful dialogues with customers based on their individual needs was the key differentiator to retail brands achieving success in the next 5 years.
A story on Glossier inspired by findings from The Retail Business Technology Expo
‘At Glossier, one of our main goals is to be a data-driven company in order to provide an optimal customer experience.’ Charles André-Bouffard, Remote Software Engineer, Glossier
Cate Trotter, Insider Trends Head of Insights’ seminar on the future of retail technology included little mention of in-store experience. Instead it focused on her contention that a move away from broadcast relationships with passive consumers to meaningful dialogues with customers based on their individual needs was the key differentiator to retail brands achieving success in the next 5 years.
How? Only by adopting a data-driven approach to understanding unique customer engagement can brands truly personalise communications and build a new kind of relationship at scale.
‘Brands that create personalised experiences by integrating advanced digital technologies and proprietary data are seeing revenues increase by 6% to 10%.’ Boston Consulting Group
An example: Cult-favourite ‘Nike of beauty’ brand Glossier, whose 600% YoY growth makes it hard to imagine its humble origins as a blog. Yet whilst their evolution from content to eCommerce platform gave Glossier a head start by fuelling their growth with insights from engaged followers, it also poses a more complicated issue for retailers…
As the most successful brands are generating engagement data through multiple touch points – take Under Armour’s investment in fitness apps and Alibaba’s enviable consumer brand ecosystem as examples – the challenge lies not in collecting but in joining data from an omnichannel strategy to generate actionable insights.
‘As sales increased exponentially year over year, we needed a way to collect multiple metrics in order to understand our customers’ behaviour to allow us to better interact and connect with them.’
The challenges Glossier reference on the road to achieving this, from ‘the possibility of multiple departments fetching their own set of answers without knowing how everything works’ to ‘data residing in multiple places’, are ones we hear time and time again from our own customers.
How are retail brands best placed to overcome this? ‘Attribution modeling’ says this Kissmetrics blog, which goes on to highlight the limitations of first touch, last touch, linear, positional and time decay models on their failure to provide a true picture and cites the need for a ‘custom model’.
At Fospha, we meet this need in three ways:
- Through advanced statistical modeling calculating the fractional value of every touch point on a customers’ path to purchase.
- Through a fully scalable solution designed to fit your businesses output needs, providing a sought after bespoke attribution modeling solution.
- By turning customer data into actionable insights which are meaningful to cross-departmental functions.